UM

Browse/Search Results:  1-10 of 16 Help

Selected(0)Clear Items/Page:    Sort:
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection From Point Clouds Journal article
Yin,Junbo, Shen,Jianbing, Gao,Xin, Crandall,David J., Yang,Ruigang. Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection From Point Clouds[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(8), 9822-9835.
Authors:  Yin,Junbo;  Shen,Jianbing;  Gao,Xin;  Crandall,David J.;  Yang,Ruigang
Favorite | TC[WOS]:48 TC[Scopus]:41  IF:20.8/22.2 | Submit date:2023/08/03
3d Video Object Detection  Autonomous Driving  Graph Neural Network  Point Cloud  Transformer Attention  
Keyframe image processing of semantic 3D point clouds based on deep learning Journal article
Wang,Junxian, Lv,Wei, Wang,Zhouya, Zhang,Xiaolong, Jiang,Meixuan, Gao,Junhan, Chen,Shangwen. Keyframe image processing of semantic 3D point clouds based on deep learning[J]. Frontiers in Neurorobotics, 2023, 16, 988024.
Authors:  Wang,Junxian;  Lv,Wei;  Wang,Zhouya;  Zhang,Xiaolong;  Jiang,Meixuan; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:2.6/3.1 | Submit date:2023/08/03
3d Point Cloud  Deep Learning  Image Processing  Keyframe  U-net  
ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection Conference paper
Yin, Junbo, Zhou, Dingfu, Zhang, Liangjun, Fang, Jin, Xu, Cheng Zhong, Shen, Jianbing, Wang, Wenguan. ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2022, 17-33.
Authors:  Yin, Junbo;  Zhou, Dingfu;  Zhang, Liangjun;  Fang, Jin;  Xu, Cheng Zhong; et al.
Favorite | TC[WOS]:33 TC[Scopus]:48 | Submit date:2023/01/30
3d Object Detection  Unsupervised Point Cloud Pre-training  
Semi-supervised 3D Object Detection with Proficient Teachers Conference paper
Yin, Junbo, Fang, Jin, Zhou, Dingfu, Zhang, Liangjun, Xu, Cheng Zhong, Shen, Jianbing, Wang, Wenguan. Semi-supervised 3D Object Detection with Proficient Teachers[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2022, 727-743.
Authors:  Yin, Junbo;  Fang, Jin;  Zhou, Dingfu;  Zhang, Liangjun;  Xu, Cheng Zhong; et al.
Favorite | TC[WOS]:35 TC[Scopus]:47 | Submit date:2023/01/30
3d Object Detection  Point Cloud  Semi-supervised Learning  
ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection Conference paper
Junbo, Yin, Junbo, Yin, Liangjun, Zhang, Jin, Fang, Dingfu, Zhou, Cheng-Zhong, Xu, Jianbing, Shen, Wenguan, Wang. ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection[C], 2022.
Authors:  Junbo, Yin;  Junbo, Yin;  Liangjun, Zhang;  Jin, Fang;  Dingfu, Zhou; et al.
Favorite | TC[WOS]:33 TC[Scopus]:48 | Submit date:2023/08/08
3d Object Detection  Unsupervised Point Cloud Pre-training  
Semi-supervised 3D Object Detection with Proficient Teachers Conference paper
Junbo, Yin, Jin, Fang, Dingfu, Zhou, Liangjun, Zhang, Cheng-Zhong, Xu, Jianbing, Shen, Wenguan, Wang. Semi-supervised 3D Object Detection with Proficient Teachers[C], 2022.
Authors:  Junbo, Yin;  Jin, Fang;  Dingfu, Zhou;  Liangjun, Zhang;  Cheng-Zhong, Xu; et al.
Favorite | TC[WOS]:35 TC[Scopus]:47 | Submit date:2023/08/08
3d Object Detection  Semi-supervised Learning  Point Cloud  
A 3D Object Recognition Method From LiDAR Point Cloud Based on USAE-BLS Journal article
Yifei Tian, Wei Song, Long Chen, Simon Fong, Yunsick Sung, Jeonghoon Kwak. A 3D Object Recognition Method From LiDAR Point Cloud Based on USAE-BLS[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(9), 15267-15277.
Authors:  Yifei Tian;  Wei Song;  Long Chen;  Simon Fong;  Yunsick Sung; et al.
Favorite | TC[WOS]:6 TC[Scopus]:5  IF:7.9/8.3 | Submit date:2022/05/17
3d Object Recognition  Broad Learning System  Feature Extraction  Unified Space Autoencoder.  Lidar Point Cloud  
InfoPCT: Mutual Information Maximization based Point Cloud Transformer Conference paper
Wang, Di, Yang, Zhixin. InfoPCT: Mutual Information Maximization based Point Cloud Transformer[C], 2022, 17-21.
Authors:  Wang, Di;  Yang, Zhixin
Favorite | TC[Scopus]:2 | Submit date:2022/08/05
3d Computer Vision  Deep Learning  Mutual Information Maximization  Point Cloud Transformer  
Dgcb-net: Dynamic graph convolutional broad network for 3d object recognition in point cloud Journal article
Tian,Yifei, Chen,Long, Song,Wei, Sung,Yunsick, Woo,Sangchul. Dgcb-net: Dynamic graph convolutional broad network for 3d object recognition in point cloud[J]. Remote Sensing, 2021, 13(1), 1-20.
Authors:  Tian,Yifei;  Chen,Long;  Song,Wei;  Sung,Yunsick;  Woo,Sangchul
Favorite | TC[WOS]:9 TC[Scopus]:10  IF:4.2/4.9 | Submit date:2021/03/09
3d Object Recognition  Broad Learning System  Dynamic Graph Convolution  Point Cloud Analysis  
VB-Net: Voxel-based broad learning network for 3D object classification Journal article
Liu, Zishu, Song, Wei, Tian, Yifei, Ji, Sumi, Sung, Yunsick, Wen, Long, Zhang, Tao, Song, Liangliang, Gozho, Amanda. VB-Net: Voxel-based broad learning network for 3D object classification[J]. Applied Sciences (Switzerland), 2020, 10(19), 6735.
Authors:  Liu, Zishu;  Song, Wei;  Tian, Yifei;  Ji, Sumi;  Sung, Yunsick; et al.
Favorite | TC[WOS]:17 TC[Scopus]:22  IF:2.5/2.7 | Submit date:2021/12/06
3d Object Classification  Broad Learning System  Point Cloud