1 code implementation • 13 May 2024 • Haoyu Deng, Zijing Xu, Yule Duan, Xiao Wu, Wenjie Shu, Liang-Jian Deng
In this paper, we attempt to interpret the behavior of deep neural networks in ISR using theories from the field of signal processing.
no code implementations • 23 Apr 2024 • Yu-Jie Liang, ZiHan Cao, Liang-Jian Deng, Xiao Wu
Besides, a new decoder employing a complex Gabor wavelet activation function, called Spatial-Frequency Interactive Decoder (SFID), is invented to enhance the interaction of INR features.
1 code implementation • 17 Apr 2024 • Yu Zhong, Xiao Wu, Liang-Jian Deng, ZiHan Cao
Pansharpening is a significant image fusion technique that merges the spatial content and spectral characteristics of remote sensing images to generate high-resolution multispectral images.
no code implementations • 17 Apr 2024 • ZiHan Cao, Xiao Wu, Liang-Jian Deng
In this paper, we identify shortcomings in directly applying DPMs to the task of pansharpening as an inverse problem: 1) initiating sampling directly from Gaussian noise neglects the low-resolution multispectral image (LRMS) as a prior; 2) low sampling efficiency often necessitates a higher number of sampling steps.
1 code implementation • 14 Apr 2024 • ZiHan Cao, Xiao Wu, Liang-Jian Deng, Yu Zhong
The LEVM block can improve local information perception of the network and simultaneously learn local and global spatial information.
1 code implementation • 11 Apr 2024 • Siran Peng, Xiangyu Zhu, Haoyu Deng, Liang-Jian Deng, Zhen Lei
Remote sensing image fusion aims to generate a high-resolution multi/hyper-spectral image by combining a high-resolution image with limited spectral data and a low-resolution image rich in spectral information.
1 code implementation • CVPR 2024 • Yule Duan, Xiao Wu, Haoyu Deng, Liang-Jian Deng
In this paper, we introduce a so-called content-adaptive non-local convolution (CANConv), a novel method tailored for remote sensing image pansharpening.
no code implementations • 1 Apr 2024 • Wen-Jie Shu, Hong-Xia Dou, Rui Wen, Xiao Wu, Liang-Jian Deng
In response, we present the Cross Modulation Transformer (CMT), a pioneering method that modifies the attention mechanism.
no code implementations • 24 Aug 2023 • Yupu Yao, ShangQi Deng, ZiHan Cao, Harry Zhang, Liang-Jian Deng
One underlying cause is that traditional diffusion models approximate Gaussian noise distribution by utilizing predictive noise, without fully accounting for the impact of inherent information within the input itself.
1 code implementation • 12 Aug 2023 • Xuerui Qiu, Rui-Jie Zhu, Yuhong Chou, Zhaorui Wang, Liang-Jian Deng, Guoqi Li
Experiments on CIFAR10/100 and ImageNet datasets demonstrate that GAC achieves state-of-the-art accuracy with remarkable efficiency.
Ranked #112 on
Image Classification
on CIFAR-10
1 code implementation • 24 Jul 2023 • Qing-Hua Zhang, Liang-Tian He, Yi-Lun Wang, Liang-Jian Deng, Jun Liu
Very recently, a quaternion-based WNNM approach (QWNNM) has been developed to mitigate this issue, which is capable of representing the color image as a whole in the quaternion domain and preserving the inherent correlation among the three color channels.
no code implementations • 14 Jul 2023 • ShangQi Deng, RuoCheng Wu, Liang-Jian Deng, Ran Ran, Gemine Vivone
In this paper, inspired by previous work of MHIF task, we realize that HR-MSI could serve as a high-frequency detail auxiliary input, leading us to propose a novel INR-based hyperspectral fusion function named Implicit Neural Feature Fusion Function (INF).
no code implementations • 10 Apr 2023 • ZiHan Cao, ShiQi Cao, Xiao Wu, JunMing Hou, Ran Ran, Liang-Jian Deng
Denosing diffusion model, as a generative model, has received a lot of attention in the field of image generation recently, thanks to its powerful generation capability.
1 code implementation • 13 Dec 2022 • Siran Peng, Chenhao Guo, Xiao Wu, Liang-Jian Deng
The U2Net utilizes a spatial U-Net and a spectral U-Net to extract spatial details and spectral characteristics, which allows for the discriminative and hierarchical learning of features from diverse images.
Hyperspectral Image Super-Resolution
Image Super-Resolution
+1
1 code implementation • 21 Jun 2022 • Rui-Jie Zhu, Malu Zhang, Qihang Zhao, Haoyu Deng, Yule Duan, Liang-Jian Deng
Given the critical role of attention mechanisms in enhancing neural network performance, the integration of SNNs and attention mechanisms exhibits potential to deliver energy-efficient and high-performance computing paradigms.
no code implementations • 30 Mar 2022 • Cheng Jin, Rui-Jie Zhu, Xiao Wu, Liang-Jian Deng
Spiking Neural Networks (SNNs) have piqued researchers' interest because of their capacity to process temporal information and low power consumption.
no code implementations • 4 Dec 2021 • Tian-Jing Zhang, Liang-Jian Deng, Ting-Zhu Huang, Jocelyn Chanussot, Gemine Vivone
Pansharpening refers to the fusion of a panchromatic image with a high spatial resolution and a multispectral image with a low spatial resolution, aiming to obtain a high spatial resolution multispectral image.
no code implementations • 5 Sep 2021 • Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng
Hyperspectral image has become increasingly crucial due to its abundant spectral information.
no code implementations • 24 Jul 2021 • Zi-Rong Jin, Liang-Jian Deng, Tai-Xiang Jiang, Tian-Jing Zhang
The convolution operation is a powerful tool for feature extraction and plays a prominent role in the field of computer vision.
Hyperspectral Image Super-Resolution
Image Super-Resolution
+1
no code implementations • ICCV 2021 • Xiao Wu, Ting-Zhu Huang, Liang-Jian Deng, Tian-Jing Zhang
In order to enhance the relationships of inter-branches, dynamic cross feature transfers are embedded into multiple branches to obtain high-resolution representations.
no code implementations • 29 May 2020 • Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng, Tai-Xiang Jiang, Gemine Vivone, Jocelyn Chanussot
In order to alleviate this issue, in this work, we propose a simple and efficient architecture for deep convolutional neural networks to fuse a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI), yielding a high-resolution hyperspectral image (HR-HSI).
no code implementations • 26 Aug 2018 • Ye-Tao Wang, Xi-Le Zhao, Tai-Xiang Jiang, Liang-Jian Deng, Yi Chang, Ting-Zhu Huang
Then, our framework starts with learning the motion blur kernel, which is determined by two factors including angle and length, by a plain neural network, denoted as parameter net, from a patch of the texture component.
3 code implementations • 20 Mar 2018 • Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
In this paper, we propose a novel video rain streak removal approach FastDeRain, which fully considers the discriminative characteristics of rain streaks and the clean video in the gradient domain.
4 code implementations • 15 Dec 2017 • Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng
In this paper, we investigate tensor recovery problems within the tensor singular value decomposition (t-SVD) framework.
no code implementations • CVPR 2017 • Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
Rain streaks removal is an important issue of the outdoor vision system and has been recently investigated extensively.
no code implementations • 12 Mar 2015 • Liang-Jian Deng, Weihong Guo, Ting-Zhu Huang
We propose a new iterative model for single image super-resolution based on an observation: an image is consisted of smooth components and non-smooth components, and we use two classes of approximated Heaviside functions (AHFs) to represent them respectively.