#Vision-and-language
Showing 36 of 36 repositories tagged #vision-and-language, ranked by stars
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
LAVIS - A One-stop Library for Language-Vision Intelligence
[EMNLP-2024] Build multimodal language agents for fast prototype and production
日本語LLMまとめ - Overview of Japanese LLMs
Real-time and accurate open-vocabulary end-to-end object detection
[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
X-modaler is a versatile and high-performance codebase for cross-modal analytics(e.g., image captioning, video captioning, vision-language pre-training, visual question answering, visual commonsense reasoning, and cross-modal retrieval).
[CVPR 2024 🔥] Grounding Large Multimodal Model (GLaMM), the first-of-its-kind model capable of generating natural language responses that are seamlessly integrated with object segmentation masks.
CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
About This repository is a curated collection of the most exciting and influential CVPR 2025 papers. 🔥 [Paper + Code + Demo]
[CVPR 2024] Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
My Reading Lists of Deep Learning and Natural Language Processing
This repository is a curated collection of the most exciting and influential CVPR 2024 papers. 🔥 [Paper + Code + Demo]
This repository is a curated collection of the most exciting and influential CVPR 2023 papers. 🔥 [Paper + Code]
Creating a software for automatic monitoring in online proctoring
This repo lists relevant papers summarized in our survey paper: A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models.
The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
This AI Smart Speaker uses speech recognition, TTS (text-to-speech), and STT (speech-to-text) to enable voice and vision-driven conversations, with additional web search capabilities via OpenAI and Langchain agents.
HPT - Open Multimodal LLMs from HyperGAI
[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Code/Data for the paper: "LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding"
Awesome Resources for Advanced Computer Vision Topics
A curated list of research papers in Vision-Language Navigation (VLN)
This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).
Official implementation of X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models
VLM driven tool that processes surveillance videos, extracts frames, and generates insightful annotations using a fine-tuned Florence-2 Vision-Language Model. Includes a Gradio-based interface for querying and analyzing video footage.
[CVPR 2024] Physical Property Understanding from Language-Embedded Feature Fields
[NeurIPS 2023] A faithful benchmark for vision-language compositionality
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
A collection of multimodal datasets, and visual features for VQA and captionning in pytorch. Just run "pip install multimodal"
Hierarchical Universal Language Conditioned Policies
[ICCV 2021] Official implementation of the paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering"
[CVPR 2023 & IJCV 2025] Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation
Awesome Large Vision-Language Model: A Curated List of Large Vision-Language Model
visual question answering prompting recipes for large vision-language models