9 papers
Flash EQ-Linear: Accelerating Equivariant Linear Layers via Group-wise Discrete Fourier Transform
Zhongchen Zhao, Jixin Wang, Qi Xie +4
Equivariant networks embed geometric symmetries as structural priors through weight sharing, achieving remarkable parameter efficiency across vision tasks. However, this parameter…
Image-to-Image Translation Framework Embedded with Rotation Symmetry Priors
Feiyu Tan, Heran Yang, Qihong Duan +3
Image-to-image translation (I2I) is a fundamental task in computer vision, focused on mapping an input image from a source domain to a corresponding image in a target domain while…
Rotation Equivariant Mamba for Vision Tasks
Zhongchen Zhao, Qi Xie, Keyu Huang +3
Rotation equivariance constitutes one of the most general and crucial structural priors for visual data, yet it remains notably absent from current Mamba-based vision architectures…
Vanilla Group Equivariant Vision Transformer: Simple and Effective
Jiahong Fu, Qi Xie, Deyu Meng +1
Incorporating symmetry priors as inductive biases to design equivariant Vision Transformers (ViTs) has emerged as a promising avenue for enhancing their performance. However, exist…
Rotation Equivariant Arbitrary-scale Image Super-Resolution
Qi Xie, Jiahong Fu, Zongben Xu +1
The arbitrary-scale image super-resolution (ASISR), a recent popular topic in computer vision, aims to achieve arbitrary-scale high-resolution recoveries from a low-resolution inpu…
A Regularization-Guided Equivariant Approach for Image Restoration
Yulu Bai, Jiahong Fu, Qi Xie +1
Equivariant and invariant deep learning models have been developed to exploit intrinsic symmetries in data, demonstrating significant effectiveness in certain scenarios. However, t…