Awesome-Transformer-Attention

"A Survey on Multimodal Large Language Models for Autonomous Driving", WACVW, 2024 ( ). [ ][ ]

"Efficient Multimodal Large Language Models: A Survey", arXiv, 2024 ( ). [ ][ ]

"From Sora What We Can See: A Survey of Text-to-Video Generation", arXiv, 2024 ( ). [ ][ ]

"When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models", arXiv, 2024 ( ). [ ][ ]

"Foundation Models for Video Understanding: A Survey", arXiv, 2024 ( ). [ ][ ]

"Vision Mamba: A Comprehensive Survey and Taxonomy", arXiv, 2024 ( ). [ ][ ]

"Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond", arXiv, 2024 ( ). [ ][ ]

"Video Diffusion Models: A Survey", arXiv, 2024 ( ). [ ][ ]

"Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras", arXiv, 2024 ( ). [ ]

"Hallucination of Multimodal Large Language Models: A Survey", arXiv, 2024 ( ). [ ][ ]

"A Survey on Vision Mamba: Models, Applications and Challenges", arXiv, 2024 ( ). [ ][ ]

"State Space Model for New-Generation Network Alternative to Transformers: A Survey", arXiv, 2024 ( ). [ ][ ]

"Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions", arXiv, 2024 ( ). [ ]

"From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models", arXiv, 2024 ( ). [ ][ ]

"Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey", arXiv, 2024 ( ). [ ]

"Sora as an AGI World Model? A Complete Survey on Text-to-Video Generation", arXiv, 2024 ( ). [ ]

"Controllable Generation with Text-to-Image Diffusion Models: A Survey", arXiv, 2024 ( ). [ ][ ]

"Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models", arXiv, 2024 ( ). [ ][ ]

"Large Multimodal Agents: A Survey", arXiv, 2024 ( ). [ ][ ]

"Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey", arXiv, 2024 ( ). [ ][ ]

"Vision-Language Navigation with Embodied Intelligence: A Survey", arXiv, 2024 ( ). [ ]

"The (R)Evolution of Multimodal Large Language Models: A Survey", arXiv, 2024 ( ). [ ]

"Masked Modeling for Self-supervised Representation Learning on Vision and Beyond", arXiv, 2024 ( ). [ ][ ]

"Transformer for Object Re-Identification: A Survey", arXiv, 2024 ( ). [ ]

"Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities", arXiv, 2024 ( ). [ ][ ]

"MM-LLMs: Recent Advances in MultiModal Large Language Models", arXiv, 2024 ( ). [ ]

"From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities", arXiv, 2024 ( ). [ ]

"A Survey on Hallucination in Large Vision-Language Models", arXiv, 2024 ( ). [ ]

"A Survey for Foundation Models in Autonomous Driving", arXiv, 2024 ( ). [ ]

"A Survey on Transformer Compression", arXiv, 2024 ( ). [ ]

"Vision + Language Applications: A Survey", CVPRW, 2023 ( ). [ ][ ]

"Multimodal Learning With Transformers: A Survey", TPAMI, 2023 ( ). [ ]

"A Survey of Visual Transformers", TNNLS, 2023 ( ). [ ][ ]

"Video Understanding with Large Language Models: A Survey", arXiv, 2023 ( ). [ ][ ]

"Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey", arXiv, 2023 ( ). [ ]

"A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook", arXiv, 2023 ( ). [ ][ ]

"A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise", arXiv, 2023 ( ). [ ] ]

"Towards the Unification of Generative and Discriminative Visual Foundation Model: A Survey", arXiv, 2023 ( ). [ ]

"Explainability of Vision Transformers: A Comprehensive Review and New Perspectives", arXiv, 2023 ( ). [ ]

"Vision-Language Instruction Tuning: A Review and Analysis", arXiv, 2023 ( ). [ ][ ]

"Understanding Video Transformers for Segmentation: A Survey of Application and Interpretability", arXiv, 2023 ( ). [ ]

"Unsupervised Object Localization in the Era of Self-Supervised ViTs: A Survey", arXiv, 2023 ( ). [ ][ ]

"A Survey on Video Diffusion Models", arXiv, 2023 ( ). [ ][ ]

"The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)", arXiv, 2023 ( ). [ ]

"Multimodal Foundation Models: From Specialists to General-Purpose Assistants", arXiv, 2023 ( ). [ ]

"Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-Art", arXiv, 2023 ( ). [ ]

"RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model", arXiv, 2023 ( ). [ ]

"A survey on efficient vision transformers: algorithms, techniques, and performance benchmarking", arXiv, 2023 ( ). [ ]

"From CNN to Transformer: A Review of Medical Image Segmentation Models", arXiv, 2023 ( ). [ ]

"Foundational Models Defining a New Era in Vision: A Survey and Outlook", arXiv, 2023 ( ). [ ][ ]

"A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models", arXiv, 2023 ( ). [ ]

"Robust Visual Question Answering: Datasets, Methods, and Future Challenges", arXiv, 2023 ( ). [ ]

"A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future", arXiv, 2023 ( ). [ ]

"Transformers in Reinforcement Learning: A Survey", arXiv, 2023 ( ). [ ]

"Vision Language Transformers: A Survey", arXiv, 2023 ( ). [ ]

"Towards Open Vocabulary Learning: A Survey", arXiv, 2023 ( ). [ ][ ]

"Large Multimodal Models: Notes on CVPR 2023 Tutorial", arXiv, 2023 ( ). [ ]

"A Survey on Multimodal Large Language Models", arXiv, 2023 ( ). [ ][ ]

"2D Object Detection with Transformers: A Review", arXiv, 2023 ( ). [ ]

"Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature", arXiv, 2023 ( ). [ ]

"Vision-Language Models in Remote Sensing: Current Progress and Future Trends", arXiv, 2023 ( ). [ ]

"Visual Tuning", arXiv, 2023 ( ). [ ]

"Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey", arXiv, 2023 ( ). [ ]

"Semantic Segmentation using Vision Transformers: A survey", arXiv, 2023 ( ). [ ]

"A Review of Deep Learning for Video Captioning", arXiv, 2023 ( ). [ ]

"Transformer-Based Visual Segmentation: A Survey", arXiv, 2023 ( ). [ ][ ]

"Vision-Language Models for Vision Tasks: A Survey", arXiv, 2023 ( ). [ ][ ]

"Text-to-image Diffusion Model in Generative AI: A Survey", arXiv, 2023 ( ). [ ]

"Foundation Models for Decision Making: Problems, Methods, and Opportunities", arXiv, 2023 ( ). [ ]

"Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review", arXiv, 2023 ( ). [ ][ ]

"Efficiency 360: Efficient Vision Transformers", arXiv, 2023 ( ). [ ][ ]

"Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Survey", arXiv, 2023 ( ). [ ]

"Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey", arXiv, 2023 ( ). [ ][ ]

"A Survey on Visual Transformer", TPAMI, 2022 ( ). [ ]

"Attention mechanisms in computer vision: A survey", Computational Visual Media, 2022 ( ). [ ][ ][ ]

"A Comprehensive Study of Vision Transformers on Dense Prediction Tasks", VISAP, 2022 ( ). [ ]

"Vision-and-Language Pretrained Models: A Survey", IJCAI, 2022 ( ). [ ]

"Vision Transformers in Medical Imaging: A Review", arXiv, 2022 ( ). [ ]

"A Comprehensive Survey of Transformers for Computer Vision", arXiv, 2022 ( ). [ ]

"Vision-Language Pre-training: Basics, Recent Advances, and Future Trends", arXiv, 2022 ( ). [ ]

"Vision+X: A Survey on Multimodal Learning in the Light of Data", arXiv, 2022 ( ). [ ]

"Vision Transformers for Action Recognition: A Survey", arXiv, 2022 ( ). [ ]

"VLP: A Survey on Vision-Language Pre-training", arXiv, 2022 ( ). [ ]

"Transformers in Remote Sensing: A Survey", arXiv, 2022 ( ). [ ][ ]

"Medical image analysis based on transformer: A Review", arXiv, 2022 ( ). [ ]

"3D Vision with Transformers: A Survey", arXiv, 2022 ( ). [ ][ ]

"Vision Transformers: State of the Art and Research Challenges", arXiv, 2022 ( ). [ ]

"Transformers in Medical Imaging: A Survey", arXiv, 2022 ( ). [ ][ ]

"Multimodal Learning with Transformers: A Survey", arXiv, 2022 ( ). [ ]

"Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives", arXiv, 2022 ( ). [ ]

"Transformers in 3D Point Clouds: A Survey", arXiv, 2022 ( ). [ ]

"A survey on attention mechanisms for medical applications: are we moving towards better algorithms?", arXiv, 2022 ( ). [ ]

"Efficient Transformers: A Survey", arXiv, 2022 ( ). [ ]

"Are we ready for a new paradigm shift? A Survey on Visual Deep MLP", arXiv, 2022 ( ). [ ]

"Vision Transformers in Medical Computer Vision - A Contemplative Retrospection", arXiv, 2022 ( ). [ ]

"Video Transformers: A Survey", arXiv, 2022 ( ). [ ]

"Transformers in Medical Image Analysis: A Review", arXiv, 2022 ( ). [ ]

"Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work", arXiv, 2022 ( ). [ ]

"Transformers Meet Visual Learning Understanding: A Comprehensive Review", arXiv, 2022 ( ). [ ]

"Image Captioning In the Transformer Age", arXiv, 2022 ( ). [ ][ ]

"Visual Attention Methods in Deep Learning: An In-Depth Survey", arXiv, 2022 ( ). [ ]

"Transformers in Vision: A Survey", ACM Computing Surveys, 2021 ( ). [ ]

"Survey: Transformer based Video-Language Pre-training", arXiv, 2021 ( ). [ ]

"A Survey of Transformers", arXiv, 2021 ( ). [ ]

"Attention mechanisms and deep learning for machine vision: A survey of the state of the art", arXiv, 2021 ( ). [ ]

: "Local Relation Networks for Image Recognition", ICCV, 2019 ( ). [ ][ ]

: "Stand-Alone Self-Attention in Vision Models", NeurIPS, 2019 ( ). [ ][ ][ ]

: "Axial Attention in Multidimensional Transformers", arXiv, 2019 ( ). [ ][ ]

: "Exploring Self-attention for Image Recognition", CVPR, 2020 ( ). [ ][ ]

: "Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation", ECCV, 2020 ( ). [ ][ ]

: "Global Self-Attention Networks for Image Recognition", arXiv, 2020 ( ). [ ][ ]

: "Scaling Local Self-Attention For Parameter Efficient Visual Backbones", CVPR, 2021 ( ). [ ][ ]

: "Contextual Transformer Networks for Visual Recognition", CVPRW, 2021 ( ). [ ][ ]

: "Vision Transformers with Hierarchical Attention", arXiv, 2022 ( ). [ ][ ]

: "Attention Augmented Convolutional Networks", ICCV, 2019 ( ). [ ][ ][ ]

: "Global Context Networks", ICCVW, 2019 (& TPAMI 2020) ( ). [ ][ ]

: "LambdaNetworks: Modeling long-range Interactions without Attention", ICLR, 2021 ( ). [ ][ ][ ]

