most citedTowards Physical World Backdoor Attacks against Skeleton Action Recognition

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Image Diffusion Models Are Good 3D Human Motion Generators

Siyuan Yang, Chong Wang, Hao Cheng +4

Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different joint layouts. We investigate…

cs.CV2026

TAME:Topology-Aware Text-Driven Motion Editing across Heterogeneous Humanoid Skeletons

Qichen Zheng, Siyuan Yang, Chong Wang +4

Text-driven motion editing modifies an existing motion sequence according to a text instruction while preserving the content of the source motion. Existing methods are typically bu…

cs.CV2026

Skeleton-to-Image Encoding: Enabling Skeleton Representation Learning via Vision-Pretrained Models

Siyuan Yang, Jun Liu, Hao Cheng +5

Recent advances in large-scale pretrained vision models have demonstrated impressive capabilities across a wide range of downstream tasks, including cross-modal and multi-modal sce…

cs.CR2024★ 1 cited

Towards Physical World Backdoor Attacks against Skeleton Action Recognition

Qichen Zheng, Yi Yu, Siyuan Yang +3

Skeleton Action Recognition (SAR) has attracted significant interest for its efficient representation of the human skeletal structure. Despite its advancements, recent studies have…

cs.CR2024

Unlearnable Examples Detection via Iterative Filtering

Yi Yu, Qichen Zheng, Siyuan Yang +6

Deep neural networks are proven to be vulnerable to data poisoning attacks. Recently, a specific type of data poisoning attack known as availability attacks has led to the failure…