Xinge Zhu
Cited by
Cited by
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection
T Wang, X Zhu, J Pang, D Lin
International Conference on Computer Vision Workshops (ICCVW), 2021
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
X Zhu*, H Zhou*, T Wang, F Hong, Y Ma, W Li, H Li, D Lin
CVPR 2021 (Oral), 2021
TrafficPredict: Trajectory prediction for heterogeneous traffic-agents
Y Ma*, X Zhu*, S Zhang, R Yang, W Wang, D Manocha
AAAI 2019, 2019
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
X Bai, Z Hu, X Zhu, Q Huang, Y Chen, H Fu, CL Tai
CVPR 2022, 2022
Adapting object detectors via selective cross-domain alignment
X Zhu, J Pang, C Yang, J Shi, D Lin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints
Y Xu, X Zhu, J Shi, G Zhang, H Bao, H Li
ICCV 2019, 2019
Probabilistic and geometric depth: Detecting objects in perspective
T Wang, X Zhu, J Pang, D Lin
Conference on Robot Learning (CoRL), 2021
Cylinder3d: An effective 3d framework for driving-scene lidar semantic segmentation
H Zhou, X Zhu, X Song, Y Ma, Z Wang, H Li, D Lin
arXiv preprint arXiv:2008.01550, 2020
Pose Guided Human Video Generation
C Yang, Z Wang, X Zhu, C Huang, J Shi, D Lin
European Conference on Computer Vision (ECCV) 2018, 2018
Point-to-voxel knowledge distillation for lidar semantic segmentation
Y Hou, X Zhu, Y Ma, CC Loy, Y Li
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation
X Zhu, H Zhou, C Yang, J Shi, D Lin
European Conference on Computer Vision (ECCV) 2018, 2018
SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds
X Zhu, Y Ma, T Wang, Y Xu, J Shi, D Lin
European Conference on Computer Vision (ECCV) 2020, 2020
Dependency Exploitation: A Unified CNN-RNN Approach for Visual Emotion Recognition
X Zhu, L Li, W Zhang, T Rao, M Xu, Q Huang, D Xu
Proceedings of the Internal Joint Conference on Artificial Intelligence …, 2017
LiDAR-based Panoptic Segmentation via Dynamic Shifting Network
F Hong, H Zhou, X Zhu, H Li, Z Liu
CVPR 2021, 2021
Cylindrical and asymmetrical 3d convolution networks for lidar-based perception
X Zhu, H Zhou, T Wang, F Hong, W Li, Y Ma, H Li, R Yang, D Lin
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6807 …, 2021
Vision-centric bev perception: A survey
Y Ma, T Wang, X Bai, H Yang, Y Hou, Y Wang, Y Qiao, R Yang, ...
arXiv preprint arXiv:2208.02797, 2022
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
R Chen, Y Liu, L Kong, X Zhu, Y Ma, Y Li, Y Hou, Y Qiao, W Wang
CVPR 2023, 2023
Rethinking range view representation for lidar segmentation
L Kong, Y Liu, R Chen, Y Ma, X Zhu, Y Li, Y Hou, Y Qiao, Z Liu
ICCV 2023, 2023
Not all areas are equal: Transfer learning for semantic segmentation via hierarchical region selection
R Sun*, X Zhu*, C Wu, C Huang, J Shi, L Ma
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
AdaStereo: a simple and efficient approach for adaptive stereo matching
X Song, G Yang, X Zhu, H Zhou, Z Wang, J Shi
CVPR 2021, 2020
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