Saved in:
| Main Authors: | Hong, Yuting, Wu, Yongkang, Xiao, Hui, Hao, Huazheng, Qiu, Xiaojie, Yao, Baochen, Peng, Chengbin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.12680 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Multi-View Consistency Framework with Semi-Supervised Domain Adaptation
by: Hong, Yuting, et al.
Published: (2026)
by: Hong, Yuting, et al.
Published: (2026)
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation
by: Xiao, Hui, et al.
Published: (2024)
by: Xiao, Hui, et al.
Published: (2024)
Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
by: Sun, Xueqing, et al.
Published: (2025)
by: Sun, Xueqing, et al.
Published: (2025)
Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling
by: Qiu, Yunfei, et al.
Published: (2026)
by: Qiu, Yunfei, et al.
Published: (2026)
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition
by: Dave, Ishan Rajendrakumar, et al.
Published: (2024)
by: Dave, Ishan Rajendrakumar, et al.
Published: (2024)
Semi-Supervised Semantic Segmentation via Derivative Label Propagation
by: Fu, Yuanbin, et al.
Published: (2025)
by: Fu, Yuanbin, et al.
Published: (2025)
PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning
by: Tian, Bowen, et al.
Published: (2024)
by: Tian, Bowen, et al.
Published: (2024)
SSFlowNet: Semi-supervised Scene Flow Estimation On Point Clouds With Pseudo Label
by: Chen, Jingze, et al.
Published: (2023)
by: Chen, Jingze, et al.
Published: (2023)
Semi-rPPG: Semi-Supervised Remote Physiological Measurement with Curriculum Pseudo-Labeling
by: Wu, Bingjie, et al.
Published: (2025)
by: Wu, Bingjie, et al.
Published: (2025)
EvoPool: Evolutionary Programmatic Annotation for Label-Efficient Specialized Supervision
by: Xu, Tianyi, et al.
Published: (2026)
by: Xu, Tianyi, et al.
Published: (2026)
DiCaP: Distribution-Calibrated Pseudo-labeling for Semi-Supervised Multi-Label Learning
by: Han, Bo, et al.
Published: (2025)
by: Han, Bo, et al.
Published: (2025)
Dual Diversity and Pseudo‐Label Correction Learning for Semi‐Supervised Medical Image Segmentation
by: Guangxing Du, et al.
Published: (2025)
by: Guangxing Du, et al.
Published: (2025)
Synergy-Guided Regional Supervision of Pseudo Labels for Semi-Supervised Medical Image Segmentation
by: Wang, Tao, et al.
Published: (2024)
by: Wang, Tao, et al.
Published: (2024)
Semi Supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-Labelling
by: Dantas, Cassio F., et al.
Published: (2024)
by: Dantas, Cassio F., et al.
Published: (2024)
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly Detection
by: Chen, Junzhuo, et al.
Published: (2024)
by: Chen, Junzhuo, et al.
Published: (2024)
Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey
by: Ran, Lingyan, et al.
Published: (2024)
by: Ran, Lingyan, et al.
Published: (2024)
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation
by: Lin, Jianghang, et al.
Published: (2025)
by: Lin, Jianghang, et al.
Published: (2025)
Cross Pseudo-Labeling for Semi-Supervised Audio-Visual Source Localization
by: Guo, Yuxin, et al.
Published: (2024)
by: Guo, Yuxin, et al.
Published: (2024)
A Confidence-Variance Theory for Pseudo-Label Selection in Semi-Supervised Learning
by: Liu, Jinshi, et al.
Published: (2026)
by: Liu, Jinshi, et al.
Published: (2026)
HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling
by: Li, Mei, et al.
Published: (2026)
by: Li, Mei, et al.
Published: (2026)
AdaSemiCD: An Adaptive Semi-Supervised Change Detection Method Based on Pseudo-Label Evaluation
by: Lingyan, Ran, et al.
Published: (2024)
by: Lingyan, Ran, et al.
Published: (2024)
ProPL: Universal Semi-Supervised Ultrasound Image Segmentation via Prompt-Guided Pseudo-Labeling
by: Chen, Yaxiong, et al.
