3 papers
cs.RO2025
Human2Robot: Learning Robot Actions from Paired Human-Robot Videos
Sicheng Xie, Haidong Cao, Zejia Weng +6
Distilling knowledge from human demonstrations is a promising way for robots to learn and act. Existing methods, which often rely on coarsely-aligned video pairs, are typically con…
cs.CV2025
FreezeVLA: Action-Freezing Attacks against Vision-Language-Action Models
Xin Wang, Jie Li, Zejia Weng +9
Vision-Language-Action (VLA) models are driving rapid progress in robotics by enabling agents to interpret multimodal inputs and execute complex, long-horizon tasks. However, their…
cs.CV2024
GenRec: Unifying Video Generation and Recognition with Diffusion Models
Zejia Weng, Xitong Yang, Zhen Xing +2
Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether suc…