: "Bottleneck Transformers for Visual Recognition", CVPR, 2021 ( ). [ ][ ][ ]

: "Gaussian Context Transformer", CVPR, 2021 ( ). [ ]

: "CoAtNet: Marrying Convolution and Attention for All Data Sizes", NeurIPS, 2021 ( ). [ ]

: "On the Integration of Self-Attention and Convolution", CVPR, 2022 ( ). [ ][ ]

: "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale", ICLR, 2021 ( ). [ ][ ][ ][ ]

: "Perceiver: General Perception with Iterative Attention", ICML, 2021 ( ). [ ][ ]

: "Rethinking Spatial Dimensions of Vision Transformers", ICCV, 2021 ( ). [ ][ ]

: "Visual Transformers: Where Do Transformers Really Belong in Vision Models?", ICCV, 2021 ( ). [ ][ ]

: "Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions", ICCV, 2021 ( ). [ ][ ]

: "Rethinking and Improving Relative Position Encoding for Vision Transformer", ICCV, 2021 ( ). [ ][ ]

: "Going deeper with Image Transformers", ICCV, 2021 ( ). [ ][ ]

: "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows", ICCV, 2021 ( ). [ ][ ][ ]

: "Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet", ICCV, 2021 ( ). [ ][ ]

: "Leveraging Batch Normalization for Vision Transformers", ICCVW, 2021 ( ). [ ]

: "DPT: Deformable Patch-based Transformer for Visual Recognition", ACMMM, 2021 ( ). [ ][ ]

: "Focal Attention for Long-Range Interactions in Vision Transformers", NeurIPS, 2021 ( ). [ ][ ]

: "XCiT: Cross-Covariance Image Transformers", NeurIPS, 2021 ( ). [ ]

: "Twins: Revisiting Spatial Attention Design in Vision Transformers", NeurIPS, 2021 ( ). [ ][ ]

: "Blending Anti-Aliasing into Vision Transformer", NeurIPS, 2021 ( ). [ ][ ]

: "Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length", NeurIPS, 2021 ( ). [ ][ ]

: "Augmented Shortcuts for Vision Transformers", NeurIPS, 2021 ( ). [ ]

: "Transformer in Transformer", NeurIPS, 2021 ( ). [ ][ ][ ]

: "ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias", NeurIPS, 2021 ( ). [ ][ ]

: "DeepViT: Towards Deeper Vision Transformer", arXiv, 2021 ( ). [ ][ ]

: "So-ViT: Mind Visual Tokens for Vision Transformer", arXiv, 2021 ( ). [ ][ ]

: "All Tokens Matter: Token Labeling for Training Better Vision Transformers", NeurIPS, 2021 ( ). [ ][ ]

: "Aggregating Nested Transformers", arXiv, 2021 ( ). [ ][ ]

: "KVT: k-NN Attention for Boosting Vision Transformers", arXiv, 2021 ( ). [ ]

: "Refiner: Refining Self-attention for Vision Transformers", arXiv, 2021 ( ). [ ][ ]

: "Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer", arXiv, 2021 ( ). [ ]

: "CAT: Cross Attention in Vision Transformer", arXiv, 2021 ( ). [ ][ ]

: "Scaling Vision with Sparse Mixture of Experts", arXiv, 2021 ( ). [ ]

: "P2T: Pyramid Pooling Transformer for Scene Understanding", arXiv, 2021 ( ). [ ]

: "PVTv2: Improved Baselines with Pyramid Vision Transformer", arXiv, 2021 ( ). [ ][ ]

: "Local-to-Global Self-Attention in Vision Transformers", arXiv, 2021 ( ). [ ]

: "Visual Parser: Representing Part-whole Hierarchies with Transformers", arXiv, 2021 ( ). [ ]

: "Scaled ReLU Matters for Training Vision Transformers", AAAI, 2022 ( ). [ ]

: "Less is More: Pay Less Attention in Vision Transformers", AAAI, 2022 ( ). [ ][ ]

: "Dynamic Token Normalization Improves Vision Transformer", ICLR, 2022 ( ). [ ][ ]

: "RegionViT: Regional-to-Local Attention for Vision Transformers", ICLR, 2022 ( ). [ ][ ]

: "CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention", ICLR, 2022 ( ). [ ][ ]

: "Scaling the Depth of Vision Transformers via the Fourier Domain Analysis", ICLR, 2022 ( ). [ ]

: "Scaling Vision Transformers", CVPR, 2022 ( ). [ ]

: "CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows", CVPR, 2022 ( ). [ ][ ]

: "MPViT: Multi-Path Vision Transformer for Dense Prediction", CVPR, 2022 ( ). [ ][ ]

: "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy", CVPR, 2022 ( ). [ ][ ]

: "Beyond Fixation: Dynamic Window Visual Transformer", CVPR, 2022 ( ). [ ][ ]

: "MixFormer: Mixing Features across Windows and Dimensions", CVPR, 2022 ( ). [ ][ ]

: "Vision Transformer with Deformable Attention", CVPR, 2022 ( ). [ ][ ]

: "Swin Transformer V2: Scaling Up Capacity and Resolution", CVPR, 2022 ( ). [ ][ ]

: "MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens", CVPR, 2022 ( ). [ ][ ]

: "NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition", CVPR, 2022 ( ). [ ][ ]

: "Shunted Self-Attention via Multi-Scale Token Aggregation", CVPR, 2022 ( ). [ ][ ]

: "PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture", CVPRW, 2022 ( ). [ ][ ]

: "X-ViT: High Performance Linear Vision Transformer without Softmax", CVPRW, 2022 ( ). [ ]

