6 papers
SkeletonAgent: An Agentic Interaction Framework for Skeleton-based Action Recognition
Hongda Liu, Yunfan Liu, Changlu Wang +2
Recent advances in skeleton-based action recognition increasingly leverage semantic priors from Large Language Models (LLMs) to enrich skeletal representations. However, the LLM is…
Affinity Contrastive Learning for Skeleton-based Human Activity Understanding
Hongda Liu, Yunfan Liu, Min Ren +3
In skeleton-based human activity understanding, existing methods often adopt the contrastive learning paradigm to construct a discriminative feature space. However, many of these a…
FingerVeinSyn-5M: A Million-Scale Dataset and Benchmark for Finger Vein Recognition
Yinfan Wang, Jie Gui, Baosheng Yu +4
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the ad…
A Unified Framework for Iris Anti-Spoofing: Introducing Iris Anti-Spoofing Cross-Domain-Testing Protocol and Masked-MoE Method
Hang Zou, Chenxi Du, Ajian Liu +6
Iris recognition is widely used in high-security scenarios due to its stability and distinctiveness. However, iris images captured by different devices exhibit certain and device-r…
Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition
Hongda Liu, Yunfan Liu, Min Ren +3
In skeleton-based action recognition, a key challenge is distinguishing between actions with similar trajectories of joints due to the lack of image-level details in skeletal repre…
Balanced Representation Learning for Long-tailed Skeleton-based Action Recognition
Hongda Liu, Yunlong Wang, Min Ren +4
Skeleton-based action recognition has recently made significant progress. However, data imbalance is still a great challenge in real-world scenarios. The performance of current act…