LC-MSM: Language-Conditioned Masked Segmentation Model for unsupervised domain adaptation
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software
Reference47 articles.
1. Prototype-guided feature learning for unsupervised domain adaptation;Du;Pattern Recognit.,2023
2. Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by Gaussian-guided latent alignment;Wang;Pattern Recognit.,2021
3. Incremental multi-target domain adaptation for object detection with efficient domain transfer;Nguyen-Meidine;Pattern Recognit.,2022
4. MCNet: Magnitude consistency network for domain adaptive object detection under inclement environments;Pang;Pattern Recognit.,2024
5. P. Zhang, B. Zhang, T. Zhang, D. Chen, Y. Wang, F. Wen, Prototypical pseudo label denoising and target structure learning for domain adaptive semantic segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 12414–12424.
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