11.2.4.8.1 Semi-Supervised, Self-Supervised Semantic Object Detection

Chapter Contents (Back)
Semantic Segmentation. Object Detection. Semantic Object Detection. Semi-Supervided Detection. Self-Supervided Detection.

Li, X.Y.[Xing-Ye], Zhang, L.[Ling], Zhu, Z.G.[Zhi-Gang],
SnapshotNet: Self-supervised feature learning for point cloud data segmentation using minimal labeled data,
CVIU(216), 2022, pp. 103339.
Elsevier DOI 2202
Self-supervision, Point cloud, Semantic segmentation BibRef

Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Wang, Q.[Qin], Chen, Y.H.[Yu-Hua], Van Gool, L.J.[Luc J.],
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation,
IJCV(131), No. 8, August 2023, pp. 2070-2096.
Springer DOI 2307
BibRef

Hoyer, L.[Lukas], Tan, D.J.[David Joseph], Naeem, M.F.[Muhammad Ferjad], Van Gool, L.J.[Luc J.], Tombari, F.[Federico],
SemiVL: Semi-supervised Semantic Segmentation with Vision-Language Guidance,
ECCV24(XXXIX: 257-275).
Springer DOI 2412
BibRef

Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Chen, Y.H.[Yu-Hua], Köring, A.[Adrian], Saha, S.[Suman], Van Gool, L.J.[Luc J.],
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation,
CVPR21(11125-11135)
IEEE DOI 2111
Geometry, Training, Image segmentation, Annotations, Semantics, Estimation, Training data BibRef

Gong, R.[Rui], Wang, Q.[Qin], Danelljan, M.[Martin], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Continuous Pseudo-Label Rectified Domain Adaptive Semantic Segmentation with Implicit Neural Representations,
CVPR23(7225-7235)
IEEE DOI 2309
BibRef

Wang, Q.[Qin], Dai, D.X.[Deng-Xin], Hoyer, L.[Lukas], Van Gool, L.J.[Luc J.], Fink, O.[Olga],
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation,
ICCV21(8495-8505)
IEEE DOI 2203
Bridges, Visualization, Correlation, Navigation, Semantics, Estimation, Transfer/Low-shot/Semi/Unsupervised Learning, Vision for robotics and autonomous vehicles BibRef

Wu, H.[Hua], Huang, Z.[Zhe], Zheng, W.[Wanhao], Bai, X.J.[Xiao-Jing], Sun, L.[Li], Pu, M.Y.[Meng-Yang],
SSGAM-Net: A Hybrid Semi-Supervised and Supervised Network for Robust Semantic Segmentation Based on Drone LiDAR Data,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Zhang, Y.S.[Yun-Sheng], Yao, J.G.[Jian-Guo], Zhang, R.X.[Rui-Xiang], Wang, X.Y.[Xu-Ying], Chen, S.Y.[Si-Yang], Fu, H.[Han],
HAVANA: Hard Negative Sample-Aware Self-Supervised Contrastive Learning for Airborne Laser Scanning Point Cloud Semantic Segmentation,
RS(16), No. 3, 2024, pp. 485.
DOI Link 2402
BibRef

Zheng, X.Y.[Xiao-Yun], Liao, L.W.[Li-Wei], Jiao, J.B.[Jian-Bo], Gao, F.[Feng], Wang, R.G.[Rong-Gang],
Surface-SOS: Self-Supervised Object Segmentation via Neural Surface Representation,
IP(33), 2024, pp. 2018-2031.
IEEE DOI Code:
WWW Link. 2403
Image segmentation, Videos, Object segmentation, Motion segmentation, Geometry, Training, multi-view object segmentation BibRef

Shu, Z.Y.[Zhen-Yu], Wu, T.[Teng], Shen, J.J.[Jia-Jun], Xin, S.Q.[Shi-Qing], Liu, L.G.[Li-Gang],
Semi-Supervised 3D Shape Segmentation via Self Refining,
IP(33), 2024, pp. 2044-2057.
IEEE DOI 2403
Shape, Training, Task analysis, Labeling, Faces, Vectors, 3D shape segmentation, semi-supervised, deep neural network BibRef

