Spatio-Temporal Pixel-Level Contrastive Learning-based Source-Free Domain Adaptation for Video Semantic Segmentation

Author:

Lo Shao-Yuan1,Oza Poojan2,Chennupati Sumanth2,Galindo Alejandro2,Patel Vishal M.1

Affiliation:

1. Johns Hopkins University

2. Amazon

Publisher

IEEE

Reference53 articles.

1. Momentum Contrast for Unsupervised Visual Representation Learning

2. Do-main adaptive video segmentation via temporal consistency regularization;guan;In IEEE International Conf on Computer Vision,0

3. Temporally Distributed Networks for Fast Video Semantic Segmentation

4. Deep Residual Learning for Image Recognition

5. Confidence Regularized Self-Training

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1. A Comprehensive Survey on Source-Free Domain Adaptation;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-08

2. Source-free unsupervised domain adaptation: A survey;Neural Networks;2024-06

3. Source-Free Unsupervised Domain Adaptation: Current research and future directions;Neurocomputing;2024-01

4. Unsupervised Camouflaged Object Segmentation as Domain Adaptation;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

5. Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

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