44 citations · 173 across the 28 of their papers we have counts for
26 papers · 1 filter
Cross-Scale Pansharpening via ScaleFormer and the PanScale Benchmark
Ke Cao, Xuanhua He, Xueheng Li +7
Pansharpening aims to generate high-resolution multi-spectral images by fusing the spatial detail of panchromatic images with the spectral richness of low-resolution MS data. Howev…
LookWise: Knowing When and Where to Look for Fine-Grained Visual Reasoning in Multimodal Large Language Models
Yuxiang Shen, Hailong Huang, Zhenkun Gao +6
Multimodal Large Language Models (MLLMs) are shifting towards "Thinking with Images" by actively exploring image details. While effective, large-scale training is computationally e…
Distilling Textual Priors from LLM to Efficient Image Fusion
Ran Zhang, Xuanhua He, Ke Cao +4
Multi-modality image fusion aims to synthesize a single, comprehensive image from multiple source inputs. Traditional approaches, such as CNNs and GANs, offer efficiency but strugg…
Shuffle Mamba: State Space Models with Random Shuffle for Multi-Modal Image Fusion
Ke Cao, Xuanhua He, Tao Hu +3
Multi-modal image fusion integrates complementary information from different modalities to produce enhanced and informative images. Although State-Space Models, such as Mamba, are…
Training-Free Large Model Priors for Multiple-in-One Image Restoration
Xuanhua He, Lang Li, Yingying Wang +7
Image restoration aims to reconstruct the latent clear images from their degraded versions. Despite the notable achievement, existing methods predominantly focus on handling specif…
Linearly-evolved Transformer for Pan-sharpening
Junming Hou, Zihan Cao, Naishan Zheng +6
Vision transformer family has dominated the satellite pan-sharpening field driven by the global-wise spatial information modeling mechanism from the core self-attention ingredient.…
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
Xuanhua He, Quande Liu, Shengju Qian +5
Generating high-fidelity human video with specified identities has attracted significant attention in the content generation community. However, existing techniques struggle to str…
Pan-Mamba: Effective pan-sharpening with State Space Model
Xuanhua He, Ke Cao, Keyu Yan +4
Pan-sharpening involves integrating information from low-resolution multi-spectral and high-resolution panchromatic images to generate high-resolution multi-spectral counterparts.…
Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain
Xuanhua He, Tao Hu, Guoli Wang +9
RAW to sRGB mapping, which aims to convert RAW images from smartphones into RGB form equivalent to that of Digital Single-Lens Reflex (DSLR) cameras, has become an important area o…
Frequency-Adaptive Pan-Sharpening with Mixture of Experts
Xuanhua He, Keyu Yan, Rui Li +3
Pan-sharpening involves reconstructing missing high-frequency information in multi-spectral images with low spatial resolution, using a higher-resolution panchromatic image as guid…
Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness
Guanlin Li, Naishan Zheng, Man Zhou +2
Adversarial examples are one of the most severe threats to deep learning models. Numerous works have been proposed to study and defend adversarial examples. However, these works la…
Empowering Low-Light Image Enhancer through Customized Learnable Priors
Naishan Zheng, Man Zhou, Yanmeng Dong +4
Deep neural networks have achieved remarkable progress in enhancing low-light images by improving their brightness and eliminating noise. However, most existing methods construct e…
Learned Image Reasoning Prior Penetrates Deep Unfolding Network for Panchromatic and Multi-Spectral Image Fusion
Man Zhou, Jie Huang, Naishan Zheng +1
The success of deep neural networks for pan-sharpening is commonly in a form of black box, lacking transparency and interpretability. To alleviate this issue, we propose a novel mo…
Generalized Lightness Adaptation with Channel Selective Normalization
Mingde Yao, Jie Huang, Xin Jin +4
Lightness adaptation is vital to the success of image processing to avoid unexpected visual deterioration, which covers multiple aspects, e.g., low-light image enhancement, image r…
High-quality Image Dehazing with Diffusion Model
Hu Yu, Jie Huang, Kaiwen Zheng +1
Image dehazing is quite challenging in dense-haze scenarios, where quite less original information remains in the hazy image. Though previous methods have made marvelous progress,…
Decomposition Ascribed Synergistic Learning for Unified Image Restoration
Jinghao Zhang, Feng Zhao
Learning to restore multiple image degradations within a single model is quite beneficial for real-world applications. Nevertheless, existing works typically concentrate on regardi…
PanFlowNet: A Flow-Based Deep Network for Pan-sharpening
Gang Yang, Xiangyong Cao, Wenzhe Xiao +4
Pan-sharpening aims to generate a high-resolution multispectral (HRMS) image by integrating the spectral information of a low-resolution multispectral (LRMS) image with the texture…
Random Weights Networks Work as Loss Prior Constraint for Image Restoration
Man Zhou, Naishan Zheng, Jie Huang +5
In this paper, orthogonal to the existing data and model studies, we instead resort our efforts to investigate the potential of loss function in a new perspective and present our b…
Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration
Man Zhou, Naishan Zheng, Jie Huang +2
Image and video restoration has achieved a remarkable leap with the advent of deep learning. The success of deep learning paradigm lies in three key components: data, model, and lo…
Probability-based Global Cross-modal Upsampling for Pansharpening
Zeyu Zhu, Xiangyong Cao, Man Zhou +2
Pansharpening is an essential preprocessing step for remote sensing image processing. Although deep learning (DL) approaches performed well on this task, current upsampling methods…
Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement
Chongyi Li, Chun-Le Guo, Man Zhou +4
Ultra-High-Definition (UHD) photo has gradually become the standard configuration in advanced imaging devices. The new standard unveils many issues in existing approaches for low-l…
Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network
Keyu Yan, Man Zhou, Jie Huang +4
Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to g…
Deep Fourier Up-Sampling
Man Zhou, Hu Yu, Jie Huang +5
Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling. However, spatial up-sampling operators (\emph{e.g.}, interpolation, transpos…
Enhancement by Your Aesthetic: An Intelligible Unsupervised Personalized Enhancer for Low-Light Images
Naishan Zheng, Jie Huang, Qi Zhu +3
Low-light image enhancement is an inherently subjective process whose targets vary with the user's aesthetic. Motivated by this, several personalized enhancement methods have been…