Adversarial cross-modal unsupervised domain adaptation in semantic segmentation
3D semantic segmentation is a vital problem in automatic driving, and thus a hot field in deep learning. These days, the research for unsupervised domain adaptation rises for solving the problem of lacking annotated datasets. However, the research on 3D UDA in semantic segmentation is still a blu...
Saved in:
Main Author: | Shi, Mengqi |
---|---|
Other Authors: | Xie Lihua |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/159248 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Multi-level adversarial network for domain adaptive semantic segmentation
by: Huang, Jiaxing, et al.
Published: (2022) -
Unsupervised domain adaptation on object recognition
by: Wang, Boxiang
Published: (2022) -
Unsupervised modality adaptation with text-to-Image diffusion models for semantic segmentation
by: XIA, Ruihao, et al.
Published: (2024) -
Unsupervised domain adaptation for LiDAR segmentation
by: Kong, Lingdong
Published: (2022) -
Domain adaption for semantic segmentation
by: Saklani Pankaj
Published: (2019)