Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

Deep Residual Learning for Image Recognition

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ImageNet classification with deep convolutional neural networks

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Adam: A Method for Stochastic Optimization

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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

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Xception: Deep Learning with Depthwise Separable Convolutions

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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

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Simultaneously Short- and Long-Term Temporal Modeling for Semi-Supervised Video Semantic Segmentation

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EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANsPreprint

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Finding Stars From Fireworks: Improving Non-Cooperative Iris Tracking

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SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations

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Semisupervised Semantic Segmentation With Certainty-Aware Consistency Training for Remote Sensing Imagery

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MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation

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Semantic Segmentation for Autonomous Driving

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Revisiting Consistency for Semi-Supervised Semantic Segmentation

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Segmenting Known Objects and Unseen Unknowns without Prior Knowledge

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LesionMix data enhancement and entropy minimization for semi-supervised lesion segmentation of lung cancer

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CARD: Semi-supervised Semantic Segmentation via Class-agnostic Relation based Denoising

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Adaptive Context Transformer for Semisupervised Remote Sensing Image Segmentation

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Survey on fast dense video segmentation techniques

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Leveraging Geometric Structure for Label-Efficient Semi-Supervised Scene Segmentation

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Twin Pseudo-training for semi-supervised semantic segmentation

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BG-Net: boundary-guidance network for object consistency maintaining in semantic segmentation

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MDT: semi-supervised medical image segmentation with mixup-decoupling training

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Bootstrapped Self-Supervised Training with Monocular Video for Semantic Segmentation and Depth Estimation

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A variable adversarial attack method based on filtering

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Exigent Examiner and Mean Teacher: An Advanced 3D CNN-Based Semi-Supervised Brain Tumor Segmentation Framework

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Advancements in urban scene segmentation using deep learning and generative adversarial networks for accurate satellite image analysis

Sangeetha, S., Sivakumar, M., Mathivanan, S. K., Rajadurai, H., Karthikeyan, P., & Shah, M. A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0307187 · Cited by 5

A baseline for semi-supervised learning of efficient semantic segmentation models

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Time-Space Transformers for Video Panoptic Segmentation

Petrovai, A., & Nedevschi, S. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00270 · Cited by 5

UGAN: Semi-supervised Medical Image Segmentation Using Generative Adversarial Network

Yuan, Z., Wang, B., & Hong, Q. (2022) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei56279.2022.9980009 · Cited by 5

S³MPL:Semi-supervised Semantic Segmentation with Mixed Pseudo Label

Zhou, Y., Jiao, R., Wang, D., & Zhou, H. (2022) · Youth Academic Annual Conference of Chinese Association of Automation (YAC) · doi:10.1109/yac57282.2022.10023879 · Cited by 5

Multi-Task Self-Training for Learning General RepresentationsPreprint

Ghiasi, G., Zoph, B., Cubuk, E. D., Le, Q. V., & Lin, T.-Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.11353 · Cited by 5

Semi-supervised Multi-organ Segmentation with Cross Supervision Using Siamese Network

Jia, D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-23911-3_26 · Cited by 4

Semantic Segmentation in Thermal Videos: A New Benchmark and Multi-Granularity Contrastive Learning-Based Framework

Zheng, Y. H., Zhou, F., Liang, S., Song, W., & Bai, X. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3300038 · Cited by 4

39. Semi-supervised semantic segmentation for grape bunch identification in natural images

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Exploratory Investigation on a Naive Pseudo-labelling Technique for Liquid Droplet Images Detection using Semi-supervised Learning

Lau, S. L., Lew, J., Ho, C. C., & Su, S. M. (2021) · IEEE International Conference on Computing (ICOCO) · doi:10.1109/icoco53166.2021.9673553 · Cited by 4

Instance Segmentation with Cross-Modal Consistency

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Weakly-supervised Metric Learning with Cross-Module Communications for the Classification of Anterior Chamber Angle Images

Huang, J., Ning, Y., Nie, D., Guan, L., & Jia, X. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00083 · Cited by 3

Is It Necessary to Transfer Temporal Knowledge for Domain Adaptive Video Semantic Segmentation?

