{"total":19,"rows":[{"id":"2208.05318","title":"Generative Action Description Prompts for Skeleton-based Action Recognition","created":"2022-08-10","cited_by_count":43,"area":null},{"id":"2210.07503","title":"STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition","created":"2022-10-14","cited_by_count":43,"area":null},{"id":"2211.09590","title":"Hypergraph Transformer for Skeleton-based Action Recognition","created":"2022-11-17","cited_by_count":36,"area":null},{"id":"2110.13385","title":"IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition","created":"2021-10-26","cited_by_count":17,"area":null},{"id":"2208.05775","title":"PSUMNet: Unified Modality Part Streams are All You Need for Efficient Pose-based Action Recognition","created":"2022-08-11","cited_by_count":14,"area":null},{"id":"2104.03020","title":"Graph-based Normalizing Flow for Human Motion Generation and Reconstruction","created":"2021-04-07","cited_by_count":12,"area":null},{"id":"2112.10570","title":"Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition","created":"2021-12-20","cited_by_count":9,"area":null},{"id":"2209.10073","title":"Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition","created":"2022-09-21","cited_by_count":9,"area":null},{"id":"2408.05436","title":"A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities","created":"2024-08-10","cited_by_count":8,"area":null},{"id":"2208.08599","title":"Spatial Temporal Graph Attention Network for Skeleton-Based Action Recognition","created":"2022-08-18","cited_by_count":4,"area":null},{"id":"2405.06574","title":"Deep video representation learning: a survey","created":"2024-05-10","cited_by_count":4,"area":null},{"id":"2208.04950","title":"BabyNet: A Lightweight Network for Infant Reaching Action Recognition in Unconstrained Environments to Support Future Pediatric Rehabilitation Applications","created":"2022-08-09","cited_by_count":2,"area":null},{"id":"2409.09678","title":"A Comprehensive Methodological Survey of Human Activity Recognition Across Divers Data Modalities","created":"2024-09-15","cited_by_count":2,"area":null},{"id":"2210.06192","title":"Pose-Guided Graph Convolutional Networks for Skeleton-Based Action Recognition","created":"2022-10-10","cited_by_count":1,"area":null},{"id":"2304.04956","title":"Multi-Graph Convolution Network for Pose Forecasting","created":"2023-04-11","cited_by_count":1,"area":null},{"id":"2305.08191","title":"Is end-to-end learning enough for fitness activity recognition?","created":"2023-05-14","cited_by_count":1,"area":null},{"id":"2504.03474","title":"Multi-encoder nnU-Net outperforms transformer models with self-supervised pretraining","created":"2025-04-04","cited_by_count":1,"area":null},{"id":"2501.11007","title":"HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition","created":"2025-01-19","cited_by_count":0,"area":null},{"id":"2607.00716","title":"Partial Skeleton Visibility for Action Recognition: A Constrained Field-of-View Approach","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}