55 citations · 136 across the 18 of their papers we have counts for
18 papers
Digging Into Uncertainty-based Pseudo-label for Robust Stereo Matching
Zhelun Shen, Xibin Song, Yuchao Dai +3
Due to the domain differences and unbalanced disparity distribution across multiple datasets, current stereo matching approaches are commonly limited to a specific dataset and gene…
A Representation Separation Perspective to Correspondences-free Unsupervised 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +3
3D point cloud registration in remote sensing field has been greatly advanced by deep learning based methods, where the rigid transformation is either directly regressed from the t…
End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +3
Even though considerable progress has been made in deep learning-based 3D point cloud processing, how to obtain accurate correspondences for robust registration remains a major cha…
Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
Lina Liu, Xibin Song, Mengmeng Wang +2
Remarkable results have been achieved by DCNN based self-supervised depth estimation approaches. However, most of these approaches can only handle either day-time or night-time ima…
MapFusion: A General Framework for 3D Object Detection with HDMaps
Jin Fang, Dingfu Zhou, Xibin Song +1
3D object detection is a key perception component in autonomous driving. Most recent approaches are based on Lidar sensors only or fused with cameras. Maps (e.g., High Definition M…
IAFA: Instance-aware Feature Aggregation for 3D Object Detection from a Single Image
Dingfu Zhou, Xibin Song, Yuchao Dai +5
3D object detection from a single image is an important task in Autonomous Driving (AD), where various approaches have been proposed. However, the task is intrinsically ambiguous a…
FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion
Lina Liu, Xibin Song, Xiaoyang Lyu +4
Depth completion aims to recover a dense depth map from a sparse depth map with the corresponding color image as input. Recent approaches mainly formulate depth completion as a one…
AES: Autonomous Excavator System for Real-World and Hazardous Environments
Jinxin Zhao, Pinxin Long, Liyang Wang +5
Excavators are widely used for material-handling applications in unstructured environments, including mining and construction. The size of the global market of excavators is 44.12…
Optimization-Based Framework for Excavation Trajectory Generation
Yajue Yang, Pinxin Long, Jia Pan +2
In this paper, we present a novel optimization-based framework for autonomous excavator trajectory generation under various objectives, including minimum joint displacement and min…
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving
Feixiang Lu, Zongdai Liu, Xibin Song +8
We present a novel approach to detect, segment, and reconstruct complete textured 3D models of vehicles from a single image for autonomous driving. Our approach combines the streng…
Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution
Xibin Song, Yuchao Dai, Dingfu Zhou +4
Despite the remarkable progresses made in deep-learning based depth map super-resolution (DSR), how to tackle real-world degradation in low-resolution (LR) depth maps remains a maj…
PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo Matching
Zhelun Shen, Yuchao Dai, Xibin Song +3
Existing deep learning based stereo matching methods either focus on achieving optimal performances on the target dataset while with poor generalization for other datasets or focus…
Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator
Yajue Yang, Jia Pan, Pinxin Long +2
In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates th…
Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem
Liu Liu, Dylan Campbell, Hongdong Li +3
Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given. When the correspond…
IoU Loss for 2D/3D Object Detection
Dingfu Zhou, Jin Fang, Xibin Song +4
In 2D/3D object detection task, Intersection-over-Union (IoU) has been widely employed as an evaluation metric to evaluate the performance of different detectors in the testing sta…
ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving
Xibin Song, Peng Wang, Dingfu Zhou +6
Autonomous driving has attracted remarkable attention from both industry and academia. An important task is to estimate 3D properties(e.g.translation, rotation and shape) of a movi…
Deeply Supervised Depth Map Super-Resolution as Novel View Synthesis
Xibin Song, Yuchao Dai, Xueying Qin
Deep convolutional neural network (DCNN) has been successfully applied to depth map super-resolution and outperforms existing methods by a wide margin. However, there still exist t…
Deep Depth Super-Resolution : Learning Depth Super-Resolution using Deep Convolutional Neural Network
Xibin Song, Yuchao Dai, Xueying Qin
Depth image super-resolution is an extremely challenging task due to the information loss in sub-sampling. Deep convolutional neural network have been widely applied to color image…