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cs.CV2023
Exploring Limits of Diffusion-Synthetic Training with Weakly Supervised Semantic Segmentation
Ryota Yoshihashi, Yuya Otsuka, Kenji Doi +2
The advance of generative models for images has inspired various training techniques for image recognition utilizing synthetic images. In semantic segmentation, one promising appro…
cs.CV2022
Ladder Siamese Network: a Method and Insights for Multi-level Self-Supervised Learning
Ryota Yoshihashi, Shuhei Nishimura, Dai Yonebayashi +3
Siamese-network-based self-supervised learning (SSL) suffers from slow convergence and instability in training. To alleviate this, we propose a framework to exploit intermediate se…