398 citations · 537 across the 28 of their papers we have counts for
18 papers · 1 filter
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…
Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration
Feiyu Tan, Qi Xie, Zongben Xu +1
Image restoration is an inherently ill posed inverse problem. Equivariant networks that embed geometric symmetry priors can mitigate this ill posedness and improve performance. How…
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…
Rotation-Equivariant Self-Supervised Method in Image Denoising
Hanze Liu, Jiahong Fu, Qi Xie +1
Self-supervised image denoising methods have garnered significant research attention in recent years, for this kind of method reduces the requirement of large training datasets. Co…
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution
Xinyi Liu, Feiyu Tan, Qi Xie +2
Burst image processing (BIP), which captures and integrates multiple frames into a single high-quality image, is widely used in consumer cameras. As a typical BIP task, Burst Image…
TRG-Net: An Interpretable and Controllable Rain Generator
Zhiqiang Pang, Hong Wang, Qi Xie +2
Exploring and modeling rain generation mechanism is critical for augmenting paired data to ease training of rainy image processing models. Against this task, this study proposes a…
KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
Jiahong Fu, Hong Wang, Qi Xie +3
Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically co…
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment
Xinyi Liu, Qi Xie, Qian Zhao +2
Motivated by their recent advances, deep learning techniques have been widely applied to low-light image enhancement (LIE) problem. Among which, Retinex theory based ones, mostly f…
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions
Qi Xie, Qian Zhao, Zongben Xu +1
It has been shown that equivariant convolution is very helpful for many types of computer vision tasks. Recently, the 2D filter parametrization technique plays an important role wh…
Learning to Purify Noisy Labels via Meta Soft Label Corrector
Yichen Wu, Jun Shu, Qi Xie +2
Recent deep neural networks (DNNs) can easily overfit to biased training data with noisy labels. Label correction strategy is commonly used to alleviate this issue by designing a m…
From Rain Generation to Rain Removal
Hong Wang, Zongsheng Yue, Qi Xie +3
For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets. Most o…
Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Qi Xie, Minghao Zhou, Qian Zhao +3
Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems. However, only high-resolution multispectral (H…
Enhanced 3DTV Regularization and Its Applications on Hyper-spectral Image Denoising and Compressed Sensing
Jiangjun Peng, Qi Xie, Qian Zhao +3
The 3-D total variation (3DTV) is a powerful regularization term, which encodes the local smoothness prior structure underlying a hyper-spectral image (HSI), for general HSI proces…
Unsupervised/Semi-supervised Deep Learning for Low-dose CT Enhancement
Mingrui Geng, Yun Deng, Qian Zhao +4
Recently, deep learning(DL) methods have been proposed for the low-dose computed tomography(LdCT) enhancement, and obtain good trade-off between computational efficiency and image…
On the Optimal Solution of Weighted Nuclear Norm Minimization
Qi Xie, Deyu Meng, Shuhang Gu +4
In recent years, the nuclear norm minimization (NNM) problem has been attracting much attention in computer vision and machine learning. The NNM problem is capitalized on its conve…