: "ReMixer: Object-aware Mixing Layer for Vision Transformers", CVPRW, 2022 ( ). [ ][ ]

: "Unified Normalization for Accelerating and Stabilizing Transformers", ACMMM, 2022 ( ). [ ][ ]

: "Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning", ECCV, 2022 ( ). [ ][ ]

: "DaViT: Dual Attention Vision Transformers", ECCV, 2022 ( ). [ ][ ]

: "ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer", ECCV, 2022 ( ). [ ]

: "MaxViT: Multi-Axis Vision Transformer", ECCV, 2022 ( ). [ ][ ]

: "VSA: Learning Varied-Size Window Attention in Vision Transformers", ECCV, 2022 ( ). [ ][ ]

: "Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning", NeurIPS, 2022 ( ). [ ]

: "Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization", NeurIPS, 2022 ( ). [ ]

: "Peripheral Vision Transformer", NeurIPS, 2022 ( ). [ ]

: "Fast Vision Transformers with HiLo Attention", NeurIPS, 2022 ( ). [ ][ ]

: "BViT: Broad Attention based Vision Transformer", arXiv, 2022 ( ). [ ]

: "O-ViT: Orthogonal Vision Transformer", arXiv, 2022 ( ). [ ]

: "Aggregating Global Features into Local Vision Transformer", arXiv, 2022 ( ). [ ][ ]

: "BOAT: Bilateral Local Attention Vision Transformer", arXiv, 2022 ( ). [ ]

: "ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond", arXiv, 2022 ( ). [ ]

: "Hierarchical Perceiver", arXiv, 2022 ( ). [ ]

: "Learning to Merge Tokens in Vision Transformers", arXiv, 2022 ( ). [ ]

: "Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention", arXiv, 2022 ( ). [ ]

: "Neighborhood Attention Transformer", arXiv, 2022 ( ). [ ][ ]

: "Adaptive Split-Fusion Transformer", arXiv, 2022 ( ). [ ][ ]

: "SP-ViT: Learning 2D Spatial Priors for Vision Transformers", arXiv, 2022 ( ). [ ]

: "EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithm", arXiv, 2022 ( ). [ ]

: "Rethinking Query-Key Pairwise Interactions in Vision Transformers", arXiv, 2022 ( ). [ ]

: "Dual Vision Transformer", arXiv, 2022 ( ). [ ][ ]

: "Multi-manifold Attention for Vision Transformers", arXiv, 2022 ( ). [ ]

: "MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition", arXiv, 2022 ( ). [ ]

: "Axially Expanded Windows for Local-Global Interaction in Vision Transformers", arXiv, 2022 ( ). [ ]

: "Grafting Vision Transformers", arXiv, 2022 ( ). [ ]

: "Rethinking Hierarchicies in Pre-trained Plain Vision Transformer", arXiv, 2022 ( ). [ ]

: "The Lottery Ticket Hypothesis for Vision Transformers", arXiv, 2022 ( ). [ ]

: "Token Transformer: Can class token help window-based transformer build better long-range interactions?", arXiv, 2022 ( ). [ ]

: "INTERN: A New Learning Paradigm Towards General Vision", arXiv, 2022 ( ). [ ][ ]

: "Group Generalized Mean Pooling for Vision Transformer", arXiv, 2022 ( ). [ ]

: "GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation", ICLR, 2023 ( ). [ ][ ]

: "Conditional Positional Encodings for Vision Transformers", ICLR, 2023 ( ). [ ][ ]

: "LipsFormer: Introducing Lipschitz Continuity to Vision Transformers", ICLR, 2023 ( ). [ ][ ]

: "BiFormer: Vision Transformer with Bi-Level Routing Attention", CVPR, 2023 ( ). [ ][ ]

: "Top-Down Visual Attention from Analysis by Synthesis", CVPR, 2023 ( ). [ ][ ][ ]

: "Visual Dependency Transformers: Dependency Tree Emerges From Reversed Attention", CVPR, 2023 ( ). [ ][ ]

: "ResFormer: Scaling ViTs with Multi-Resolution Training", CVPR, 2023 ( ). [ ][ ]

: "Vision Transformer with Super Token Sampling", CVPR, 2023 ( ). [ ]

: "PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers", CVPR, 2023 ( ). [ ][ ]

: "Global Context Vision Transformers", ICML, 2023 ( ). [ ][ ]

: "MAGNETO: A Foundation Transformer", ICML, 2023 ( ). [ ]

: "Fcaformer: Forward Cross Attention in Hybrid Vision Transformer", ICCV, 2023 ( ). [ ][ ]

: "Scale-Aware Modulation Meet Transformer", ICCV, 2023 ( ). [ ][ ]

: "FLatten Transformer: Vision Transformer using Focused Linear Attention", ICCV, 2023 ( ). [ ][ ]

: "Revisiting Vision Transformer from the View of Path Ensemble", ICCV, 2023 ( ). [ ]

: "SG-Former: Self-guided Transformer with Evolving Token Reallocation", ICCV, 2023 ( ). [ ][ ]

: "Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?", ICCV, 2023 ( ). [ ]

: "LaPE: Layer-adaptive Position Embedding for Vision Transformers with Independent Layer Normalization", ICCV, 2023 ( ). [ ][ ]

: "Scratching Visual Transformer's Back with Uniform Attention", ICCV, 2023 ( ). [ ]

: "Fully Attentional Networks with Self-emerging Token Labeling", ICCV, 2023 ( ). [ ][ ]

: "ClusterFormer: Clustering As A Universal Visual Learner", NeurIPS, 2023 ( ). [ ]

: "Scattering Vision Transformer: Spectral Mixing Matters", NeurIPS, 2023 ( ). [ ][ ][ ]

: "CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale Attention", arXiv, 2023 ( ). [ ][ ]

: "Vision Transformer with Quadrangle Attention", arXiv, 2023 ( ). [ ][ ]

: "ViT-Calibrator: Decision Stream Calibration for Vision Transformer", arXiv, 2023 ( ). [ ]

: "SpectFormer: Frequency and Attention is what you need in a Vision Transformer", arXiv, 2023 ( ). [ ][ ][ ]

: "UniNeXt: Exploring A Unified Architecture for Vision Recognition", arXiv, 2023 ( ). [ ]

: "CageViT: Convolutional Activation Guided Efficient Vision Transformer", arXiv, 2023 ( ). [ ]

: "Making Vision Transformers Truly Shift-Equivariant", arXiv, 2023 ( ). [ ]

: "2-D SSM: A General Spatial Layer for Visual Transformers", arXiv, 2023 ( ). [ ][ ]

: "Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution", NeurIPS, 2023 ( ). [ ]

: "DAT++: Spatially Dynamic Vision Transformer with Deformable Attention", arXiv, 2023 ( ). [ ][ ]

: "Replacing softmax with ReLU in Vision Transformers", arXiv, 2023 ( ). [ ]

: "RMT: Retentive Networks Meet Vision Transformers", arXiv, 2023 ( ). [ ]

: "Vision Transformers Need Registers", arXiv, 2023 ( ). [ ]

: "Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words", arXiv, 2023 ( ). [ ]

: "EViT: An Eagle Vision Transformer with Bi-Fovea Self-Attention", arXiv, 2023 ( ). [ ]

: "ViR: Vision Retention Networks", arXiv, 2023 ( ). [ ]

: "Window Attention is Bugged: How not to Interpolate Position Embeddings", arXiv, 2023 ( ). [ ]

: "FMViT: A multiple-frequency mixing Vision Transformer", arXiv, 2023 ( ). [ ][ ]

: "Advancing Vision Transformers with Group-Mix Attention", arXiv, 2023 ( ). [ ][ ]

: "Perceptual Group Tokenizer: Building Perception with Iterative Grouping", arXiv, 2023 ( ). [ ]

: "SCHEME: Scalable Channer Mixer for Vision Transformers", arXiv, 2023 ( ). [ ]

: "Agent Attention: On the Integration of Softmax and Linear Attention", arXiv, 2023 ( ). [ ][ ]

: "ViTamin: Designing Scalable Vision Models in the Vision-Language Era", CVPR, 2024 ( ). [ ][ ]

: "HIRI-ViT: Scaling Vision Transformer with High Resolution Inputs", TPAMI, 2024 ( ). [ ]

: "SPFormer: Enhancing Vision Transformer with Superpixel Representation", arXiv, 2024 ( ). [ ]

: "A Manifold Representation of the Key in Vision Transformers", arXiv, 2024 ( ). [ ]

: "Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers", arXiv, 2024 ( ). [ ]

: "VisionLLaMA: A Unified LLaMA Interface for Vision Tasks", arXiv, 2024 ( ). [ ][ ]

: "xT: Nested Tokenization for Larger Context in Large Images", arXiv, 2024 ( ). [ ]

: "ACC-ViT: Atrous Convolution's Comeback in Vision Transformers", arXiv, 2024 ( ). [ ]

: "ViTAR: Vision Transformer with Any Resolution", arXiv, 2024 ( ). [ ]

: "Adapting LLaMA Decoder to Vision Transformer", arXiv, 2024 ( ). [ ]

: "Training data-efficient image transformers & distillation through attention", ICML, 2021 ( ). [ ][ ]

: "ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases", ICML, 2021 ( ). [ ][ ]

: "Improving the Efficiency of Transformers for Resource-Constrained Devices", DSD, 2021 ( ). [ ]

: "Vision Transformer with Progressive Sampling", ICCV, 2021 ( ). [ ]

: "Scalable Visual Transformers with Hierarchical Pooling", ICCV, 2021 ( ). [ ][ ]

: "CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification", ICCV, 2021 ( ). [ ][ ]

: "Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding", ICCV, 2021 ( ). [ ][ ]

: "Visformer: The Vision-friendly Transformer", ICCV, 2021 ( ). [ ][ ]

: "Multi-Exit Vision Transformer for Dynamic Inference", BMVC, 2021 ( ). [ ][ ]

: "Chasing Sparsity in Vision Transformers: An End-to-End Exploration", NeurIPS, 2021 ( ). [ ][ ]

: "Dynamic Grained Encoder for Vision Transformers", NeurIPS, 2021 ( ). [ ][ ]

: "Glance-and-Gaze Vision Transformer", NeurIPS, 2021 ( ). [ ][ ]

: "DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification", NeurIPS, 2021 ( ). [ ][ ][ ]

: "ResT: An Efficient Transformer for Visual Recognition", NeurIPS, 2021 ( ). [ ][ ]

: "Adder Attention for Vision Transformer", NeurIPS, 2021 ( ). [ ]

: "SOFT: Softmax-free Transformer with Linear Complexity", NeurIPS, 2021 ( ). [ ][ ][ ]

: "IA-RED : Interpretability-Aware Redundancy Reduction for Vision Transformers", NeurIPS, 2021 ( ). [ ][ ]

: "LocalViT: Bringing Locality to Vision Transformers", arXiv, 2021 ( ). [ ][ ]

: "Escaping the Big Data Paradigm with Compact Transformers", arXiv, 2021 ( ). [ ][ ]

: "Vision Transformers with Patch Diversification", arXiv, 2021 ( ). [ ][ ]

