1 code implementation • 18 Jul 2024 • YuHan Liu, Qianxin Huang, Siqi Hui, Jingwen Fu, Sanping Zhou, Kangyi Wu, Pengna Li, Jinjun Wang
In our work, we seek another way to use the semantic information, that is semantic-aware feature representation learning framework. Based on this, we propose SRMatcher, a new detector-free feature matching method, which encourages the network to learn integrated semantic feature representation. Specifically, to capture precise and rich semantics, we leverage the capabilities of recently popularized vision foundation models (VFMs) trained on extensive datasets.
no code implementations • 29 Jun 2023 • Siqi Hui, Sanping Zhou, Ye Deng, Jinjun Wang
Specifically, we select the teacher model as the one with the best validation accuracy during meta-training and restrict the symmetric Kullback-Leibler (SKL) divergence between the output distribution of the linear classifier of the teacher model and that of the student model.
2 code implementations • 12 May 2023 • Ye Deng, Siqi Hui, Sanping Zhou, Deyu Meng, Jinjun Wang
And based on this attention, a network called $T$-former is designed for image inpainting.
1 code implementation • 14 Nov 2021 • Siqi Hui, Sanping Zhou, Ye Deng, Wenli Huang, Jinjun Wang
TPL and TSL are supersets of perceptual and style losses and release the auxiliary potential of standard perceptual and style losses.