object-detection

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

We write your reusable computer vision tools. 💜

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

NVR with realtime local object detection for IP cameras

OpenMMLab Detection Toolbox and Benchmark

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

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.

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

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

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.

Refine high-quality datasets and visual AI models

Fast and Accurate ML in 3 Lines of Code

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