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multi-object-tracking

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DLRook1e
DLRook1e commented Apr 26, 2022

Environment:
{'sys.platform': 'win32', 'Python': '3.9.12 (main, Apr 4 2022, 05:22:27) [MSC v.1916 64 bit (AMD64)]', 'CUDA available': True, 'GPU 0': 'NVIDIA GeForce RTX 3060 Ti', 'CUDA_HOME': 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3', 'NVCC': 'Cuda compilation tools, release 11.3, V11.3.58', 'MSVC': '用于 x64 的 Microsoft (R) C/C++ 优化编译器 19.29.30141 版', 'GCC': 'n/a', 'PyTorch':

good first issue

[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).

  • Updated Apr 26, 2022
  • Python

A multi-object tracking component. Works in the conditions where identification and classical object trackers don't (e.g. shaky/unstable camera footage, occlusions, motion blur, covered faces, etc.). Works on any object despite their nature.

  • Updated Apr 19, 2021
  • Python

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