Published: (2025)
by: Chen, Yaxiong, et al.
Published: (2025)
Enhancing Dual Network Based Semi-Supervised Medical Image Segmentation with Uncertainty-Guided Pseudo-Labeling
by: Lu, Yunyao, et al.
Published: (2025)
by: Lu, Yunyao, et al.
Published: (2025)
Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentation
by: Chen, Yuanbin, et al.
Published: (2023)
by: Chen, Yuanbin, et al.
Published: (2023)
The Efficiency of Pre-training with Objective Masking in Pseudo Labeling for Semi-Supervised Text Classification
by: Hatefi, Arezoo, et al.
Published: (2025)
by: Hatefi, Arezoo, et al.
Published: (2025)
Pseudo-Labeling Based Practical Semi-Supervised Meta-Training for Few-Shot Learning
by: Dong, Xingping, et al.
Published: (2022)
by: Dong, Xingping, et al.
Published: (2022)
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation
by: Yang, Danni, et al.
Published: (2024)
by: Yang, Danni, et al.
Published: (2024)
Learning Adaptive Pseudo-Label Selection for Semi-Supervised 3D Object Detection
by: Kong, Taehun, et al.
Published: (2025)
by: Kong, Taehun, et al.
Published: (2025)
Semi-Supervised Cognitive State Classification from Speech with Multi-View Pseudo-Labeling
by: Li, Yuanchao, et al.
Published: (2024)
by: Li, Yuanchao, et al.
Published: (2024)
Semi-Supervised Crowd Counting with Contextual Modeling: Facilitating Holistic Understanding of Crowd Scenes
by: Qian, Yifei, et al.
Published: (2023)
by: Qian, Yifei, et al.
Published: (2023)
A Semi-Supervised Framework for Breast Ultrasound Segmentation with Training-Free Pseudo-Label Generation and Label Refinement
by: Li, Ruili, et al.
Published: (2026)
by: Li, Ruili, et al.
Published: (2026)
Striving for Simplicity: Simple Yet Effective Prior-Aware Pseudo-Labeling for Semi-Supervised Ultrasound Image Segmentation
by: Chen, Yaxiong, et al.
Published: (2025)
by: Chen, Yaxiong, et al.
Published: (2025)
Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation
by: Saito, Nagito, et al.
Published: (2025)
by: Saito, Nagito, et al.
Published: (2025)
SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation
by: Keuth, Ron, et al.
Published: (2024)
by: Keuth, Ron, et al.
Published: (2024)
Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation
by: Ghamsarian, Negin, et al.
Published: (2025)
by: Ghamsarian, Negin, et al.
Published: (2025)
Multi-View Semi-Supervised Label Distribution Learning with Local Structure Complementarity
by: Xiao, Yanshan, et al.
Published: (2025)
by: Xiao, Yanshan, et al.
Published: (2025)
AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning
by: Wu, Zhiyu, et al.
Published: (2024)
by: Wu, Zhiyu, et al.
Published: (2024)
Learning to Predict Gradients for Semi-Supervised Continual Learning
by: Luo, Yan, et al.
Published: (2022)
by: Luo, Yan, et al.
Published: (2022)
Context-Based Semantic-Aware Alignment for Semi-Supervised Multi-Label Learning
by: Fan, Heng-Bo, et al.
Published: (2024)
by: Fan, Heng-Bo, et al.
Published: (2024)
Semi-Supervised Variational Adversarial Active Learning via Learning to Rank and Agreement-Based Pseudo Labeling
by: Lyu, Zongyao, et al.
Published: (2024)
by: Lyu, Zongyao, et al.
Published: (2024)
Similar Items
-
A Multi-View Consistency Framework with Semi-Supervised Domain Adaptation
by: Hong, Yuting, et al.
Published: (2026) -
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation
by: Xiao, Hui, et al.
Published: (2024) -
Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
by: Sun, Xueqing, et al.
Published: (2025) -
Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling
by: Qiu, Yunfei, et al.
Published: (2026) -
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition
by: Dave, Ishan Rajendrakumar, et al.
Published: (2024)