Top-K Confidence Map Aggregation for Robust Semantic Segmentation Against Unexpected Degradation
Author:
Affiliation:
1. School of Engineering, Tokyo Institute of Technology,Tokyo,Japan
2. NTT Corporation,Communication Science Laboratories,Tokyo,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10043349/10043179/10043389.pdf?arnumber=10043389
Reference27 articles.
1. Degraded image semantic segmentation with dense-gram networks;guo;IEEE Transactions Image Process (TIP),2019
2. Image Processing
3. Better Aggregation in Test-Time Augmentation
4. Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers
5. Cnn-based classification of degraded images with awareness of degradation levels;endo;IEEE Trans on Circuits and Systems for Video Technology,2020
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