{"url":"/dataset/n-ucla","name":"N-UCLA","full_name":"Northwestern-UCLA Multiview Action 3D Dataset","description_markdown":"The Multiview 3D event dataset is capture by me and Xiaohan Nie in UCLA. it contains RGB, depth and human skeleton data captured simultaneously by three Kinect cameras. This dataset include 10 action categories: pick up with one hand, pick up with two hands, drop trash, walk around, sit down, stand up, donning, doffing, throw, carry. Each action is performed by 10 actors. This dataset contains data taken from a variety of viewpoints.\r\nThe dataset can be found in part-1, part-2 part-3, part-4, part-5, part-6, part-7, part-8, part-9, part-10, part-11, part-12, part-13, part-14, part-15, part-16,\r\nWe also created a version of the dataset that only contains RGB videos: RGB videos only.","description_withheld":null,"homepage":"http://wangjiangb.github.io/my_data.html","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"},{"name":"Skeleton Based Action Recognition","url":"/task/skeleton-based-action-recognition","datasets_with_task":"/datasets/task/skeleton-based-action-recognition"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["N-UCLA"],"data_loaders":[],"num_papers_in_archive":30,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/skeleton-based-action-recognition-on-n-ucla","task":"Skeleton Based Action Recognition","dataset_variant":"N-UCLA","rows":25,"metrics":["Accuracy","Data Modality (Joint, Bone, Motion)"],"first_row_in_archive_order":{"model":"DSCNet (RGB + Pose)","paper":"/paper/a-dense-sparse-complementary-network-for","metrics":{"Accuracy":"99.1"},"code_links":[{"title":"Maxchengqin/DSCNet","url":"https://github.com/Maxchengqin/DSCNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/action-recognition-on-n-ucla","task":"Action Recognition","dataset_variant":"N-UCLA","rows":1,"metrics":["Accuracy (Cross-Subject)","Accuracy (Cross-View)"],"first_row_in_archive_order":{"model":"DVANet","paper":"/paper/dvanet-disentangling-view-and-action-features","metrics":{"Accuracy (Cross-Subject)":"94.4","Accuracy (Cross-View)":"96.5"},"code_links":[{"title":"NyleSiddiqui/MultiView_Actions","url":"https://github.com/NyleSiddiqui/MultiView_Actions"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/action-recognition-in-real-world-ambient","title":"Action Recognition in Real-World Ambient Assisted Living Environment","date":"2025-03-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dstsa-gcn-advancing-skeleton-based-gesture","title":"DSTSA-GCN: Advancing Skeleton-Based Gesture Recognition with Semantic-Aware Spatio-Temporal Topology Modeling","date":"2025-01-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/action-recognition-for-privacy-preserving","title":"Action Recognition for Privacy-Preserving Ambient Assisted Living","date":"2024-08-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/joint-partition-group-attention-for-skeleton","title":"Joint-Partition Group Attention for skeleton-based action recognition","date":"2024-07-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-modality-co-learning-for-efficient-1","title":"Multi-Modality Co-Learning for Efficient Skeleton-based Action Recognition","date":"2024-07-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":9,"samples_unverified":1,"pointer_only_for_licence":10,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/skateformer-skeletal-temporal-transformer-for","title":"SkateFormer: Skeletal-Temporal Transformer for Human Action Recognition","date":"2024-03-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/a-dense-sparse-complementary-network-for","title":"A Dense-Sparse Complementary Network for Human Action Recognition based on RGB and Skeleton Modalities","date":"2023-12-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dvanet-disentangling-view-and-action-features","title":"DVANet: Disentangling View and Action Features for Multi-View Action Recognition","date":"2023-12-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/language-knowledge-assisted-representation","title":"Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition","date":"2023-05-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-scale-spatial-temporal-convolutional","title":"Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognition","date":"2023-05-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/temporal-decoupling-graph-convolutional","title":"Temporal Decoupling Graph Convolutional Network for Skeleton-based Gesture Recognition","date":"2023-05-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/action-capsules-human-skeleton-action","title":"Action Capsules: Human Skeleton Action Recognition","date":"2023-01-30","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/hierarchically-decomposed-graph-convolutional","title":"Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition","date":"2022-08-23","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":8,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/language-supervised-training-for-skeleton","title":"Generative Action Description Prompts for Skeleton-based Action Recognition","date":"2022-08-10","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":7,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/skeleton-based-action-recognition-via","title":"Skeleton-based Action Recognition via Temporal-Channel Aggregation","date":"2022-05-31","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/mmnet-a-model-based-multimodal-network-for","title":"MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D Videos","date":"2022-05-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/infogcn-representation-learning-for-human","title":"InfoGCN: Representation Learning for Human Skeleton-Based Action Recognition","date":"2022-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/channel-wise-topology-refinement-graph","title":"Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition","date":"2021-07-26","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":2,"samples_unverified":3,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/vpn-rethinking-video-pose-embeddings-for","title":"VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Living","date":"2021-05-17","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hierarchical-action-classification-with","title":"Hierarchical Action Classification with Network Pruning","date":"2020-07-30","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/vpn-learning-video-pose-embedding-for","title":"VPN: Learning Video-Pose Embedding for Activities of Daily Living","date":"2020-07-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/eleatt-rnn-adding-attentiveness-to-neurons-in","title":"EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks","date":"2019-09-03","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/semantics-guided-neural-networks-for","title":"Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition","date":"2019-04-02","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":3,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/action-machine-rethinking-action-recognition","title":"Action Machine: Rethinking Action Recognition in Trimmed Videos","date":"2018-12-14","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/view-adaptive-neural-networks-for-high","title":"View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition","date":"2018-04-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":6,"samples_unverified":6,"pointer_only_for_licence":9,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/glimpse-clouds-human-activity-recognition","title":"Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points","date":"2018-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":8,"samples_harvested":65,"samples_ran":39,"samples_unverified":26,"pointer_only_for_licence":23,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}