P46-R1 |
Kimura, Tamura and Yamamoto |
Extraction of Climbing Moves for Performance Quantification in
Bouldering |
https://www.jstage.jst.go.jp/article/sit/2025/0/2025_A-2-2/_article/-char/en |
P46-R2 |
Yan, Xiong and Lin |
Spatial Temporal Graph Convolutional Networks for Skeleton-Based
Action Recognition |
https://ojs.aaai.org/index.php/aaai/article/view/12328 |
P46-R3 |
Duan, Zhao, Chen, Lin and Dai |
Revisiting Skeleton-Based Action Recognition |
https://openaccess.thecvf.com/content/CVPR2022/html/Duan_Revisiting_Skeleton-Based_Action_Recognition_CVPR_2022_paper.html |
P46-R4 |
Chen, Zhang, Yuan, Li, Deng and Hu |
Channel-Wise Topology Refinement Graph Convolution for
Skeleton-Based Action Recognition |
https://openaccess.thecvf.com/content/ICCV2021/html/Chen_Channel-Wise_Topology_Refinement_Graph_Convolution_for_Skeleton-Based_Action_Recognition_ICCV_2021_paper.html |
P46-R5 |
Zhu, Ma, Liu, Liu, Wu and Wang |
MotionBERT: A Unified Perspective on Learning Human Motion
Representations |
https://openaccess.thecvf.com/content/ICCV2023/html/Zhu_MotionBERT_A_Unified_Perspective_on_Learning_Human_Motion_Representations_ICCV_2023_paper.html |
P46-R6 |
Yi, Wen and Jiang |
ASFormer: Transformer for Action Segmentation |
https://bmva-archive.org.uk/bmvc/2021/conference/papers/paper_0183.html |
P46-R7 |
Ishikawa, Kasai, Aoki and Kataoka |
Alleviating Over-Segmentation Errors by Detecting Action
Boundaries |
https://openaccess.thecvf.com/content/WACV2021/html/Ishikawa_Alleviating_Over-Segmentation_Errors_by_Detecting_Action_Boundaries_WACV_2021_paper.html |
P46-R8 |
Liu, Li, Dinh, Jiang, Shah and Xu |
Diffusion Action Segmentation |
https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Diffusion_Action_Segmentation_ICCV_2023_paper.html |
P46-R9 |
Li, Abu Farha and Gall |
Temporal Action Segmentation From Timestamp Supervision |
https://openaccess.thecvf.com/content/CVPR2021/html/Li_Temporal_Action_Segmentation_From_Timestamp_Supervision_CVPR_2021_paper.html |
P46-R10 |
Bendale and Boult |
Towards Open Set Deep Networks |
https://openaccess.thecvf.com/content_cvpr_2016/html/Bendale_Towards_Open_Set_CVPR_2016_paper.html |
P46-R11 |
Bao, Yu and Kong |
Evidential Deep Learning for Open Set Action Recognition |
https://openaccess.thecvf.com/content/ICCV2021/html/Bao_Evidential_Deep_Learning_for_Open_Set_Action_Recognition_ICCV_2021_paper.html |
P46-R12 |
Zhao, Du, Hoogs and Funk |
Open Set Action Recognition via Multi-Label Evidential Learning |
https://openaccess.thecvf.com/content/CVPR2023/html/Zhao_Open_Set_Action_Recognition_via_Multi-Label_Evidential_Learning_CVPR_2023_paper.html |
P46-R13 |
Zhai, Liu, Wu, Wu, Zhou, Doermann, Yuan and Hua |
SOAR: Scene-debiasing Open-set Action Recognition |
https://openaccess.thecvf.com/content/ICCV2023/html/Zhai_SOAR_Scene-debiasing_Open-set_Action_Recognition_ICCV_2023_paper.html |
P46-R14 |
Guo, Pleiss, Sun and Weinberger |
On Calibration of Modern Neural Networks |
https://proceedings.mlr.press/v70/guo17a.html |
P46-R15 |
Dabah and Tirer |
On Temperature Scaling and Conformal Prediction of Deep
Classifiers |
https://proceedings.mlr.press/v267/dabah25a.html |
P46-R16 |
Khosla et al. |
Supervised Contrastive Learning |
https://proceedings.neurips.cc/paper/2020/hash/d89a66c7c80a29b1bdbab0f2a1a94af8-Abstract.html |
P46-R17 |
Cui, Jia, Lin and Belongie |
Class-Balanced Loss Based on Effective Number of Samples |
https://openaccess.thecvf.com/content_CVPR_2019/html/Cui_Class-Balanced_Loss_Based_on_Effective_Number_of_Samples_CVPR_2019_paper.html |
P46-R18 |
Lin, Goyal, Girshick, He and Dollar |
Focal Loss for Dense Object Detection |
https://openaccess.thecvf.com/content_ICCV_2017/html/Lin_Focal_Loss_for_ICCV_2017_paper.html |
P46-R19 |
Maschek and Schedl |
SPEED21: Speed Climbing Motion Dataset |
https://doi.org/10.1145/3475722.3482795 |
P46-R20 |
Boulanger, Seifert, Herault and Coeurjolly |
Automatic sensor-based detection and classification of climbing
activities |
https://arxiv.org/abs/1508.04153 |
P46-R21 |
Yan et al. |
CIMI4D: A Large Multimodal Climbing Motion Dataset Under Human-Scene
Interactions |
https://openaccess.thecvf.com/content/CVPR2023/html/Yan_CIMI4D_A_Large_Multimodal_Climbing_Motion_Dataset_Under_Human-Scene_Interactions_CVPR_2023_paper.html |
P46-R22 |
Yan et al. |
ClimbingCap: Multi-Modal Dataset and Method for Rock Climbing in
World Coordinate |
https://openaccess.thecvf.com/content/CVPR2025/html/Yan_ClimbingCap_Multi-Modal_Dataset_and_Method_for_Rock_Climbing_in_World_CVPR_2025_paper.html |
P46-R23 |
Maschek and Schedl |
The Way Up: A Dataset for Hold Usage Detection in Sport
Climbing |
https://openaccess.thecvf.com/content/CVPR2025W/CVSPORTS/html/Maschek_The_Way_Up_A_Dataset_for_Hold_Usage_Detection_in_CVPRW_2025_paper.html |
P46-R24 |
Bertinetto, Mueller, Tertikas, Samangooei and Lord |
Making Better Mistakes: Leveraging Class Hierarchies With Deep
Networks |
https://openaccess.thecvf.com/content_CVPR_2020/html/Bertinetto_Making_Better_Mistakes_Leveraging_Class_Hierarchies_With_Deep_Networks_CVPR_2020_paper.html |
P46-R25 |
Geifman and El-Yaniv |
SelectiveNet: A Deep Neural Network with an Integrated Reject
Option |
https://proceedings.mlr.press/v97/geifman19a.html |
P46-R26 |
Mitchell et al. |
Model Cards for Model Reporting |
https://doi.org/10.1145/3287560.3287596 |
P46-R27 |
Gebru et al. |
Datasheets for Datasets |
https://doi.org/10.1145/3458723 |