"pseudo-labeling" Papers

15 papers found

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

Haozhao Wang, Shengyu Wang, Jiaming Li et al.

ICML 2025

CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

Nikita Karaev, Iurii Makarov, Jianyuan Wang et al.

ICCV 2025highlightarXiv:2410.11831
223
citations

Point-to-Region Loss for Semi-Supervised Point-Based Crowd Counting

Wei Lin, Chenyang ZHAO, Antoni B. Chan

CVPR 2025highlightarXiv:2505.21943
5
citations

Probability-Density-aware Semi-supervised Learning

Shuyang Liu, Ruiqiu Zheng, Yunhang Shen et al.

AAAI 2025paperarXiv:2412.17547

Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift

Kaizheng Wang

NEURIPS 2025arXiv:2302.10160
15
citations

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

Ronghang Zhu, Mengxuan Hu, Weiming Zhuang et al.

CVPR 2025
5
citations

Scale-Free Graph-Language Models

Jianglin Lu, Yixuan Liu, Yitian Zhang et al.

ICLR 2025arXiv:2502.15189
1
citations

Steady Progress Beats Stagnation: Mutual Aid of Foundation and Conventional Models in Mixed Domain Semi-Supervised Medical Image Segmentation

Qinghe Ma, Jian Zhang, Zekun Li et al.

CVPR 2025arXiv:2503.16997
4
citations

Towards Cost-Effective Learning: A Synergy of Semi-Supervised and Active Learning

Tianxiang Yin, Ningzhong Liu, Han Sun

CVPR 2025
1
citations

Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning

Biao Liu, Ning Xu, Xiangyu Fang et al.

ICML 2024

Federated Learning with Extremely Noisy Clients via Negative Distillation

Yang Lu, Lin Chen, Yonggang Zhang et al.

AAAI 2024paperarXiv:2312.12703
21
citations

FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition

Ishan Rajendrakumar Dave, Mamshad Nayeem Rizve, Shah Mubarak

ECCV 2024arXiv:2409.01448
5
citations

Language-conditioned Detection Transformer

Jang Hyun Cho, Philipp Krähenbühl

CVPR 2024arXiv:2311.17902
6
citations

Mitigating Background Shift in Class-Incremental Semantic Segmentation

gilhan Park, WonJun Moon, SuBeen Lee et al.

ECCV 2024arXiv:2407.11859
12
citations

SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection

JUNSU KIM, Hoseong Cho, Jihyeon Kim et al.

CVPR 2024highlightarXiv:2402.17323
50
citations