vstar
Visual search framework
PyTorch implementation of guided visual search mechanism for multimodal LLMs
PyTorch Implementation of "V* : Guided Visual Search as a Core Mechanism in Multimodal LLMs"
541 stars
11 watching
37 forks
Language: Python
last commit: about 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
| An open-source PyTorch implementation of a visual semantic reasoning model for image-text matching | 294 |
| A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,236 |
| A PyTorch implementation of visual-semantic embedding methods for image-caption retrieval | 492 |
| An implementation of an imperative learning to search framework in PyTorch for deep learning-based structured prediction and reinforcement learning. | 111 |
| Transfers visual prompt generators across large language models to reduce training costs and enable customization of multimodal LLMs | 270 |
| A PyTorch implementation of visual question answering with multimodal representation learning | 718 |
| A PyTorch-based framework for training large language models in parallel on multiple devices | 679 |
| A PyTorch implementation of an improved question answering architecture with dynamic memory networks and attention mechanisms | 64 |
| An implementation of MobileNetV3 using PyTorch with search space optimization | 292 |
| An implementation of reinforcement learning for visual relationship and attribute detection using PyTorch. | 63 |
| An efficient framework for end-to-end learning on image-text and video-text tasks | 709 |
| Provides a PyTorch implementation of several computer vision tasks including object detection, segmentation and parsing. | 1,191 |
| A PyTorch project for comparing image classification models and facilitating quick experiment setup | 366 |
| Pytorch implementation of unsupervised depth and ego-motion learning from video sequences | 1,022 |
| A collection of tutorials and lessons on building deep learning models using the PyTorch library. | 326 |