28 citations · 66 across the 9 of their papers we have counts for
9 papers
VideoScaffold: Elastic-Scale Visual Hierarchies for Streaming Video Understanding in MLLMs
Naishan Zheng, Jie Huang, Qingpei Guo +1
Understanding long videos with multimodal large language models (MLLMs) remains challenging due to the heavy redundancy across frames and the need for temporally coherent represent…
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…
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…
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…
CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removal
Qianhao Yu, Naishan Zheng, Jie Huang +1
The key to shadow removal is recovering the contents of the shadow regions with the guidance of the non-shadow regions. Due to the inadequate long-range modeling, the CNN-based app…
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…
Source-Free Domain Adaptation for Real-world Image Dehazing
Hu Yu, Jie Huang, Yajing Liu +3
Deep learning-based source dehazing methods trained on synthetic datasets have achieved remarkable performance but suffer from dramatic performance degradation on real hazy images…