Du, A.[Anan], Zhou, T.F.[Tian-Fei], Pang, S.[Shuchao], Wu, Q.[Qiang], Zhang, J.[Jian],
PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation,
MultMed(26), 2024, pp. 8902-8914.
IEEE DOI 2408
Point cloud compression, Semantic segmentation, Task analysis, Self-supervised learning, Convolution, Training, Point cloud, contrastive learning BibRef

Xuan, W.H.[Wei-Hao], Qi, H.[Heli], Xiao, A.[Aoran],
TSG-Seg: Temporal-selective guidance for semi-supervised semantic segmentation of 3D LiDAR point clouds,
PandRS(216), 2024, pp. 217-228.
Elsevier DOI Code:
WWW Link. 2408
3D point cloud, LiDAR, Semantic segmentation, Semi-supervised learning, Spatio-temporal learning, Autonomous driving BibRef

Wu, J.W.[Jun-Wei], Sun, M.J.[Ming-Jie], Xu, H.T.[Hao-Tian], Jiang, C.[Chenru], Ma, W.[Wuwei], Zhang, Q.[Quan],
Class Agnostic and Specific Consistency Learning for Weakly-Supervised Point Cloud Semantic Segmentation,
PR(158), 2025, pp. 111067.
Elsevier DOI Code:
WWW Link. 2411
3d point cloud, Weakly-supervised learning, Consistency learning BibRef

Liu, Y.[Yan], Hu, Q.Y.[Qing-Yong], Guo, Y.L.[Yu-Lan],
BSTS: A Weakly-Supervised Method for Semantic Learning of 3D Point Clouds,
CirSysVideo(34), No. 11, November 2024, pp. 11386-11399.
IEEE DOI 2412
Point cloud compression, Annotations, Semantics, Semantic segmentation, Labeling, Circuits and systems BibRef

Zhang, Y.F.[Yi-Fan], Hou, J.H.[Jun-Hui], Ren, S.[Siyu], Wu, J.J.[Jin-Jian], Yuan, Y.X.[Yi-Xuan], Shi, G.M.[Guang-Ming],
Self-Supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration,
PAMI(47), No. 10, October 2025, pp. 9201-9216.
IEEE DOI 2510
Point cloud compression, Self-supervised learning, Training, Laser radar, Image reconstruction, Semantic segmentation, registration BibRef

Dong, Q.L.[Qiu-Lei], Li, J.A.[Jian-An], Deng, S.[Shuang],
Towards Semi-Supervised Dual-Modal Semantic Segmentation,
MultMed(27), 2025, pp. 8212-8224.
IEEE DOI 2511
BibRef
Earlier: A2, A1, Only:
Density-Guided Semi-Supervised 3D Semantic Segmentation with Dual-Space Hardness Sampling,
CVPR24(3260-3269)
IEEE DOI 2410
Point cloud compression, Feature extraction, Semantic segmentation, Contrastive learning, Training, Semantics, semi-supervised semantic segmentation. Annotations, Semantics, Point Cloud Segmentation, Semi-supervised Learning BibRef

Xu, J.Y.[Jing-Yi], Yang, W.D.[Wei-Dong], Kong, L.[Lingdong], Liu, Y.[Youquan], Zhou, Q.Y.[Qing-Yuan], Zhang, R.[Rui], Li, Z.J.[Zhi-Jun], Chen, W.M.[Wen-Ming], Fei, B.[Ben],
Visual Foundation Models Boost Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation,
ITS(26), No. 11, November 2025, pp. 20287-20301.
IEEE DOI Code:
WWW Link. 2511
Point cloud compression, Visualization, Neural networks, Foundation models, Training, Semantics, Semantic segmentation, visual foundation model BibRef

Wang, J.Y.[Jing-Yi], Xiang, X.J.[Xiao-Jia], Lai, J.[Jun], Liu, Y.[Yu], Li, Q.[Qi], Chen, C.[Chen],
Ground to Altitude: Weakly-Supervised Cross-Platform Domain Generalization for LiDAR Semantic Segmentation,
RS(18), No. 2, 2026, pp. 192.
DOI Link 2602
BibRef


Liu, C.D.[Chuan-Dong], Weng, X.X.[Xing-Xing], Jiang, S.[Shuguo], Li, P.C.[Peng-Cheng], Yu, L.[Lei], Xia, G.S.[Gui-Song],
Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation,
CVPR25(27380-27389)
IEEE DOI Code:
WWW Link. 2508
Backpropagation, Training, Laser radar, Correlation, Semantic segmentation, Semantics, Benchmark testing BibRef