: "Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead", arXiv, 2021 ( ). [ ]

: "Multi-Exit Vision Transformer for Dynamic Inference", arXiv, 2021 ( ). [ ]

: "Vision Xformers: Efficient Attention for Image Classification", arXiv, 2021 ( ). [ ]

: "Long-Short Transformer: Efficient Transformers for Language and Vision", NeurIPS, 2021 ( ). [ ][ ]

: "Go Wider Instead of Deeper", arXiv, 2021 ( ). [ ]

: "Armour: Generalizable Compact Self-Attention for Vision Transformers", arXiv, 2021 ( ). [ ]

: "Exploring and Improving Mobile Level Vision Transformers", arXiv, 2021 ( ). [ ]

: "DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers", arXiv, 2021 ( ). [ ][ ]

: "UFO-ViT: High Performance Linear Vision Transformer without Softmax", arXiv, 2021 ( ). [ ]

: "Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer", AAAI, 2022 ( ). [ ][ ]

: "Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped Attention", AAAI, 2022 ( ). [ ][ ]

: "When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism", AAAI, 2022 ( ). [ ][ ]

: "Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations", ICLR, 2022 ( ). [ ][ ]

: "QuadTree Attention for Vision Transformers", ICLR, 2022 ( ). [ ][ ]

: "Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice", ICLR, 2022 ( ). [ ][ ]

: "Learned Queries for Efficient Local Attention", CVPR, 2022 ( ). [ ][ ]

: "Lite Vision Transformer with Enhanced Self-Attention", CVPR, 2022 ( ). [ ][ ]

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: "Bytes Are All You Need: Transformers Operating Directly On File Bytes", arXiv, 2023 ( ). [ ]

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: "ConvFormer: Closing the Gap Between CNN and Vision Transformers", arXiv, 2022 ( ). [ ]

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: "Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality", arXiv, 2022 ( ). [ ][ ]

: "GMML is All you Need", arXiv, 2022 ( ). [ ][ ]

: "Siamese Image Modeling for Self-Supervised Vision Representation Learning", arXiv, 2022 ( ). [ ]

: "SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners", arXiv, 2022 ( ). [ ][ ]

: "Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction", arXiv, 2022 ( ). [ ]

: "Spatial Entropy Regularization for Vision Transformers", arXiv, 2022 ( ). [ ]

: "Extreme Masking for Learning Instance and Distributed Visual Representations", arXiv, 2022 ( ). [ ]

: "Exploring Feature Self-relation for Self-supervised Transformer", arXiv, 2022 ( ). [ ]

: "Position Labels for Self-Supervised Vision Transformer", arXiv, 2022 ( ). [ ]

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: "BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers", arXiv, 2022 ( ). [ ][ ]

: "MILAN: Masked Image Pretraining on Language Assisted Representation", arXiv, 2022 ( ). [ ][ ]

: "Accelerating Vision Transformer Training via a Patch Sampling Schedule", arXiv, 2022 ( ). [ ][ ]

: "Exploring Target Representations for Masked Autoencoders", arXiv, 2022 ( ). [ ]

: "Effective Vision Transformer Training: A Data-Centric Perspective", arXiv, 2022 ( ). [ ]

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: "Location-Aware Self-Supervised Transformers", arXiv, 2022 ( ). [ ]

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: "Stare at What You See: Masked Image Modeling without Reconstruction", CVPR, 2023 ( ). [ ][ ]

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: "Rank-DETR for High Quality Object Detection", NeurIPS, 2023 ( ). [ ][ ]

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: "KS-DETR: Knowledge Sharing in Attention Learning for Detection Transformer", arXiv, 2023 ( ). [ ][ ]

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: "Align-DETR: Improving DETR with Simple IoU-aware BCE loss", arXiv, 2023 ( ). [ ][ ]

: "Box-DETR: Understanding and Boxing Conditional Spatial Queries", arXiv, 2023 ( ). [ ][ ]

: "Enhancing Your Trained DETRs with Box Refinement", arXiv, 2023 ( ). [ ][ ]

: "Revisiting DETR Pre-training for Object Detection", arXiv, 2023 ( ). [ ]

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: "TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers", CVPR, 2022 ( ). [ ][ ]

: "CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection", CVPR, 2022 ( ). [ ]

: "Multimodal Token Fusion for Vision Transformers", CVPR, 2022 ( ). [ ]

: "Embracing Single Stride 3D Object Detector with Sparse Transformer", CVPR, 2022 ( ). [ ][ ]

: "LIFT: Learning 4D LiDAR Image Fusion Transformer for 3D Object Detection", CVPR, 2022 ( ). [ ]

: "BoxeR: Box-Attention for 2D and 3D Transformers", CVPR, 2022 ( ). [ ][ ]

: "Bridged Transformer for Vision and Point Cloud 3D Object Detection", CVPR, 2022 ( ). [ ]

: "VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention", CVPR, 2022 ( ). [ ][ ]

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: "CenterFormer: Center-based Transformer for 3D Object Detection", ECCV, 2022 ( ). [ ][ ]

: "Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Clouds", ECCV, 2022 ( ). [ ][ ][ ]

: "SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention", ECCV, 2022 ( ). [ ][ ]

: "CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection", ECCV, 2022 ( ). [ ]

: "SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds", ECCV, 2022 ( ). [ ]

: "Enhancing Multi-modal Features Using Local Self-Attention for 3D Object Detection", ECCV, 2022 ( ). [ ]

: "Unifying Voxel-based Representation with Transformer for 3D Object Detection", NeurIPS, 2022 ( ). [ ][ ]

: "MsSVT: Mixed-scale Sparse Voxel Transformer for 3D Object Detection on Point Clouds", NeurIPS, 2022 ( ). [ ][ ]

