32 citations · 79 across the 11 of their papers we have counts for
11 papers
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving
Lingdong Kong, Xiang Xu, Jiawei Ren +5
Efficient data utilization is crucial for advancing 3D scene understanding in autonomous driving, where reliance on heavily human-annotated LiDAR point clouds challenges fully supe…
Any-point Trajectory Modeling for Policy Learning
Chuan Wen, Xingyu Lin, John So +4
Learning from demonstration is a powerful method for teaching robots new skills, and having more demonstration data often improves policy learning. However, the high cost of collec…
RGBManip: Monocular Image-based Robotic Manipulation through Active Object Pose Estimation
Boshi An, Yiran Geng, Kai Chen +3
Robotic manipulation requires accurate perception of the environment, which poses a significant challenge due to its inherent complexity and constantly changing nature. In this con…
Visual-Kinematics Graph Learning for Procedure-agnostic Instrument Tip Segmentation in Robotic Surgeries
Jiaqi Liu, Yonghao Long, Kai Chen +3
Accurate segmentation of surgical instrument tip is an important task for enabling downstream applications in robotic surgery, such as surgical skill assessment, tool-tissue intera…
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation
Jun Zhou, Kai Chen, Linlin Xu +2
One critical challenge in 6D object pose estimation from a single RGBD image is efficient integration of two different modalities, i.e., color and depth. In this work, we tackle th…
Value-Informed Skill Chaining for Policy Learning of Long-Horizon Tasks with Surgical Robot
Tao Huang, Kai Chen, Wang Wei +3
Reinforcement learning is still struggling with solving long-horizon surgical robot tasks which involve multiple steps over an extended duration of time due to the policy explorati…
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
Youquan Liu, Lingdong Kong, Jun Cen +5
Recent advancements in vision foundation models (VFMs) have opened up new possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a novel fram…
Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot
Tao Huang, Kai Chen, Bin Li +2
Task automation of surgical robot has the potentials to improve surgical efficiency. Recent reinforcement learning (RL) based approaches provide scalable solutions to surgical auto…
StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS
Kai Chen, Stephen James, Congying Sui +3
Most existing methods for category-level pose estimation rely on object point clouds. However, when considering transparent objects, depth cameras are usually not able to capture m…
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking
Kai Chen, Rui Cao, Stephen James +4
In this paper, we propose an iterative self-training framework for sim-to-real 6D object pose estimation to facilitate cost-effective robotic grasping. Given a bin-picking scenario…
Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks
Jiaze Wang, Kai Chen, Qi Dou
Category-level 6D pose estimation, aiming to predict the location and orientation of unseen object instances, is fundamental to many scenarios such as robotic manipulation and augm…