Nisar, B.[Barza], Waslander, S.L.[Steven L.],
PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point Clouds,
CVPR25(6670-6679)
IEEE DOI Code:
WWW Link. 2508
Point cloud compression, Location awareness, Solid modeling, Laser radar, Semantic segmentation, Object detection, 3d semantic segmentation BibRef

Zhang, Z.[Zihui], Dai, W.S.[Wei-Sheng], Wen, H.T.[Hong-Tao], Yang, B.[Bo],
LogoSP: Local-global Grouping of Superpoints for Unsupervised Semantic Segmentation of 3D Point Clouds,
CVPR25(1374-1384)
IEEE DOI Code:
WWW Link. 2508
Training, Point cloud compression, Accuracy, Codes, Semantic segmentation, Frequency-domain analysis, Semantics, Pattern recognition BibRef

Lin, R.D., Weng, P.C.[Peng-Cheng], Wang, Y.Q.[Yin-Qiao], Ding, H.[Han], Han, J.S.[Jin-Song], Wang, F.[Fei],
HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving,
CVPR25(1429-1438)
IEEE DOI 2508
Point cloud compression, Representation learning, Sensitivity, Laser radar, Graphical models, Shape, Semantic segmentation, Roads, point cloud semantic segmentation BibRef

Chen, T.Y.[Tsung-Yu], Yang, L.[Luyu], Chuang, T.Y.[Tzu-Yu], Lai, S.H.[Shang-Hong],
CACE: Sim-to-Real Indoor 3D Semantic Segmentation via Context-Aware Augmentation and Consistency Enforcement,
WACV25(8356-8367)
IEEE DOI 2505
Semantic segmentation, Noise, Training data, Benchmark testing, unsupervised domain adaptation, point cloud, self-supervised learning BibRef

Liu, Y.Y.[Yu-Yuan], Chen, Y.H.[Yuan-Hong], Wang, H.[Hu], Belagiannis, V.[Vasileios], Reid, I.D.[Ian D.], Carneiro, G.[Gustavo],
Ittakestwo: Leveraging Peer Representations for Semi-supervised Lidar Semantic Segmentation,
ECCV24(I: 81-99).
Springer DOI 2412
BibRef

Li, J.A.[Jian-An], Dong, Q.[Qiulei],
Lass3d: Language-assisted Semi-supervised 3d Semantic Segmentation with Progressive Unreliable Data Exploitation,
ECCV24(III: 252-269).
Springer DOI 2412
BibRef

Wang, C.Y.[Cheng-Yao], Jiang, L.[Li], Wu, X.Y.[Xiao-Yang], Tian, Z.T.[Zhuo-Tao], Peng, B.H.[Bo-Hao], Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya],
GroupContrast: Semantic-Aware Self-Supervised Representation Learning for 3D Understanding,
CVPR24(4917-4928)
IEEE DOI 2410
Representation learning, Point cloud compression, Semantic segmentation, Semantics, Transfer learning, Prototypes BibRef

Du, S.L.[Sheng-Lan], Ibrahimli, N.[Nail], Stoter, J.[Jantien], Kooij, J.[Julian], Nan, L.L.[Liang-Liang],
Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds,
3DV22(1-10)
IEEE DOI Code:
WWW Link. 2408
Point cloud compression, Location awareness, Semantic segmentation, Semantics, Self-supervised learning, Encoding BibRef

Unal, O.[Ozan], Dai, D.X.[Deng-Xin], Hoyer, L.[Lukas], Can, Y.B.[Yigit Baran], Van Gool, L.J.[Luc J.],
2D Feature Distillation for Weakly- and Semi-Supervised 3D Semantic Segmentation,
WACV24(7321-7330)
IEEE DOI 2404
Training, Image sensors, Laser radar, Annotations, Semantic segmentation, Semantics, Applications, Autonomous Driving, Remote Sensing BibRef

Liu, J.X.[Jia-Xu], Yu, Z.[Zhengdi], Breckon, T.P.[Toby P.], Shum, H.P.H.[Hubert P. H.],
U3DS3: Unsupervised 3D Semantic Scene Segmentation,
WACV24(3747-3756)
IEEE DOI 2404
Point cloud compression, Training, Representation learning, Solid modeling, Semantics, Algorithms, 3D computer vision, Image recognition and understanding BibRef

