• Planar Object Tracking via Weighted Optical Flow [[https://cmp.felk.cvut.cz/~serycjon/WOFT/][Project Page]]

Official implementation of the WOFT tracker from the paper

[[https://cmp.felk.cvut.cz/~serycjon/][Jonáš Šerých]], [[https://cmp.felk.cvut.cz/~matas/][Jiří Matas]]: "Planar Object Tracking via Weighted Optical Flow", WACV 2023

Please cite our paper, if you use any of this. #+begin_example @inproceedings{serych2023planar, title={Planar Object Tracking via Weighted Optical Flow}, author={{\v{S}}er{'{y}}ch, Jon{'{a}}{\v{s}} and Matas, Ji{\v{r}}{'{i}}}, booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision}, pages={1593--1602}, year={2023} } #+end_example

** License This work is licensed under the [[https://creativecommons.org/licenses/by-nc-sa/4.0/][Attribution-NonCommercial-ShareAlike 4.0 International]] license. The ~pytracking/external/RAFT~ directory contains a slightly modified copy of [[https://github.com/princeton-vl/RAFT][RAFT]], which is licensed under BSD-3-Clause license, except for the ~pytracking/external/RAFT/raft_core/weighted_raft.py~ file, which is again licensed under the [[https://creativecommons.org/licenses/by-nc-sa/4.0/][Attribution-NonCommercial-ShareAlike 4.0 International]]. The ~demo~ directory includes samples from the [[https://www3.cs.stonybrook.edu/~hling/data/POT-210/planar_benchmark.html][POT-210]] dataset. ** Installation #+BEGIN_SRC sh python -m pip install virtualenv python -m virtualenv envs/WOFT source envs/WOFT/bin/activate python -m pip install tqdm einops opencv-python kornia==0.5.11 ipdb pandas matplotlib scipy #+END_SRC

For the liteflownet experiment, install the following #+BEGIN_SRC sh python -m pip install torch==1.8.1 torchvision==0.9.1 tqdm einops opencv-python kornia==0.5.11 ipdb pandas matplotlib scipy openmim==0.2.1 mim install mmcv-full==1.6.1

we use a very slightly modified / patched version of mmflow (included as submodule):

git submodule update --init --recursive cd pytracking/external/mmflow python -m pip install -v -e .

mim download mmflow --config liteflownet2_ft_4x1_600k_sintel_kitti_320x768 #+END_SRC

** Demo for video demo, run: #+BEGIN_SRC sh python WOFT_demo.py demo/V25_2/

or

python WOFT_demo.py demo/V24_7/ #+END_SRC

Feel free to try other configs, like for example: #+BEGIN_SRC sh python WOFT_demo.py demo/V25_2/ --config pytracking/configs/WOFT_downscale_3x.py #+END_SRC

** Acknowledgments This work was supported by Toyota Motor Europe, by CTU student grant ~SGS20/171/OHK3/3T/13~, and by the Research Center for Informatics project ~CZ.02.1.01/0.0/0.0/16_019/0000765~ funded by OP VVV.