Name
Abstract | ||
|---|---|---|
•A simple yet effective unsupervised image translation method (SUIT)is proposed for domain adaptation on semantic segmentation, which avoids labor-intensive pixel-wise annotation.•The decoupled model design makes it moreflexible; the adaptation network be easily transplanted to other segmentation networks without repeating the adaptation process.•A model average skill is developed to improve the performance in domain adaptation context. The effectiveness of our proposed model is verified on multiple synthetic-to-real adaptation benchmarks. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patcog.2020.107343 | Pattern Recognition |
Keywords | DocType | Volume |
Domain adaptation,Image segmentation,Image translation | Journal | 105 |
Issue | ISSN | Citations |
1 | 0031-3203 | 3 |
PageRank | References | Authors |
0.42 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Li | 1 | 17 | 4.90 |
| Wen-Ming Cao | 2 | 26 | 11.53 |
| Qianfen Jiao | 3 | 3 | 1.43 |
| Si Wu | 4 | 148 | 16.73 |
| Hau-San Wong | 5 | 1008 | 86.89 |