Tran, A.T.[Anh-Thuan], Le, H.S.[Hoanh-Su], Lee, S.H.[Suk-Hwan], Kwon, K.R.[Ki-Ryong],
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic Segmentation,
WACV24(3544-3553)
IEEE DOI 2404
Point cloud compression, Annotations, Semantic segmentation, Noise, Transformers, Algorithms, 3D computer vision BibRef

Rahman, M.A.[Md Awsafur], Fattah, S.A.[Shaikh Anowarul],
Semi-Supervised Semantic Depth Estimation using Symbiotic Transformer and NearFarMix Augmentation,
WACV24(249-258)
IEEE DOI 2404
Symbiosis, Semantics, Merging, Information sharing, Estimation, Algorithms BibRef

Carós, M.[Mariona], Just, A.[Ariadna], Seguí, S.[Santi], Vitriŕ, J.[Jordi],
Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR data,
MVA23(1-6)
DOI Link 2403
Point cloud compression, Laser radar, Semantic segmentation, Semantics, Supervised learning, Object segmentation BibRef

Qian, R.[Rui], Ding, S.[Shuangrui], Liu, X.[Xian], Lin, D.[Dahua],
Semantics Meets Temporal Correspondence: Self-supervised Object-centric Learning in Videos,
ICCV23(16629-16641)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, Z.Y.[Zong-Yi], Yuan, B.[Bo], Zhao, S.S.[Shan-Shan], Zhang, Q.N.[Qian-Ni], Gao, X.B.[Xin-Bo],
Hierarchical Point-Based Active Learning for Semi-Supervised Point Cloud Semantic Segmentation,
ICCV23(18052-18062)
IEEE DOI Code:
WWW Link. 2401
BibRef

Liu, L.Z.[Li-Zhao], Zhuang, Z.W.[Zhuang-Wei], Huang, S.X.[Shang-Xin], Xiao, X.L.[Xun-Long], Xiang, T.H.[Tian-Hang], Chen, C.[Cen], Wang, J.D.[Jing-Dong], Tan, M.K.[Ming-Kui],
CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation,
ICCV23(18367-18376)
IEEE DOI 2401
BibRef

Kong, L.D.[Ling-Dong], Ren, J.W.[Jia-Wei], Pan, L.[Liang], Liu, Z.W.[Zi-Wei],
LaserMix for Semi-Supervised LiDAR Semantic Segmentation,
CVPR23(21706-21716)
IEEE DOI 2309
BibRef

Unal, O.[Ozan], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Scribble-Supervised LiDAR Semantic Segmentation,
CVPR22(2687-2697)
IEEE DOI 2210
Point cloud compression, Training, Laser radar, Codes, Annotations, Computational modeling, Segmentation, Self- semi- meta- unsupervised learning BibRef

Bansal, N.[Nitin], Ji, P.[Pan], Yuan, J.S.[Jun-Song], Xu, Y.[Yi],
Semantics-Depth-Symbiosis: Deeply Coupled Semi-Supervised Learning of Semantics and Depth,
WACV23(5817-5828)
IEEE DOI 2302
Training, Symbiosis, Semantic segmentation, Semantics, Estimation, Performance gain BibRef

Li, L.X.[Lan-Xiao], Heizmann, M.[Michael],
A Closer Look at Invariances in Self-supervised Pre-training for 3D Vision,
ECCV22(XXX:656-673).
Springer DOI 2211
BibRef

Jiang, L.[Li], Shi, S.S.[Shao-Shuai], Tian, Z.T.[Zhuo-Tao], Lai, X.[Xin], Liu, S.[Shu], Fu, C.W.[Chi-Wing], Jia, J.Y.[Jia-Ya],
Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation,
ICCV21(6403-6412)
IEEE DOI 2203
Point cloud compression, Training, Representation learning, Solid modeling, Costs, Semantics, Stereo, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Jiang, L.[Li], Zhao, H.S.[Heng-Shuang], Liu, S.[Shu], Shen, X.Y.[Xiao-Yong], Fu, C.W.[Chi-Wing], Jia, J.Y.[Jia-Ya],
Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation,
ICCV19(10432-10440)
IEEE DOI 2004
graph theory, image colour analysis, image segmentation, message passing, object detection, Labeling BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Semantic Object Detection RGB-D Data, RGBD Data .


Last update:Apr 6, 2026 at 11:28:57