Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
-
Updated
Mar 17, 2023 - Python
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
[IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
Lightweight Python library for adding real-time multi-object tracking to any detector.
Paper list and source code for multi-object-tracking
(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"
High-performance multiple object tracking based on YOLO, Deep SORT, and KLT
Multi-object trackers in Python
Official Implementation of How To Train Your Deep Multi-Object Tracker (CVPR2020)
SiamMOT: Siamese Multi-Object Tracking
BoT-SORT: Robust Associations Multi-Pedestrian Tracking
Library for tracking-by-detection multi object tracking implemented in python
[ECCV2022] MOTR: End-to-End Multiple-Object Tracking with TRansformer
Multiple object tracking (MOT) algorithm implemented in C++
Official PyTorch implementation of "Learning a Neural Solver for Multiple Object Tracking" (CVPR 2020 Oral).
[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).
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.
Real-time multi-camera multi-object tracker using YOLOv7 and StrongSORT with OSNet
Add a description, image, and links to the multi-object-tracking topic page so that developers can more easily learn about it.
To associate your repository with the multi-object-tracking topic, visit your repo's landing page and select "manage topics."