99 citations · 106 across the 6 of their papers we have counts for
6 papers
Robo-GS: A Physics Consistent Spatial-Temporal Model for Robotic Arm with Hybrid Representation
Haozhe Lou, Yurong Liu, Yike Pan +9
Real2Sim2Real plays a critical role in robotic arm control and reinforcement learning, yet bridging this gap remains a significant challenge due to the complex physical properties…
ASSIST: Interactive Scene Nodes for Scalable and Realistic Indoor Simulation
Zhide Zhong, Jiakai Cao, Songen Gu +6
We present ASSIST, an object-wise neural radiance field as a panoptic representation for compositional and realistic simulation. Central to our approach is a novel scene node data…
MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving
Zirui Wu, Tianyu Liu, Liyi Luo +13
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner c…
Eff-3DPSeg: 3D organ-level plant shoot segmentation using annotation-efficient point clouds
Liyi Luo, Xintong Jiang, Yu Yang +4
Reliable and automated 3D plant shoot segmentation is a core prerequisite for the extraction of plant phenotypic traits at the organ level. Combining deep learning and point clouds…
VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling
Beiwen Tian, Liyi Luo, Hao Zhao +1
Recently, 3D scenes parsing with deep learning approaches has been a heating topic. However, current methods with fully-supervised models require manually annotated point-wise supe…
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck
Liyi Luo, Beiwen Tian, Hao Zhao +1
Semantic understanding of 3D point clouds is important for various robotics applications. Given that point-wise semantic annotation is expensive, in this paper, we address the chal…