: "DeepInteraction: 3D Object Detection via Modality Interaction", NeurIPS, 2022 ( ). [ ][ ]

: "PETR: Position Embedding Transformation for Multi-View 3D Object Detection", arXiv, 2022 ( ). [ ]

: "Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection", arXiv, 2022 ( ). [ ]

: "PolarFormer: Multi-camera 3D Object Detection with Polar Transformer", arXiv, 2022 ( ). [ ][ ]

: "Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds", arXiv, 2022 ( ). [ ]

: "SEFormer: Structure Embedding Transformer for 3D Object Detection", arXiv, 2022 ( ). [ ]

: "CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer", arXiv, 2022 ( ). [ ]

: "CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection", arXiv, 2022 ( ). [ ][ ]

: "Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection", arXiv, 2022 ( ). [ ]

: "Li3DeTr: A LiDAR based 3D Detection Transformer", WACV, 2023 ( ). [ ]

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: "OcTr: Octree-based Transformer for 3D Object Detection", CVPR, 2023 ( ). [ ]

: "MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer", CVPR, 2023 ( ). [ ]

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: "ConQueR: Query Contrast Voxel-DETR for 3D Object Detection", CVPR, 2023 ( ). [ ][ ][ ]

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: "Pixel-Aligned Recurrent Queries for Multi-View 3D Object Detection", ICCV, 2023 ( ). [ ][ ][ ]

: "Cross Modal Transformer: Towards Fast and Robust 3D Object Detection", ICCV, 2023 ( ). [ ][ ]

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: "Efficient Transformer-based 3D Object Detection with Dynamic Token Halting", ICCV, 2023 ( ). [ ]

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: "Uni3DETR: Unified 3D Detection Transformer", NeurIPS, 2023 ( ). [ ][ ]

: "Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection", NeurIPS, 2023 ( ). [ ][ ]

: "Spatial-Temporal Enhanced Transformer Towards Multi-Frame 3D Object Detection", arXiv, 2023 ( ). [ ][[Code (in construction)(

: "V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection", arXiv, 2023 ( ). [ ][ ]

: "3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features", arXiv, 2023 ( ). [ ][ ][ ]

: "PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection", arXiv, 2023 ( ). [ ][ ]

: "Point-DETR3D: Leveraging Imagery Data with Spatial Point Prior for Weakly Semi-supervised 3D Object Detection", AAAI, 2024 ( ). [ ]

: "MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection", ICLR, 2024 ( ). [ ][ ]

: "Enhancing 3D Object Detection with 2D Detection-Guided Query Anchors", CVPR, 2024 ( ). [ ]

: "ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention", arXiv, 2024 ( ). [ ][ ]

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: "Open-Vocabulary Object Detection Using Captions", CVPR, 2021 ( ). [ ][ ]

: "MDETR - Modulated Detection for End-to-End Multi-Modal Understanding", ICCV, 2021 ( ). [ ][ ][ ]

: "FETNet: Feature Exchange Transformer Network for RGB-D Object Detection", BMVC, 2021 ( ). [ ]

: "Exploiting Scene Depth for Object Detection with Multimodal Transformers", BMVC, 2021 ( ). [ ][ ]

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: "Class-agnostic Object Detection with Multi-modal Transformer", ECCV, 2022 ( ). [ ][ ]

: "Simple Open-Vocabulary Object Detection with Vision Transformers", ECCV, 2022 ( ). [ ][ ][ ]

: "X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks", ECCV, 2022 ( ). [ ]

: "simCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision Transformers", arXiv, 2022 ( ). [ ][ ]

: "DALL-E for Detection: Language-driven Context Image Synthesis for Object Detection", arXiv, 2022 ( ). [ ]

: "You Only Need One Detector: Unified Object Detector for Different Modalities based on Vision Transformers", arXiv, 2022 ( ). [ ][ ]

: "OmDet: Language-Aware Object Detection with Large-scale Vision-Language Multi-dataset Pre-training", arXiv, 2022 ( ). [ ]

: "Video Referring Expression Comprehension via Transformer with Content-aware Query", arXiv, 2022 ( ). [ ]

: "DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding", AAAI, 2023 ( ). [ ][ ]

: "F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models", ICLR, 2023 ( ). [ ][ ]

: "Open-Vocabulary Point-Cloud Object Detection without 3D Annotation", CVPR, 2023 ( ). [ ][ ]

: "Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embedding", CVPR, 2023 ( ). [ ]

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: "Multi-Modal Classifiers for Open-Vocabulary Object Detection", ICML, 2023 ( ). [ ][ ][ ]

: "CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection", NeurIPS, 2023 ( ). [ ][ ][ ]

: "Contextual Object Detection with Multimodal Large Language Models", arXiv, 2023 ( ). [ ][ ][ ]

: "Object2Scene: Putting Objects in Context for Open-Vocabulary 3D Detection", arXiv, 2023 ( ). [ ]

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: "MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection", CVPR, 2022 ( ). [ ]

: "What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions", CVPR, 2022 ( ). [ ]

: "Consistency Learning via Decoding Path Augmentation for Transformers in Human Object Interaction Detection", CVPR, 2022 ( ). [ ][ ]

: "Human-Object Interaction Detection via Disentangled Transformer", CVPR, 2022 ( ). [ ]

: "Exploring Structure-Aware Transformer Over Interaction Proposals for Human-Object Interaction Detection", CVPR, 2022 ( ). [ ][ ]

: "Distillation Using Oracle Queries for Transformer-Based Human-Object Interaction Detection", CVPR, 2022 ( ). [ ]

