Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Detection, segmentation, tracking, OCR models, 3D reconstruction and classical vision.
Signals: computer-vision, object-detection, image-segmentation, yolo, opencv, image-classification, pose-estimation, object-tracking
1,474 results
MonSter++: A Unified Geometric Foundation Model for Stereo and Multi-View Depth Estimation via the Unleashing of Monodepth Priors
Official repository for Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation. (DINOv3)
[CVPR 2023] Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners
Official implementation of "Depth Any Panoramas: A Foundation Model for Panoramic Depth Estimation".
[CVPR 2024] Probing the 3D Awareness of Visual Foundation Models
[CVPR 2025] DEFOM-Stereo: Depth foundation model based stereo matching
[ECCV 2024] Official repository of Agent Attention
VIGA: Vision-as-Inverse-Graphics Agent
Our method reconstructs 3D worlds from video diffusion models using non-rigid alignment to resolve inherent 3D inconsistencies in the generated sequences.
[CVPR'25 Oral] Official implementation for "DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models"
Official pytorch implementation for "LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Models"
This is the official Pytorch implementation of the paper "Diffusion Models for Implicit Image Segmentation Ensembles".
[CVPR'24] Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
[CVPR 2023] DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models
Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]
[SIGGRAPH Asia 2026] AnyRecon: Arbitrary-View 3D Reconstruction with Video Diffusion Model
[AAAI 2025] MV-VTON: Multi-View Virtual Try-On with Diffusion Models
AI-Video-Cropper is a Python-based tool that leverages the power of GPT-4 (OpenAI's language model) to automatically analyze videos, extract the most interesting sections, and crop them for improved viewing experience. This project combines the capabilities of GPT-4, FFmpeg, and OpenCV to automate the process of identifying highlights in videos
(CVPR 2025 highlight✨) Official repository of paper "LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models"
This is the pytorch implement of our paper "RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model"
🌟A curated list of DUSt3R-related papers and resources, tracking recent advancements using this geometric foundation model.
[NeurIPS'23 Spotlight] Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
The repo for "Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image" and "Metric3Dv2: A Versatile Monocular Geometric Foundation Model..."
Official implementation of "Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction"
24,544 repositories in the index in total.
