11.2.4.3 Semi-Supervised Object Detection, 3D Object Detection

Chapter Contents (Back)
Object Detection. Semi-Supervised.
See also Semi-Supervised Object Detection.
See also Depth Object Segmentation, Point Cloud Segmentation.
See also Semantic Object Detection, 3D, Depth.

An, P.[Pei], Liang, J.X.[Jun-Xiong], Hong, X.[Xing], Quan, S.[Siwen], Ma, T.[Tao], Chen, Y.F.[Yan-Fei], Wang, L.[Liheng], Ma, J.[Jie],
Leveraging Self-Paced Semi-Supervised Learning with Prior Knowledge for 3D Object Detection on a LiDAR-Camera System,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

An, P.[Pei], Liang, J.X.[Jun-Xiong], Ma, T.[Tao], Chen, Y.F.[Yan-Fei], Wang, L.[Liheng], Ma, J.[Jie],
ProUDA: Progressive unsupervised data augmentation for semi-Supervised 3D object detection on point cloud,
PRL(170), 2023, pp. 64-69.
Elsevier DOI 2306
3D Object detection, Semi-supervised learning, 3D Point cloud BibRef

Liu, J.X.[Jin-Xian], Chen, Y.[Ye], Ni, B.B.[Bing-Bing], Yu, Z.B.[Zhen-Bo],
Joint Global and Dynamic Pseudo Labeling for Semi-Supervised Point Cloud Sequence Segmentation,
CirSysVideo(33), No. 10, October 2023, pp. 5679-5691.
IEEE DOI 2310
BibRef


Gao, H.A.[Huan-Ang], Tian, B.[Beiwen], Li, P.F.[Peng-Fei], Zhao, H.[Hao], Zhou, G.[Guyue],
DQS3D: Densely-matched Quantization-aware Semi-supervised 3D Detection,
ICCV23(21848-21858)
IEEE DOI 2401
BibRef

Hwang, S.[Sunwook], Kim, Y.[Youngseok], Kim, S.W.[Seong-Won], Bahk, S.[Saewoong], Kim, H.S.[Hyung-Sin],
UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes,
ICCV23(23294-23304)
IEEE DOI 2401
BibRef

Nozarian, F.[Farzad], Agarwal, S.[Shashank], Rezaeianaran, F.[Farzaneh], Shahzad, D.[Danish], Poibrenski, A.[Atanas], Müller, C.[Christian], Slusallek, P.[Philipp],
Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection,
L3D-IVU23(4981-4990)
IEEE DOI 2309
BibRef

Liu, C.D.[Chuan-Dong], Gao, C.Q.[Chen-Qiang], Liu, F.[Fangcen], Li, P.C.[Peng-Cheng], Meng, D.Y.[De-Yu], Gao, X.B.[Xin-Bo],
Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection,
CVPR23(23819-23828)
IEEE DOI 2309
BibRef

Chen, Z.[Zehui], Li, Z.Y.[Zhen-Yu], Wang, S.[Shuo], Fu, D.[Dengpan], Zhao, F.[Feng],
Learning with Noisy Data for Semi-Supervised 3D Object Detection,
ICCV23(6906-6916)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhang, D.[Dingyuan], Liang, D.[Dingkang], Zou, Z.[Zhikang], Li, J.Y.[Jing-Yu], Ye, X.Q.[Xiao-Qing], Liu, Z.[Zhe], Tan, X.[Xiao], Bai, X.[Xiang],
A Simple Vision Transformer for Weakly Semi-supervised 3D Object Detection,
ICCV23(8339-8349)
IEEE DOI 2401
BibRef

Wang, C.X.[Chu-Xin], Yang, W.F.[Wen-Fei], Zhang, T.Z.[Tian-Zhu],
Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection,
ICCV23(3791-3801)
IEEE DOI 2401
BibRef

Wu, W.H.[Wen-Hao], Wong, H.S.[Hau-San], Wu, S.[Si],
Semi-Supervised Stereo-Based 3D Object Detection via Cross-View Consensus,
CVPR23(17471-17481)
IEEE DOI 2309
BibRef

Park, J.H.[Jin-Hyung], Xu, C.F.[Chen-Feng], Zhou, Y.Y.[Yi-Yang], Tomizuka, M.[Masayoshi], Zhan, W.[Wei],
DetMatch: Two Teachers are Better than One for Joint 2D and 3D Semi-Supervised Object Detection,
ECCV22(X:370-389).
Springer DOI 2211
BibRef

Liu, L.[Linhu], Tian, J.[Jiang], Cheng, X.Q.[Xiang-Qian], Shi, Z.C.[Zhong-Chao], Fan, J.P.[Jian-Ping], Rui, Y.[Yong],
Semi-Supervised 3D Medical Image Segmentation Via Boundary-Aware Consistent Hidden Representation Learning,
ICIP22(836-840)
IEEE DOI 2211
Representation learning, Image segmentation, Perturbation methods, Benchmark testing, Robustness, Decoding, Semi-supervised segmentation BibRef

Yin, J.[Junbo], Fang, J.[Jin], Zhou, D.[Dingfu], Zhang, L.J.[Liang-Jun], Xu, C.Z.[Cheng-Zhong], Shen, J.B.[Jian-Bing], Wang, W.G.[Wen-Guan],
Semi-supervised 3D Object Detection with Proficient Teachers,
ECCV22(XXXVIII:727-743).
Springer DOI 2211
BibRef

Xu, H.Y.[Hong-Yi], Liu, F.Q.[Feng-Qi], Zhou, Q.Y.[Qian-Yu], Hao, J.K.[Jin-Kun], Cao, Z.J.[Zhi-Jie], Feng, Z.Y.[Zheng-Yang], Ma, L.Z.[Li-Zhuang],
Semi-Supervised 3d Object Detection Via Adaptive Pseudo-Labeling,
ICIP21(3183-3187)
IEEE DOI 2201
Annotations, Filtering, Image processing, Object detection, Benchmark testing, 3D object detection, point clouds, semi-supervised learning BibRef

Wang, H.[He], Cong, Y.Z.[Ye-Zhen], Litany, O.[Or], Gao, Y.[Yue], Guibas, L.J.[Leonidas J.],
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection,
CVPR21(14610-14619)
IEEE DOI 2111
Location awareness, Training, Filtering, Estimation, Object detection, Detectors BibRef

Tang, Y.S., Lee, G.H.,
Transferable Semi-Supervised 3D Object Detection From RGB-D Data,
ICCV19(1931-1940)
IEEE DOI 2004
image classification, image colour analysis, object detection, stereo image processing, supervised learning, Estimation BibRef

Zhao, N., Chua, T., Lee, G.H.,
SESS: Self-Ensembling Semi-Supervised 3D Object Detection,
CVPR20(11076-11084)
IEEE DOI 2008
Object detection, Perturbation methods, Proposals, Task analysis, Training BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Range and Color, RGB-D Segmentation and Analysis .


Last update:Apr 27, 2024 at 11:46:35