2 citations · 6 across the 5 of their papers we have counts for
5 papers
Energy-based Domain-Adaptive Segmentation with Depth Guidance
Jinjing Zhu, Zhedong Hu, Tae-Kyun Kim +1
Recent endeavors have been made to leverage self-supervised depth estimation as guidance in unsupervised domain adaptation (UDA) for semantic segmentation. Prior arts, however, ove…
Source-Free Cross-Modal Knowledge Transfer by Unleashing the Potential of Task-Irrelevant Data
Jinjing Zhu, Yucheng Chen, Lin Wang
Source-free cross-modal knowledge transfer is a crucial yet challenging task, which aims to transfer knowledge from one source modality (e.g., RGB) to the target modality (e.g., de…
A Good Student is Cooperative and Reliable: CNN-Transformer Collaborative Learning for Semantic Segmentation
Jinjing Zhu, Yunhao Luo, Xu Zheng +2
In this paper, we strive to answer the question "how to collaboratively learn convolutional neural network (CNN)-based and vision transformer (ViT)-based models by selecting and ex…
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation
Xu Zheng, Jinjing Zhu, Yexin Liu +3
The ability of scene understanding has sparked active research for panoramic image semantic segmentation. However, the performance is hampered by distortion of the equirectangular…
Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective
Jinjing Zhu, Haotian Bai, Lin Wang
Endeavors have been recently made to leverage the vision transformer (ViT) for the challenging unsupervised domain adaptation (UDA) task. They typically adopt the cross-attention i…