6 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
Exploring Adaptive Masked Reconstruction for Self-Supervised Skeleton-Based Action Recognition
Shengkai Sun, Zhiyong Cheng, Zefan Zhang +3
Recently, masked skeleton reconstruction models have emerged as strong action representation learners, driving significant progress in self-supervised skeleton-based action recogni…
VERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models
Zefan Zhang, Kehua Zhu, Shijie Jiang +3
Video Large Language Models (VideoLLMs) exhibit various types of hallucinations. Existing research has primarily focused on hallucinations involving the presence of events, objects…
Towards Efficient General Feature Prediction in Masked Skeleton Modeling
Shengkai Sun, Zefan Zhang, Jianfeng Dong +3
Recent advances in the masked autoencoder (MAE) paradigm have significantly propelled self-supervised skeleton-based action recognition. However, most existing approaches limit rec…
Unified Multi-modal Unsupervised Representation Learning for Skeleton-based Action Understanding
Shengkai Sun, Daizong Liu, Jianfeng Dong +5
Unsupervised pre-training has shown great success in skeleton-based action understanding recently. Existing works typically train separate modality-specific models, then integrate…
Hierarchical Contrast for Unsupervised Skeleton-based Action Representation Learning
Jianfeng Dong, Shengkai Sun, Zhonglin Liu +3
This paper targets unsupervised skeleton-based action representation learning and proposes a new Hierarchical Contrast (HiCo) framework. Different from the existing contrastive-bas…