Awesome
CATRE
This repo provides for the implementation of the ECCV'22 paper:
CATRE: Iterative Point Clouds Alignment for Category-level Object Pose Refinement<br> [arXiv][Video]
Overview
Dependencies
See INSTALL.md
Datasets
Prepare datasets folder like this:
datasets/
├── NOCS
├──REAL
├── real_test # download from http://download.cs.stanford.edu/orion/nocs/real_test.zip
├── real_train # download from http://download.cs.stanford.edu/orion/nocs/real_train.zip
└── image_set # generate from pose_data.py
├──gts # download from http://download.cs.stanford.edu/orion/nocs/gts.zip
└── real_test
├──test_init_poses # we provide
└──object_models # we provide some necesarry files, complete files can be download from http://download.cs.stanford.edu/orion/nocs/obj_models.zip
Run python scripts to prepare the datasets. (Modified from https://github.com/mentian/object-deformnet)
# NOTE: this code will directly modify the data
cd $ROOT/preprocess
python pose_data.py
Reproduce the results
The trained model has been saved at output/catre/NOCS_REAL/aug05_kpsMS_r9d_catreDisR_shared_tspcl_convPerRot_scaleexp_120e/model_final_wo_optim-82cf930e.pth
. Run the following command to reproduce the results:
./core/catre/test_catre.sh configs/catre/NOCS_REAL/aug05_kpsMS_r9d_catreDisR_shared_tspcl_convPerRot_scaleexp_120e.py 1 output/catre/NOCS_REAL/aug05_kpsMS_r9d_catreDisR_shared_tspcl_convPerRot_scaleexp_120e/model_final_wo_optim-82cf930e.pth
NOTE
NOTE that there is a small bug in the original evaluation code of NOCS w.r.t. IOU. We fixed this bug in our evaluation code and re-evaluated all the compared methods in the paper (we only revised the value of IOU and kept rotation/translation results the same, but indeed the accuracy of R/t will also change a little bit). See the revised code for details. Also thanks Peng et al. for further confirming this bug.
Training
./core/catre/train_catre.sh configs/catre/NOCS_REAL/aug05_kpsMS_r9d_catreDisR_shared_tspcl_convPerRot_scaleexp_120e.py <gpu_ids> (other args)
Testing
./core/catre/test_catre.sh configs/catre/NOCS_REAL/aug05_kpsMS_r9d_catreDisR_shared_tspcl_convPerRot_scaleexp_120e.py <gpu_ids> <ckpt_path> (other args)
Citation
If you find this repo useful in your research, please consider citing:
@InProceedings{liu_2022_catre,
title = {{CATRE:} Iterative Point Clouds Alignment for Category-level Object Pose Refinement},
author = {Liu, Xingyu and Wang, Gu and Li, Yi and Ji, Xiangyang},
booktitle = {European Conference on Computer Vision (ECCV)},
month = {October},
year = {2022}
}