: "Efficient Two-Stage Detection of Human-Object Interactions with a Novel Unary-Pairwise Transformer", CVPR, 2022 ( ). [ ][ ][ ]

: "Category-Aware Transformer Network for Better Human-Object Interaction Detection", CVPR, 2022 ( ). [ ]

: "GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection", CVPR, 2022 ( ). [ ][ ]

: "Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection", ECCV, 2022 ( ). [ ][ ]

: "Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows", ECCV, 2022 ( ). [ ]

: "RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection", NeurIPS, 2022 ( ). [ ][ ]

: "Video-based Human-Object Interaction Detection from Tubelet Tokens", NeurIPS, 2022 ( ). [ ]

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: "Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning", ICLR, 2023 ( ). [ ]

: "HOICLIP: Efficient Knowledge Transfer for HOI Detection with Vision-Language Models", CVPR, 2023 ( ). [ ][ ]

: "ViPLO: Vision Transformer based Pose-Conditioned Self-Loop Graph for Human-Object Interaction Detection", CVPR, 2023 ( ). [ ][ ]

: "Open-Category Human-Object Interaction Pre-Training via Language Modeling Framework", CVPR, 2023 ( ). [ ]

: "Category Query Learning for Human-Object Interaction Classification", CVPR, 2023 ( ). [ ][ ]

: "Re-mine, Learn and Reason: Exploring the Cross-modal Semantic Correlations for Language-guided HOI detection", ICCV, 2023 ( ). [ ]

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: "Agglomerative Transformer for Human-Object Interaction Detection", ICCV, 2023 ( ). [ ][ ]

: "RLIPv2: Fast Scaling of Relational Language-Image Pre-training", ICCV, 2023 ( ). [ ][ ]

: "EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding", ICCV, 2023 ( ). [ ][ ]

: "Detecting Any Human-Object Interaction Relationship: Universal HOI Detector with Spatial Prompt Learning on Foundation Models", NeurIPS, 2023 ( ). [ ][ ]

: "Neural-Logic Human-Object Interaction Detection", NeurIPS, 2023 ( ). [ ][ ]

: "Exploiting CLIP for Zero-shot HOI Detection Requires Knowledge Distillation at Multiple Levels", arXiv, 2023 ( ). [ ]

: "Disentangled Pre-training for Human-Object Interaction Detection", CVPR, 2024 ( ). [ ][ ]

: "HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision", arXiv, 2024 ( ). [ ][ ][ ]

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: "Transformer Transforms Salient Object Detection and Camouflaged Object Detection", arXiv, 2021 ( ). [ ]

: "Unifying Global-Local Representations in Salient Object Detection with Transformer", arXiv, 2021 ( ). [ ]

: "TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Network", arXiv, 2021 ( ). [ ]

: "Boosting Salient Object Detection with Transformer-based Asymmetric Bilateral U-Net", arXiv, 2021 ( ). [ ]

: "TranSalNet: Visual saliency prediction using transformers", arXiv, 2021 ( ). [ ]

: "DFTR: Depth-supervised Hierarchical Feature Fusion Transformer for Salient Object Detection", arXiv, 2022 ( ). [ ]

: "GroupTransNet: Group Transformer Network for RGB-D Salient Object Detection", arXiv, 2022 ( ). [ ]

: "SelfReformer: Self-Refined Network with Transformer for Salient Object Detection", arXiv, 2022 ( ). [ ]

: "Dual Swin-Transformer based Mutual Interactive Network for RGB-D Salient Object Detection", arXiv, 2022 ( ). [ ]

: "Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection", arXiv, 2022 ( ). [ ][ ]

: "SiaTrans: Siamese Transformer Network for RGB-D Salient Object Detection with Depth Image Classification", arXiv, 2022 ( ). [ ]

: "PSFormer: Point Transformer for 3D Salient Object Detection", arXiv, 2022 ( ). [ ]

: "Recurrent Multi-scale Transformer for High-Resolution Salient Object Detection", ACMMM, 2023 ( ). [ ]

: "Localizing Objects with Self-Supervised Transformers and no Labels", BMVC, 2021 ( ). [ ][ ]

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: "Scaling Novel Object Detection with Weakly Supervised Detection Transformers", CVPRW, 2022 ( ). [ ]

: "Re-Attention Transformer for Weakly Supervised Object Localization", arXiv, 2022 ( ). [ ][ ]

: "TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut", arXiv, 2022 ( ). [ ][ ][ ]

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Paper

: "HASSOD: Hierarchical Adaptive Self-Supervised Object Detection", NeurIPS, 2023 ( ). [ ][ ][ ]

: "SeqCo-DETR: Sequence Consistency Training for Self-Supervised Object Detection with Transformers", arXiv, 2023 ( ). [ ]

: "R-MAE: Regions Meet Masked Autoencoders", arXiv, 2023 ( ). [ ]

: "SimDETR: Simplifying self-supervised pretraining for DETR", arXiv, 2023 ( ). [ ]

: "Unsupervised Universal Image Segmentation", arXiv, 2023 ( ). [ ][ ]

: "CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers", CVPR, 2024 ( ). [ ][ ]

: "Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection", CVPR, 2024 ( ). [ ]

: "Adaptive Image Transformer for One-Shot Object Detection", CVPR, 2021 ( ). [ ]

: "Meta-DETR: Few-Shot Object Detection via Unified Image-Level Meta-Learning", arXiv, 2021 ( ). [ ][ ]

: "CAT: Cross-Attention Transformer for One-Shot Object Detection", arXiv, 2021 ( ). [ ]

: "Few-Shot Object Detection with Fully Cross-Transformer", CVPR, 2022 ( ). [ ]

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