awesome-video-text-retrieval

by danieljf24

awesome listpushed almost 3 years ago

A curated list of deep learning resources for video-text retrieval.

AI summary

Video-text retrieval techniques

A curated list of resources and papers on deep learning techniques for text-video retrieval tasks

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What's in the list

131 links in 11 sections, with live GitHub stats.activeno commit in 2y

Implementations

hybrid_space
87over 3 years
dual_encoding
154over 3 years
w2vvpp
282 years
Mixture-of-Embedding-Experts
1186 years
howto100m
254over 6 years
collaborative
337over 3 years
hgr
210over 6 years
coot
2884 years
mmt
259almost 2 years
ClipBERT
7093 years
jsfusion
31almost 8 years
w2vv
(Keras)
69over 6 years
Extracting CNN features from video frames by MXNet
31over 4 years

Papers / 2023

[paper]
CLIPPING: Distilling CLIP-Based Models with a Student Base for Video-Language Retrieval. CVPR, 2023
[paper]
SViTT: Temporal Learning of Sparse Video-Text Transformers. CVPR, 2023
[paper]
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval. CVPR, 2023
[paper]
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models. CVPR, 2023
[paper]
All in One: Exploring Unified Video-Language Pre-Training. CVPR, 2023
[paper]
IMAGEBIND: One Embedding Space To Bind Them All. CVPR, 2023
[paper]
VoP: Text-Video Co-Operative Prompt Tuning for Cross-Modal Retrieval. CVPR, 2023
[paper]
LAVENDER: Unifying Video-Language Understanding As Masked Language Modeling. CVPR, 2023
[paper]
Clover: Towards a Unified Video-Language Alignment and Fusion Model. CVPR, 2023
[paper]
Seeing What You Miss: Vision-Language Pre-Training With Semantic Completion Learning. CVPR, 2023
[paper]
CNVid-3.5M: Build, Filter, and Pre-train the Large-scale Public Chinese Video-text Dataset. CVPR, 2023
[paper]
Cali-NCE: Boosting Cross-Modal Video Representation Learning With Calibrated Alignment. CVPRWorkshop, 2023
[paper]
Using Multimodal Contrastive Knowledge Distillation for Video-Text Retrieval. TCSVT, 2023

Papers / 2022

[homepage]
Partially Relevant Video Retrieval. ACM Multimedia, 2022
[paper]
Cross-Lingual Cross-Modal Retrieval with Noise-Robust Learning. ACM Multimedia, 2022
[paper]
Learn to Understand Negation in Video Retrieval. ACM Multimedia, 2022
[paper]
A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval. ACM Multimedia, 2022
[paper]
X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval. ACM Multimedia, 2022
[paper]
Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval. ECCV, 2022
[paper]
TS2-Net: Token Shift and Selection Transformer for Text-Video Retrieval. ECCV, 2022
[paper]
Reading-strategy Inspired Visual Representation Learning for Text-to-Video Retrieval. TCSVT, 2022
[paper]
Align and Prompt: Video-and-Language Pre-training with Entity Prompts, CVPR, 2022
[paper]
Everything at Once -- Multi-modal Fusion Transformer for Video Retrieval. CVPR, 2022
[paper]
Bridging Video-text Retrieval with Multiple Choice Questions. CVPR, 2022
[paper]
Temporal Alignment Networks for Long-term Video. CVPR.2022
[paper]
X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. CVPR, 2022
[paper]
LGDN: Language-Guided Denoising Network for Video-Language Modeling. NIPS, 2022
[paper]
Animating Images to Transfer CLIP for Video-Text Retrieval. SIGIR, 2022
[paper]
CenterCLIP: Token Clustering for Efficient Text-Video Retrieval. SIGIR, 2022
[paper]
Cross-Modal Discrete Representation Learning. ACL, 2022
[paper]
Masking Modalities for Cross-modal Video Retrieval. WACV, 2022
[paper]
Visual Consensus Modeling for Video-Text Retrieval. AAAI, 2022
[paper]
Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss. AAAI, 2022
[paper]
Many Hands Make Light Work: Transferring Knowledge from Auxiliary Tasks for Video-Text Retrieval. IEEE Transactions on Multimedia, 2022
[paper]
Exposing the Limits of Video-Text Models through Contrast Sets. NAACL, 2022
[paper]
Adversarial Multi-Grained Embedding Network for Cross-Modal Text-Video Retrieval. TOMM, 2022
[paper]
LaT: Latent Translation with Cycle-Consistency for Video-Text Retrieval. arXiv:2207.04858, 2022
[paper]
A CLIP-Hitchhiker's Guide to Long Video Retrieval. arXiv:2205.08508, 2022
[paper]
CLIP2TV: Align, Match and Distill for Video-Text Retrieval. arXiv:2111.05610, 2022
[paper]
Tencent Text-Video Retrieval: Hierarchical Cross-Modal Interactions with Multi-Level Representations. arXiv:2204.03382, 2022

