P47-R1 |
Pushkarna, Zaldivar and Kjartansson |
Data Cards: Purposeful and Transparent Dataset Documentation for
Responsible AI |
https://doi.org/10.1145/3531146.3533231 |
P47-R2 |
MLCommons Croissant Working Group |
Croissant Format Specification 1.1 |
https://docs.mlcommons.org/croissant/docs/croissant-spec-1.1.html |
P47-R3 |
W3C Provenance Working Group |
PROV-O: The PROV Ontology |
https://www.w3.org/TR/prov-o/ |
P47-R4 |
ASAM e.V. |
ASAM OpenLABEL 1.0.0 |
https://www.asam.net/standards/detail/openlabel/ |
P47-R5 |
CVAT.ai Corporation |
CVAT Dataset Formats |
https://docs.cvat.ai/docs/dataset_management/formats/ |
P47-R6 |
CVAT.ai Corporation |
CVAT Quality Control |
https://docs.cvat.ai/docs/qa-analytics/quality-control/ |
P47-R7 |
CVAT.ai Corporation |
CVAT Consensus-Based Annotation |
https://docs.cvat.ai/docs/qa-analytics/consensus/ |
P47-R8 |
Cohen |
A Coefficient of Agreement for Nominal Scales |
https://doi.org/10.1177/001316446002000104 |
P47-R9 |
Fleiss |
Measuring Nominal Scale Agreement Among Many Raters |
https://doi.org/10.1037/h0031619 |
P47-R10 |
Krippendorff |
Computing Krippendorff’s Alpha-Reliability |
https://repository.upenn.edu/asc_papers/43/ |
P47-R11 |
Shrout and Fleiss |
Intraclass Correlations: Uses in Assessing Rater Reliability |
https://doi.org/10.1037/0033-2909.86.2.420 |
P47-R12 |
Lin |
A Concordance Correlation Coefficient to Evaluate
Reproducibility |
https://doi.org/10.2307/2532051 |
P47-R13 |
Dawid and Skene |
Maximum Likelihood Estimation of Observer Error-Rates Using the EM
Algorithm |
https://doi.org/10.2307/2346806 |
P47-R14 |
Warfield, Zou and Wells |
Simultaneous Truth and Performance Level Estimation (STAPLE) |
https://doi.org/10.1109/TMI.2004.828354 |
P47-R15 |
Lin et al. |
Microsoft COCO: Common Objects in Context |
https://arxiv.org/abs/1405.0312 |
P47-R16 |
Heilbron, Escorcia, Ghanem and Niebles |
ActivityNet: A Large-Scale Video Benchmark for Human Activity
Understanding |
https://openaccess.thecvf.com/content_cvpr_2015/html/Heilbron_ActivityNet_A_Large-Scale_2015_CVPR_paper.html |
P47-R17 |
Zhao, Torralba, Torresani and Yan |
HACS: Human Action Clips and Segments Dataset for Recognition and
Temporal Localization |
https://openaccess.thecvf.com/content_ICCV_2019/html/Zhao_HACS_Human_Action_Clips_and_Segments_Dataset_for_Recognition_and_ICCV_2019_paper.html |
P47-R18 |
Yu et al. |
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask
Learning |
https://openaccess.thecvf.com/content_CVPR_2020/html/Yu_BDD100K_A_Diverse_Driving_Dataset_for_Heterogeneous_Multitask_Learning_CVPR_2020_paper.html |
P47-R19 |
DVC Project |
Data Version Control Documentation |
https://dvc.org/doc |
P47-R20 |
National Institute of Standards and Technology |
Artificial Intelligence Risk Management Framework (AI RMF 1.0) |
https://doi.org/10.6028/NIST.AI.100-1 |
P47-R21 |
National Institute of Standards and Technology |
NIST Privacy Framework 1.0 |
https://www.nist.gov/privacy-framework/privacy-framework |
P47-R22 |
European Parliament and Council of the European Union |
Regulation (EU) 2016/679 — General Data Protection Regulation |
https://eur-lex.europa.eu/eli/reg/2016/679/oj |
P47-R23 |
Stanovcic, Sliwowski and Lee |
ATLAS: An Annotation Tool for Long-Horizon Robotic Action
Segmentation |
https://arxiv.org/abs/2604.26637 |
P47-R24 |
Helvaci and Cheung |
Boundary-Centric Active Learning for Temporal Action
Segmentation |
https://arxiv.org/abs/2604.15173 |
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-R27 |
Gebru et al. |
Datasheets for Datasets |
https://doi.org/10.1145/3458723 |