Wu, X., Wu, Z., Wan, J., Ju, L., & Wang, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19812-0_21 · Cited by 3

An Iterative Semi-supervised Approach with Pixel-wise Contrastive Loss for Road Extraction in Aerial Images

Zhang, H., Li, P., Liu, X., Yang, X. “., & An, L. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3606374 · Cited by 5

A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation

Vödisch, N., Petek, K., Käppeler, M., Valada, A., & Burgard, W. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3505779 · Cited by 5

Dual-Level Masked Semantic Inference for Semi-Supervised Semantic Segmentation

Ma, Q., Zhang, Z., Qiao, P., Wang, Y., Ji, R., Liu, C., & Chen, J. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3535294 · Cited by 5

Semi-supervised Domain Adaptation for Semantic SegmentationPreprint

Chen, Y., Ouyang, X., Zhu, K., & Gady Agam, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.10639 · Cited by 6

Improved Road Extraction Models through Semi-Supervised Learning with ACCT

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Attention decoupled contrastive learning for semi-supervised segmentation method based on data augmentation

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Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation on Edge Devices

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Multimodal Semantic Forecasting Based on Conditional Generation of Future Features

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AinnoSeg: Panoramic Segmentation with High PerfomancePreprint

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Semi-Supervised Surgical Video Semantic Segmentation with Cross Supervision of Inter-Frame

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Temporality-guided Masked Image Consistency for Domain Adaptive Video Segmentation

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Cloud Detection on PRISMA Second Generation Using a Secondary RGB Forward-Looking Camera

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Knowledge Distillation for Semantic Segmentation: A Label Space Unification Approach

Backhaus, A., Luettel, T., & Maehlisch, M. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246619 · Cited by 1

Video Shadow Detection with Intra-and Inter-video Cooperation

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A Semi-supervised Teacher-Student Model Based on MMAN for Brain Tissue Segmentation

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Object-Centric Representation Learning for Video Scene Understanding

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Semi-supervised Lip-Tongue segmentation with Boundary Region Contrast Sampling

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Hungarian Traffic Sign Detection and Classification using Semi-Supervised Learning

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Domain-based semi-supervised learning: exploiting label invariance in unlabeled data from distributed cameras

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Striving for Less: Minimally-Supervised Pseudo-Label Generation for Monocular Road Segmentation

Robinet, F., Akl, Y., Ullah, K., Nozarian, F., Müller, C. A., & Frank, R. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3193463

Sequential semi-supervised active learning model in extremely low training set (SSSAL)

Khalili, E., Malekhosseini, R., Yaghoubyan, S. H., Bagherifard, K., & Parvïn, H. (2022) · The Journal of Supercomputing · doi:10.1007/s11227-022-04847-z

Quality-aware face alignment using high-resolution spatial dependencies

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Deep Learning Model for Behavioral Image Data Annotation

Wang, B., He, W. P., Jiang, C., Ru, X., & Du, C. (2024) · International Conference on Mobile Computing and Sustainable Informatics (ICMCSI) · doi:10.1109/icmcsi61536.2024.00064

An fMRI-based visual decoding framework combined with two-stage learning and asynchronous iterative update strategy

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Pseudosupervision With Contrast–Separation Awareness in Endoscopy Image Segmentation

Wu, H., Li, J., & Qin, J. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3481581

Object Segmentation Based on Pseudo Supervision Relearning Under Extremely Weak Annotations for Remote Sensing Images

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Unlocking CLIP for Zero-Shot Dense Segmentation

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Fairness without Labels: Pseudo-Balancing for Bias Mitigation in Face Gender Classification

Dong, H., Rodriguez, A. M., Guinaudeau, C., & Satoh, S. (2025) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw69036.2025.00796

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-Supervised Panoptic Segmentation

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Enhancing Human-Robot Interaction with Computer Vision

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ACRS: Active contour-regularized semi-supervised framework for carotid plaque segmentation in ultrasound images with limited labels

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Can Unsupervised Segmentation Reduce Annotation Costs for Video Semantic Segmentation?

Some, S., & Namboodiri, V. P. (2025) · Indian Conference on Computer Vision, Graphics and Image Processing · doi:10.1145/3774521.3774590

Semi-Supervised Learning in Video Sequences for Urban Scene SegmentationPreprint

Chen, L.-C., Lopes, R. G., Cheng, B., Collins, M. D., Cubuk, E. D., Zoph, B., Adam, H., & Shlens, J. (2020) · arXiv (Cornell University) · Cited by 14

Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.Preprint

Chen, L.-C., Lopes, R. G., Cheng, B., Collins, M. D., Cubuk, E. D., Zoph, B., Adam, H., & Shlens, J. (2020) · arXiv (Cornell University) · Cited by 12

Urban scene semantic segmentation with insufficient labeled data

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Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024Preprint

Wu, B., Zhang, D., Gao, S. J., Zheng, C., Liu, S., & Wang, N. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2406.00587

Semantics Through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation

Marcu, A., Licăreţ, V., Costea, D., & Leordeanu, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69525-5_32 · Cited by 27