Papers / 2021

[paper]
Dual Encoding for Video Retrieval by Text. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
[paper]
Universal Weighting Metric Learning for Cross-Modal Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
[paper]
Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling. CVPR, 2021
[paper]
On Semantic Similarity in Video Retrieval. CVPR, 2021
[paper]
Learning the Best Pooling Strategy for Visual Semantic Embedding. CVPR, 2021
[paper]
T2VLAD: Global-Local Sequence Alignment for Text-Video Retrieval. CVPR, 2021
[paper]
Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers. CVPR, 2021
[paper]
Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval. CVPR, 2021
[paper]
Multimodal Clustering Networks for Self-Supervised Learning from Unlabeled Videos. ICCV, 2021
[paper]
TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval. ICCV, 2021
[paper]
TACo: Token-aware Cascade Contrastive Learning for Video-Text Alignment. ICCV, 2021
[paper]
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval. ICCV, 2021
[paper]
COOKIE: Contrastive Cross-Modal Knowledge Sharing Pre-Training for Vision-Language Representation. ICCV, 2021
[paper]
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising. ACM Multimedia, 2021
[paper]
HANet: Hierarchical Alignment Networks for Video-Text Retrieval. ACM Multimedia, 2021
[paper]
Progressive Semantic Matching for Video-Text Retrieval. ACM Multimedia, 2021
[paper]
Fine-grained Cross-modal Alignment Network for Text-Video Retrieval. ACM Multimedia, 2021
[paper]
Meta Self-Paced Learning for Cross-Modal Matching. ACM Multimedia, 2021
[paper]
Support-set Bottlenecks for Video-text Representation Learning. ICLR, 2021
[paper]
Semantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval. IEEE Transactions on Image Processing, 2021
[paper]
Spatial-temporal Graphs for Cross-modal Text2Video Retrieval. IEEE Transactions on Multimedia, 2021
[paper]
Multi-level Alignment Network for Domain Adaptive Cross-modal Retrieval. Neurocomputing, 2021
[paper]
Hierarchical Cross-Modal Graph Consistency Learning for Video-Text Retrieval. SIGIR, 2020
[paper]
Improving Video Retrieval by Adaptive Margin. SIGIR, 2021
[paper]
Dig into Multi-modal Cues for Video Retrieval with Hierarchical Alignment. IJCAI, 2021
[paper]
Mind-the-Gap! Unsupervised Domain Adaptation for Text-Video Retrieval. AAAI, 2021
[paper]
What Matters: Attentive and Relational Feature Aggregation Network for Video-Text Retrieval. ICME, 2021
[paper]
Multi-Dimensional Attentive Hierarchical Graph Pooling Network for Video-Text Retrieval. ICME, 2021
[paper]
Semantic-Preserving Metric Learning for Video-Text Retrieval. IEEE International Conference on Image Processing, 2021
[paper]
Multi-Feature Graph Attention Network for Cross-Modal Video-Text Retrieval. ICMR, 2021
[paper]
HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval. arXiv:2103.15049, 2021
[paper]
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text. arXiv:2104.11178 , 2021
[paper]
CLIP2Video: Mastering Video-Text Retrieval via Image CLIP. arXiv:2106.11097, 2021
[paper]
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval. arXiv:2104.08860, 2021
[paper]
Align and Prompt: Video-and-Language Pre-training with Entity Prompts. arXiv:2112.09583, 2021

