YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Ultralytics YOLO 🚀

LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.

We write your reusable computer vision tools. 💜

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

OpenMMLab Detection Toolbox and Benchmark

NVR with realtime local object detection for IP cameras

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

deep learning for image processing including classification and object-detection etc.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

CVPR 2026 论文和开源项目合集

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

End-to-End Object Detection with Transformers

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

A paper list of object detection using deep learning.

YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

Refine high-quality datasets and visual AI models

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Fast and Accurate ML in 3 Lines of Code

Techniques for deep learning with satellite & aerial imagery

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Best Practices, code samples, and documentation for Computer Vision.

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.