Cover Image

LSTC-MDA: A Unified Framework for Long-Short Term Temporal Convolution and Mixed Data Augmentation in Skeleton-Based Action Recognition

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ding, Feng, Fu, Haisheng, Oraki, Soroush, Liang, Jie
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SCALE: Semantic- and Confidence-Aware Conditional Variational Autoencoder for Zero-shot Skeleton-based Action Recognition
by: Oraki, Soroush, et al.
Published: (2026)

LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition
by: Oraki, Soroush, et al.
Published: (2024)

Generative Data Augmentation for Skeleton Action Recognition
by: Dong, Xu, et al.
Published: (2026)

Topological Symmetry Enhanced Graph Convolution for Skeleton-Based Action Recognition
by: Liang, Zeyu, et al.
Published: (2024)

Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
by: Zhang, Jiahang, et al.
Published: (2024)

Skeleton-Based Action Recognition with Spatial-Structural Graph Convolution
by: Wang, Jingyao, et al.
Published: (2024)

Graph Convolutional Long Short-Term Memory Attention Network for Post-Stroke Compensatory Movement Detection Based on Skeleton Data
by: Fan, Jiaxing, et al.
Published: (2025)

Towards Universal Skeleton-Based Action Recognition
by: Kuang, Jidong, et al.
Published: (2026)

UniSTFormer: Unified Spatio-Temporal Lightweight Transformer for Efficient Skeleton-Based Action Recognition
by: Wu, Wenhan, et al.
Published: (2025)

STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton Sequences
by: Mehraban, Soroush, et al.
Published: (2024)

High-Performance Inference Graph Convolutional Networks for Skeleton-Based Action Recognition
by: Wang, Junyi, et al.
Published: (2023)

SBF: An Effective Representation to Augment Skeleton for Video-based Human Action Recognition
by: Peng, Zhuoxuan, et al.
Published: (2026)

HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition
by: Dong, Pengcheng, et al.
Published: (2025)

Marrying Text-to-Motion Generation with Skeleton-Based Action Recognition
by: Kuang, Jidong, et al.
Published: (2026)

An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition
by: Xu, Haojun, et al.
Published: (2024)

SkeletonAgent: An Agentic Interaction Framework for Skeleton-based Action Recognition
by: Liu, Hongda, et al.
Published: (2025)

Spatio-Temporal Joint Density Driven Learning for Skeleton-Based Action Recognition
by: Gunasekara, Shanaka Ramesh, et al.
Published: (2025)

Joint Temporal Pooling for Improving Skeleton-based Action Recognition
by: Gunasekara, Shanaka Ramesh, et al.
Published: (2024)

Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation
by: Gökay, Uzay, et al.
Published: (2025)

TSGCNeXt: Dynamic-Static Multi-Graph Convolution for Efficient Skeleton-Based Action Recognition with Long-term Learning Potential
by: Liu, Dongjingdin, et al.
Published: (2023)

Multi-Scale Spatial-Temporal Self-Attention Graph Convolutional Networks for Skeleton-based Action Recognition
by: Nakamura, Ikuo
Published: (2024)

3DM-WeConvene: Learned Image Compression with 3D Multi-Level Wavelet-Domain Convolution and Entropy Model
by: Fu, Haisheng, et al.
Published: (2025)

Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action Recognition
by: Tanaka, Nariki, et al.
Published: (2023)

MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition
by: Zheng, Naichuan, et al.
Published: (2024)

A Survey on 3D Skeleton-Based Action Recognition Using Learning Method
by: Ren, Bin, et al.
Published: (2020)

Balanced Representation Learning for Long-tailed Skeleton-based Action Recognition
by: Liu, Hongda, et al.
Published: (2023)

G3CN: Gaussian Topology Refinement Gated Graph Convolutional Network for Skeleton-Based Action Recognition
by: Ren, Haiqing, et al.
Published: (2025)

Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition
by: Zhu, Anqi, et al.
Published: (2024)

PoseBridge: Bridging the Skeletonization Gap for Zero-Shot Skeleton-Based Action Recognition
by: Lee, Sanghyeon, et al.
Published: (2026)

ReL-SAR: Representation Learning for Skeleton Action Recognition with Convolutional Transformers and BYOL
by: Naimi, Safwen, et al.
Published: (2024)

3D Skeleton-Based Action Recognition: A Review
by: Liu, Mengyuan, et al.
Published: (2025)

An Improved Graph Pooling Network for Skeleton-Based Action Recognition
by: Wu, Cong, et al.
Published: (2024)

Expressive Keypoints for Skeleton-based Action Recognition via Skeleton Transformation
by: Yang, Yijie, et al.
Published: (2024)

Neurosymbolic Framework for Concept-Driven Logical Reasoning in Skeleton-Based Human Action Recognition
by: Ilyas, Talha, et al.
Published: (2026)

Skeleton-Based Human Action Recognition with Noisy Labels
by: Xu, Yi, et al.
Published: (2024)

Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections
by: Zhou, Youwei, et al.
Published: (2024)

Heterogeneous Skeleton-Based Action Representation Learning
by: Wang, Hongsong, et al.
Published: (2025)

FreqMixFormerV2: Lightweight Frequency-aware Mixed Transformer for Human Skeleton Action Recognition
by: Wu, Wenhan, et al.
Published: (2024)

Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition
by: Lin, Lilang, et al.
Published: (2024)

Recovering Complete Actions for Cross-dataset Skeleton Action Recognition
by: Liu, Hanchao, et al.
Published: (2024)