40 citations · 126 across the 14 of their papers we have counts for
14 papers
SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation
Xuechao Chen, Shuangjie Xu, Xiaoyi Zou +3
LiDAR-based semantic perception tasks are critical yet challenging for autonomous driving. Due to the motion of objects and static/dynamic occlusion, temporal information plays an…
From One to Many: Dynamic Cross Attention Networks for LiDAR and Camera Fusion
Rui Wan, Shuangjie Xu, Wei Wu +2
LiDAR and cameras are two complementary sensors for 3D perception in autonomous driving. LiDAR point clouds have accurate spatial and geometry information, while RGB images provide…
Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation
Shuangjie Xu, Rui Wan, Maosheng Ye +2
Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially fo…
DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
Maosheng Ye, Rui Wan, Shuangjie Xu +2
Recently, many approaches have been proposed through single or multiple representations to improve the performance of point cloud semantic segmentation. However, these works do not…
DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation
Maosheng Ye, Shuangjie Xu, Tongyi Cao +1
We present a novel and flexible architecture for point cloud segmentation with dual-representation iterative learning. In point cloud processing, different representations have the…
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network
Zhikang Zou, Xiaoye Qu, Pan Zhou +4
Recent deep networks have convincingly demonstrated high capability in crowd counting, which is a critical task attracting widespread attention due to its various industrial applic…
Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation
Daizong Liu, Shuangjie Xu, Xiao-Yang Liu +3
This paper addresses the task of segmenting class-agnostic objects in semi-supervised setting. Although previous detection based methods achieve relatively good performance, these…
HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection
Maosheng Ye, Shuangjie Xu, Tongyi Cao
We present Hybrid Voxel Network (HVNet), a novel one-stage unified network for point cloud based 3D object detection for autonomous driving. Recent studies show that 2D voxelizatio…
Crowd Counting via Hierarchical Scale Recalibration Network
Zhikang Zou, Yifan Liu, Shuangjie Xu +3
The task of crowd counting is extremely challenging due to complicated difficulties, especially the huge variation in vision scale. Previous works tend to adopt a naive concatenati…
Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels
Daizong Liu, Shuangjie Xu, Pan Zhou +3
Disease diagnosis on chest X-ray images is a challenging multi-label classification task. Previous works generally classify the diseases independently on the input image without co…
Tell-the-difference: Fine-grained Visual Descriptor via a Discriminating Referee
Shuangjie Xu, Feng Xu, Yu Cheng +1
In this paper, we investigate a novel problem of telling the difference between image pairs in natural language. Compared to previous approaches for single image captioning, it is…
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
Shuangjie Xu, Daizong Liu, Linchao Bao +2
We address the problem of semi-supervised video object segmentation (VOS), where the masks of objects of interests are given in the first frame of an input video. To deal with chal…
Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification
Xinxing Su, Yingtian Zou, Yu Cheng +3
We tackle the problem of person re-identification in video setting in this paper, which has been viewed as a crucial task in many applications. Meanwhile, it is very challenging si…
Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Shuangjie Xu, Yu Cheng, Kang Gu +3
Person Re-Identification (person re-id) is a crucial task as its applications in visual surveillance and human-computer interaction. In this work, we present a novel joint Spatial…