BoxMOT: Pluggable python and c++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes

Joint Detection and Embedding for fast multi-object tracking

Python implementation of the IOU Tracker

Library for tracking-by-detection multi object tracking implemented in python

Object detection and tracking algorithm implemented for Real-Time video streams and static images.

Finger Detection and Tracking using OpenCV and Python

[NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).

Video and Image Analytics for Multiple Environments

Joint detection and tracking model named DEFT, or ``Detection Embeddings for Tracking." Our approach relies on an appearance-based object matching network jointly-learned with an underlying object detection network. An LSTM is also added to capture motion constraints.

[IROS2025]This is the offical implementation of the paper "MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving"

🔥 CVPR 2025 (Nashville TN) - The 4th Anti-UAV Workshop & Challenge 🥉

Cascade-RCNN+DeepSort MOTDT Trackor++

Official implementation of 🐫 CAMELTrack: Context-Aware Multi-cue ExpLoitation for Online Multi-Object Tracking 🐫

Optical Flow Dataset and Benchmark for Visual Crowd Analysis

Official PyTorch implementation of "Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking" (CVPR 2021).

AutoTrackAnything is a universal, flexible and interactive tool for insane automatic object tracking over thousands of frames. It is developed upon XMem, Yolov8 and MobileSAM (Segment Anything), can track anything which detect Yolov8.

Tracking-by-Detection形式のMOT(Multi Object Tracking)について、 DetectionとTrackingの処理を分離して寄せ集めたフレームワーク(Tracking-by-Detection method MOT(Multi Object Tracking) is a framework that separates the processing of Detection and Tracking.)

Particle tracking by solving linear assignment problem.

Multi-Object Tracking with Uncertain Detections [ECCV 2024 UnCV]

Object tracking with OpenCV in open field behavioral test (overhead view maze)