Starred repositories
Official repository for the paper "SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentation."
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Updated May 29, 2025
This is the official code (based on Pytorch framework) for the paper "Open-Det: An Efficient Learning Framework for Open-Ended Detection".
1
Updated May 29, 2025
Model Context Protocol Servers
Code for "LiftFeat: 3D Geometry-Aware Local Feature Matching", ICRA2025
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025
mcp-use is the easiest way to interact with mcp servers with custom agents
LangGraph-powered ReAct agent with Model Context Protocol (MCP) integration. A Streamlit web interface for dynamically configuring, deploying, and interacting with AI agents capable of accessing va…
MambaGlue: Fast and Robust Local Feature Matching With Mamba @ ICRA'25
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"
Edge Weight Prediction For Category-Agnostic Pose Estimation
DINO-X: The World's Top-Performing Vision Model for Open-World Object Detection and Understanding
Master programming by recreating your favorite technologies from scratch.
Hiera: A fast, powerful, and simple hierarchical vision transformer.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
[ECCV 2024] The official code of paper "Open-Vocabulary SAM".
Official implementation of OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
[NeurIPS 2024] Code release for "Segment Anything without Supervision"
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series