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Siliang Wang

1 accepted papers

2022

Deep Tri-Training for Semi-Supervised Image Segmentation

RA-L 2022

Semantic segmentation is of great value to autonomous driving and many robotic applications, while it highly depends on costly and time-consuming pixel-level annotation. To make full use of unlabeled data, this work proposes a deep tri-training framework (dubbed DTT) to utilize labeled along with un

Cited by 11SourceScholar