There are 10 repositories under visual-tracking topic.
CVPR 2022 论文和开源项目合集
Visual Tracking Paper List
Visual tracking library based on PyTorch.
(2020-2022)The PyTorch version of SiamFC,SiamRPN,DaSiamRPN, UpdateNet , SiamDW, SiamRPN++, SiamMask, SiamFC++, SiamCAR, SiamBAN, Ocean, LightTrack , TrTr, NanoTrack; Visual object tracking based on deep learning
Matlab implementation of the ECO tracker.
Python re-implementation of some correlation filter based tracker
Visual Object Tracking (VOT) challenge evaluation toolkit
PyTorch implementation of GOTURN object tracker: Learning to Track at 100 FPS with Deep Regression Networks (ECCV 2016)
2019-2020年目标跟踪资源全汇总(论文、模型代码、优秀实验室)极市团队整理
The official VOT Challenge evaluation and analysis toolkit
C++ Implementation of SiamMask
Open source visual object tracking library in python
Official implementation of "Energy-Based Models for Deep Probabilistic Regression" (ECCV 2020) and "How to Train Your Energy-Based Model for Regression" (BMVC 2020).
Reference implementation of the Visual Tracking eXchange protocol.
Implementation of MOSSE tracker in MATLAB: Visual Object Tracking using Adaptive Correlation Filters (CVPR 2010)
Synthetic data generation for end-to-end TIR tracking (TIP2018)
Visual Object Tracking algorithms. Hold on! There is a lot to come
Visual Tracking by TridenAlign and Context Embedding
Real-time visual object tracking using correlations filters and deep learning
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark (CVPR 2021)
Matlab code for several visual tracking algorithms
This Repo include some paperlist and code with visual tracking based on deep reinforcement。
Official code implementation of the papers "Tracking-by-Trackers with a Distilled and Reinforced Model" (ACCV 2020) and "Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator" (ICCVW 2019).
Personal website for Abdallah Dib.
Webots visual tracking example with OpenCV
Official implementation of deep-multi-trajectory-based single object tracking (IEEE T-CSVT 2021).
Multi Agent Visual Tracking Project is based on the CamShift Algorithm on the Platform of MultiAgent Control
This work proposes a feature refined end-to-end tracking framework with a balanced performance using a high-level feature refine tracking framework. The feature refine module enhances the target feature representation power that allows the network to capture salient information to locate the target. The attention module is employed inside the feature refine mechanism to improve network discrimination power that augments the network ability to track the target in challenging scenarios.
Official code repository to download the TREK-150 benchmark dataset and run experiments on it.