P44-R1 |
Beltrán B., Richter and Heinkel |
Automated Human Movement Segmentation by Means of Human Pose
Estimation in RGB-D Videos for Climbing Motion Analysis |
https://www.scitepress.org/PublishedPapers/2022/108173/ |
P44-R2 |
Dovgalecs et al. |
Movement phase detection in climbing |
https://www.tandfonline.com/doi/abs/10.1080/19346182.2015.1064128 |
P44-R3 |
Beltrán B., Richter and Heinkel |
Climbing Technique Evaluation by Means of Skeleton Video Stream
Analysis |
https://www.mdpi.com/1424-8220/23/19/8216 |
P44-R4 |
Lea et al. |
Temporal Convolutional Networks for Action Segmentation and
Detection |
https://openaccess.thecvf.com/content_cvpr_2017/html/Lea_Temporal_Convolutional_Networks_CVPR_2017_paper.html |
P44-R5 |
Abu Farha and Gall |
MS-TCN: Multi-Stage Temporal Convolutional Network for Action
Segmentation |
https://openaccess.thecvf.com/content_CVPR_2019/html/Abu_Farha_MS-TCN_Multi-Stage_Temporal_Convolutional_Network_for_Action_Segmentation_CVPR_2019_paper.html |
P44-R6 |
Yi, Wen and Jiang |
ASFormer: Transformer for Action Segmentation |
https://arxiv.org/abs/2110.08568 |
P44-R7 |
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 |
P44-R8 |
Ahn and Lee |
Refining Action Segmentation With Hierarchical Video
Representations |
https://openaccess.thecvf.com/content/ICCV2021/html/Ahn_Refining_Action_Segmentation_With_Hierarchical_Video_Representations_ICCV_2021_paper.html |
P44-R9 |
Killick, Fearnhead and Eckley |
Optimal Detection of Changepoints With a Linear Computational
Cost |
https://www.tandfonline.com/doi/abs/10.1080/01621459.2012.737745 |
P44-R10 |
Nakamura et al. |
Segmenting Continuous Motions with Hidden Semi-markov Models and
Gaussian Processes |
https://www.frontiersin.org/articles/10.3389/fnbot.2017.00067/full |
P44-R11 |
Tamura, Aihara 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 |
P44-R12 |
Mitsuoka and Hotta |
Combining Boundary Supervision and Segment-Level Regularization for
Fine-Grained Action Segmentation — CVPR 2026 workshop paper; relevant to
boundary quality but not climbing-specific validation. |
https://openaccess.thecvf.com/content/CVPR2026W/SAUAFG/html/Mitsuoka_Combining_Boundary_Supervision_and_Segment-Level_Regularization_for_Fine-Grained_Action_Segmentation_CVPRW_2026_paper.html |
P44-R13 |
Ee et al. |
Improving Temporal Action Segmentation via Constraint-Aware Decoding
— 2026 preprint; used as exploratory support for constrained decoding,
not normative ground truth. |
https://arxiv.org/abs/2605.10149 |
P44-R14 |
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 |