13 citations · 25 across the 10 of their papers we have counts for
10 papers
UniDexTok: A Unified Dexterous Hand Tokenizer from Real Data
Dong Fang, Youjun Wu, Yuanxin Zhong +4
Dexterous hands are essential for fine-grained manipulation, but their hardware designs vary substantially across embodiments. Differences in kinematics, joint definitions, and deg…
HT-Bench: Benchmarking and Learning Dexterous Full-Hand Tactile Representations with Egocentric Vision
Yuzhe Huang, Jiaping Wu, Jiaming Jiang +8
Establishing a universal benchmark for tactile representation learning in robotic manipulation remains challenging due to the diversity of tactile sensor designs, data formats, and…
Enhancing End-to-End Autonomous Driving with Risk Semantic Distillaion from VLM
Jack Qin, Zhitao Wang, Yinan Zheng +4
The autonomous driving (AD) system has exhibited remarkable performance in complex driving scenarios. However, generalization is still a key limitation for the current system, whic…
Real-time Semantic 3D Dense Occupancy Mapping with Efficient Free Space Representations
Yuanxin Zhong, Huei Peng
A real-time semantic 3D occupancy mapping framework is proposed in this paper. The mapping framework is based on the Bayesian kernel inference strategy from the literature. Two nov…
VIN: Voxel-based Implicit Network for Joint 3D Object Detection and Segmentation for Lidars
Yuanxin Zhong, Minghan Zhu, Huei Peng
A unified neural network structure is presented for joint 3D object detection and point cloud segmentation in this paper. We leverage rich supervision from both detection and segme…
Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
Minghan Zhu, Songan Zhang, Yuanxin Zhong +3
This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera. Most previous monocular 3D vehicle detection algorithms focu…
Differentiable Computational Geometry for 2D and 3D machine learning
Yuanxin Zhong
With the growth of machine learning algorithms with geometry primitives, a high-efficiency library with differentiable geometric operators are desired. We present an optimized Diff…
Uncertainty-Aware Voxel based 3D Object Detection and Tracking with von-Mises Loss
Yuanxin Zhong, Minghan Zhu, Huei Peng
Object detection and tracking is a key task in autonomy. Specifically, 3D object detection and tracking have been an emerging hot topic recently. Although various methods have been…
Monocular Depth Prediction through Continuous 3D Loss
Minghan Zhu, Maani Ghaffari, Yuanxin Zhong +4
This paper reports a new continuous 3D loss function for learning depth from monocular images. The dense depth prediction from a monocular image is supervised using sparse LIDAR po…
Mcity Data Collection for Automated Vehicles Study
Yiqun Dong, Yuanxin Zhong, Wenbo Yu +5
The main goal of this paper is to introduce the data collection effort at Mcity targeting automated vehicle development. We captured a comprehensive set of data from a set of perce…