| --- |
| license: apache-2.0 |
| language: |
| - en |
| metrics: |
| - accuracy |
| --- |
| |
| # \[NeurIPS 2024\] CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition |
|
|
| ArXiv: https://arxiv.org/abs/2410.07153 |
|
|
| Github: https://github.com/Necolizer/CHASE |
|
|
| Checkpoints of best backbone (+CHASE) for each benchmark: |
| - NTU Mutual 11 (XSub): STSA-Net (+CHASE) |
| - NTU Mutual 11 (XView): CTR-GCN (+CHASE) |
| - NTU Mutual 26 (XSub): InfoGCN (+CHASE) |
| - NTU Mutual 26 (XSet): InfoGCN (+CHASE) |
| - H2O: STSA-Net (+CHASE) |
| - Assembly101 (Action): CTR-GCN (+CHASE) |
| - Collective Activity: CTR-GCN (+CHASE) |
| - Volleyball (Original): CTR-GCN (+CHASE) |
|
|
| ## Citation |
| ``` |
| @inproceedings{NEURIPS2024_wen2024chase, |
| author = {Wen, Yuhang and Liu, Mengyuan and Wu, Songtao and Ding, Beichen}, |
| booktitle = {Advances in Neural Information Processing Systems}, |
| editor = {A. Globerson and L. Mackey and D. Belgrave and A. Fan and U. Paquet and J. Tomczak and C. Zhang}, |
| pages = {9388--9420}, |
| publisher = {Curran Associates, Inc.}, |
| title = {CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition}, |
| url = {https://proceedings.neurips.cc/paper_files/paper/2024/file/11f5520daf9132775e8604e89f53925a-Paper-Conference.pdf}, |
| volume = {37}, |
| year = {2024} |
| } |
| ``` |