Papers / 2020

[paper]
Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval. SIGIR, 2020
[paper]
COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning. NeurIPS, 2020
[paper]
Multi-modal Transformer for Video Retrieval. ECCV, 2020
[paper]
SEA: Sentence Encoder Assembly for Video Retrieval by Textual Queries. IEEE Transactions on Multimedia, 2020
[paper]
Learning Coarse-to-Fine Graph Neural Networks for Video-Text Retrieval. IEEE Transactions on Multimedia, 2020
[paper]
Interclass-Relativity-Adaptive Metric Learning for Cross-Modal Matching and Beyond. IEEE Transactions on Multimedia, 2020
[paper]
Interpretable Embedding for Ad-Hoc Video Search. ACM Multimedia, 2020
[paper]
Exploiting Visual Semantic Reasoning for Video-Text Retrieval. IJCAI, 2020
[paper]
Universal Weighting Metric Learning for Cross-Modal Retrieval. CVPR, 2020
[paper]
Action Modifiers: Learning from Adverbs in Instructional Videos. CVPR, 2020
[paper]
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning. CVPR, 2020
[paper]
ActBERT: Learning Global-Local Video-Text Representations. CVPR, 2020
[paper]
End-to-End Learning of Visual Representations From Uncurated Instructional Videos. CVPR, 2020
[paper]
Stacked Convolutional Deep Encoding Network For Video-Text Retrieval. ICME, 2020
[paper]
UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation. arXiv:2002.06353, 2020

Papers / 2019

[paper]
Dual Encoding for Zero-Example Video Retrieval. CVPR, 2019
[paper]
Polysemous visual-semantic embedding for cross-modal retrieval. CVPR, 2019
[paper]
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings. ICCV, 2019
[paper]
A Graph-Based Framework to Bridge Movies and Synopses. ICCV, 2019
[paper]
W2VV++ Fully Deep Learning for Ad-hoc Video Search. ACM Multimedia, 2019
[paper]
Use What You Have: Video Retrieval Using Representations From Collaborative Experts. MBVC, 2019
[paper]
From Intra-Modal to Inter-Modal Space: Multi-Task Learning of Shared Representations for Cross-Modal Retrieval. International Conference on Multimedia Big Data, 2019

Papers / 2018

[paper]
Predicting visual features from text for image and video caption retrieval. IEEE Transactions on Multimedia, 2018
[paper]
Cross-Modal and Hierarchical Modeling of Video and Text. ECCV, 2018
[paper]
A Joint Sequence Fusion Model for Video Question Answering and Retrieval. ECCV, 2018
[paper]
Find and focus: Retrieve and localize video events with natural language queries. ECCV, 2018
[paper]
Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval. ICMR, 2018
[paper]
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data. arXiv preprint arXiv:1804.02516, 2018

Papers / Before

[paper]
End-to-end concept word detection for video captioning, retrieval, and question answering. CVPR, 2017
[paper]
Learning joint representations of videos and sentences with web image search. ECCV Workshop, 2016
[paper]
Jointly modeling deep video and compositional text to bridge vision and language in a unified framework. AAAI, 2015

Papers / Ad-hoc Video Search

TRECVID
For the papers targeting at ad-hoc video search in the context of , please refer to

[paper]
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos. Interspeech, 2021
[paper]
Learning Spatiotemporal Features via Video and Text Pair Discrimination. arXiv preprint arXiv:2001.05691, 2020

Datasets

[paper]
David et al. Collecting Highly Parallel Data for Paraphrase Evaluation. ACL, 2011
[paper]
Xu et al. MSR-VTT: A Large Video Description Dataset for Bridging Video and Language. CVPR, 2016
[paper]
Li et al. TGIF: A new dataset and benchmark on animated GIF description. CVPR, 2016
[paper]
Awad et al. Trecvid 2016: Evaluating video search, video event detection, localization, and hyperlinking. TRECVID Workshop, 2016
[paper]
Rohrbach et al. Movie description. IJCV, 2017
[paper]
Krishna et al. Dense-captioning events in videos. ICCV, 2017
[paper]
Hendricks et al. Localizing Moments in Video with Natural Language. ICCV, 2017
[paper]
Miech et al. HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips. ICCV, 2019
[paper]
Wang et al. VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research. ICCV, 2019

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