Just-Go-with-the-Flow-Self-Supervised-Scene-Flow-Estimation
Just-Go-with-the-Flow-Self-Supervised-Scene-Flow-Estimation copied to clipboard
HimangiM
Self-supervised method for scene-flow estimation of LiDAR point clouds. Method is trained and tested on the nuScenes and KITTI datasets in TensorFlow. (CVPR 2020)
Bumps [jinja2](https://github.com/pallets/jinja) from 2.10.1 to 2.11.3. Release notes Sourced from jinja2's releases. 2.11.3 This contains a fix for a speed issue with the urlize filter. urlize is likely to be...
![dependabot[bot] avatar](https://avatars.githubusercontent.com/in/29110?v=4 "dependabot[bot] avatar"){kind=avatar}
@HimangiM Hi, in your command_train_cycle_nuscenes.sh file, there seems an model named model_concat_upsa_1nn_cycle_nuscenes. However, we couldn't find it in your repo. Would you mind provide it later?
Could you provide the processed nuScenes datasets or the processing codes for nuScenes datasets? Thanks.
Bumps [bleach](https://github.com/mozilla/bleach) from 3.1.0 to 3.3.0. Changelog Sourced from bleach's changelog. Version 3.3.0 (February 1st, 2021) Backwards incompatible changes clean escapes HTML comments even when strip_comments=False Security fixes Fix bug...
README indicates that you would release the pre-trained model soon, but that was many months ago. When do you plan on doing this?
Could you please release a Pytorch version of the code? Thanks~
