3 citations · 4 across the 10 of their papers we have counts for
6 papers · 1 filter
ECHO: Event-Augmented Context with Hindsight and Outlook for Wrist-Only Manipulation
Xinyue Wang, Yicheng Jiang, Zesen Gan +8
Learning-based manipulation policies relying on RGB cameras often suffer from degraded observations under extreme exposure. Event cameras mitigate this degradation by asynchronousl…
AR-WAM: A Visual-Conditioned Agent-Ready World Action Model for Robotic Manipulation
Yicheng Jiang, Zesen Gan, Xiaobo Wang +8
As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action (VLA) models and world actio…
OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal
Qinming Zhou, Chenxi Sun, Deyang Kong +6
Real-world object removal is challenging due to two key difficulties: the target object's non-local effects, such as shadows and reflections, which are difficult to model, and the…
MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy
Jiaxu Wang, Junhao He, Jingkai Sun +5
Learning real-world dynamics from visual observations is crucial for various domains. A common strategy is to calibrate simulators by estimating physical parameters, yet accuracy i…
Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation
Yicheng Jiang, Jiaxu Wang, Junhao He +8
Current 3D-aware pretraining methods for embodied perception and manipulation are largely built on differentiable rendering frameworks, producing either fully implicit neural field…
MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation
Jiaxu Wang, Yicheng Jiang, Tianlun He +8
World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoni…