1 citations · 1 across the 7 of their papers we have counts for
7 papers
TacPAC: Tactile Prediction and Real-Time Action Correction in World-Action Models for Contact-Rich Manipulation
Zipei Ma, Xiaofei Wei, Junzhe Jiang +2
World-action models guide action generation with predicted future observations, but vision-centric predictions miss the local contact cues that decide contact-rich manipulation. Ho…
Inter-Reflective Gaussian Splatting for Robust and Efficient Inverse Rendering
Chun Gu, Xiaofei Wei, Zixuan Zeng +2
Faithful inverse rendering requires visibility and indirect radiance to explain secondary illumination and inter-reflection, yet rasterization-oriented Gaussian representations do…
From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation
Yajie Li, Bozhou Zhang, Chun Gu +5
Video generation models offer a promising imagination mechanism for robot manipulation by predicting long-horizon future observations, but effectively exploiting these imagined fut…
NavOL: Navigation Policy with Online Imitation Learning
Xiaofei Wei, Chun Gu, Li Zhang
Learning robust navigation policies remains a core challenge in robotics. Offline imitation learning suffers from distribution shift and compounding errors at rollout, while reinfo…
RealEngine: Simulating Autonomous Driving in Realistic Context
Junzhe Jiang, Nan Song, Jingyu Li +2
Driving simulation plays a crucial role in developing reliable driving agents by providing controlled, evaluative environments. To enable meaningful assessments, a high-quality dri…
TensoFlow: Tensorial Flow-based Sampler for Inverse Rendering
Chun Gu, Xiaofei Wei, Li Zhang +1
Inverse rendering aims to recover scene geometry, material properties, and lighting from multi-view images. Given the complexity of light-surface interactions, importance sampling…
GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting
Junzhe Jiang, Chun Gu, Yurui Chen +1
LiDAR novel view synthesis (NVS) has emerged as a novel task within LiDAR simulation, offering valuable simulated point cloud data from novel viewpoints to aid in autonomous drivin…