Mmtrack

Improvements

- Fixed typos ([104](https://github.com/open-mmlab/mmtracking/commit/3ccc9b79ce6e14e013268d0dbb53462c0432f357), [#121](https://github.com/open-mmlab/mmtracking/commit/fadcd811df095781fbbdc7c47f8dac1305555461), [#145](https://github.com/open-mmlab/mmtracking/commit/48a47868abd9a0d96c010fc3f85cba1bd2854a9b))
- Added conference reference ([111](https://github.com/open-mmlab/mmtracking/commit/9a3c463b087cdee201a9345f270f6c01e116cf2c))
- Updated the link of CONTRIBUTING to mmcv ([112](https://github.com/open-mmlab/mmtracking/commit/b725e63463b1bd795fd3c3000b30ef37832a844d))
- Adapt updates in mmcv (FP16Hook) ([114](https://github.com/open-mmlab/mmtracking/commit/49f910878345250d22fd5da1104f1fb227244939), [#119](https://github.com/open-mmlab/mmtracking/commit/f1df53dd8e571f4674867919d1886b9fb2024bf9))
- Added bibtex and links to other codebases ([122](https://github.com/open-mmlab/mmtracking/commit/1b456423e0aeddb52e7c29e5b0ec3d48e058c615))
- Added docker files ([124](https://github.com/open-mmlab/mmtracking/commit/a01c3e8fff97a2b8eebc8d28e3e9d9a360ffbc3c))
- Used `collect_env` in mmcv ([129](https://github.com/open-mmlab/mmtracking/commit/0055947c4d19c8921c32ce128ae0314d61e593d2))
- Added and updated Chinese README ([135](https://github.com/open-mmlab/mmtracking/commit/ecc83b5e6523582b92196095eb21d72d654322f2), [#147](https://github.com/open-mmlab/mmtracking/commit/19004b6eeca594a2179d8b3a3622764e1753aa4d), [#148](https://github.com/open-mmlab/mmtracking/commit/dc367868453fdcb528041176a59ede368f0e2053))

Bug Fixes

- Fixed ReID checkpoint loading ([80](https://github.com/open-mmlab/mmtracking/pull/80))
- Fixed empty tensor in `track_result` ([86](https://github.com/open-mmlab/mmtracking/pull/86))
- Fixed `wait_time` in MOT demo script ([92](https://github.com/open-mmlab/mmtracking/pull/92))

Improvements

- Support single-stage detector for DeepSORT ([100](https://github.com/open-mmlab/mmtracking/pull/100))

Highlights

- MMTracking is released! It is the first open source toolbox that unifies versatile video perception tasks include single object tracking, multiple object tracking, and video object detection.

New Features

- Support video object detection methods: [DFF](https://arxiv.org/abs/1611.07715), [FGFA](https://arxiv.org/abs/1703.10025), [SELSA](https://arxiv.org/abs/1907.06390)
- Support multi object tracking methods: [SORT](https://arxiv.org/abs/1602.00763)/[DeepSORT](https://arxiv.org/abs/1703.07402), [Tracktor](https://arxiv.org/abs/1903.05625)
- Support single object tracking methods: [SiameseRPN++](https://arxiv.org/abs/1812.11703)