35 citations · 51 across the 32 of their papers we have counts for
33 papers
Predicting Functions, Not Features: KANs with Function-Space Joint-Embedding Predictive Learning for Medical Image Segmentation
Yungeng Liu, Xuanzi Fang, Yuge Zhang +3
Kolmogorov--Arnold Networks (KANs) introduce explicit functional representations by parameterizing each network edge as a learnable univariate function. However, existing KAN-based…
SegDem: Segmentation helps Demosaicing
Ping Chen, Xiangming Wang, Yongyong Chen +5
Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most existing methods formulate d…
The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results
Xiang Chen, Hao Li, Jiangxin Dong +89
This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image restoration under diverse real-wo…
Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation
Yungeng Liu, Xuanzi Fang, Haijin Zeng +2
Text-guided medical image segmentation leverages clinical semantics to improve lesion delineation, yet many existing models bind cross-modal fusion, supervision, and decoder design…
Computer-Aided Design Generation by Cascaded Discrete Diffusion Model
Honghu Pan, Xiaoling Luo, Yongyong Chen +2
Recent deep learning approaches seek to automate CAD creation by representing a model as a sequence of discrete commands and parameters, and then generating them using autoregressi…
Agentic Flow Steering and Parallel Rollout Search for Spatially Grounded Text-to-Image Generation
Ping Chen, Daoxuan Zhang, Xiangming Wang +3
Precise Text-to-Image (T2I) generation has achieved great success but is hindered by the limited relational reasoning of static text encoders and the error accumulation in open-loo…
Deep LoRA-Unfolding Networks for Image Restoration
Xiangming Wang, Haijin Zeng, Benteng Sun +4
Deep unfolding networks (DUNs), combining conventional iterative optimization algorithms and deep neural networks into a multi-stage framework, have achieved remarkable accomplishm…
HSI-VAR: Rethinking Hyperspectral Restoration through Spatial-Spectral Visual Autoregression
Xiangming Wang, Benteng Sun, Yungeng Liu +4
Hyperspectral images (HSIs) capture richer spatial-spectral information beyond RGB, yet real-world HSIs often suffer from a composite mix of degradations, such as noise, blur, and…
Vision-Language Controlled Deep Unfolding for Joint Medical Image Restoration and Segmentation
Ping Chen, Zicheng Huang, Xiangming Wang +4
We propose VL-DUN, a principled framework for joint All-in-One Medical Image Restoration and Segmentation (AiOMIRS) that bridges the gap between low-level signal recovery and high-…
SlowFast-SCI: Slow-Fast Deep Unfolding Learning for Spectral Compressive Imaging
Haijin Zeng, Xuan Lu, Jiezhang Cao +8
Humans learn in two complementary ways: a slow, cumulative process that builds broad, general knowledge, and a fast, on-the-fly process that captures specific experiences. Existing…
Association and Consolidation: Evolutionary Memory-Enhanced Incremental Multi-View Clustering
Zisen Kong, Bo Zhong, Pengyuan Li +3
Incremental multi-view clustering aims to achieve stable clustering results while addressing the stability-plasticity dilemma (SPD) in view-incremental scenarios. The core challeng…
Lightweight Quad Bayer HybridEVS Demosaicing via State Space Augmented Cross-Attention
Shiyang Zhou, Haijin Zeng, Yunfan Lu +3
Event cameras like the Hybrid Event-based Vision Sensor (HybridEVS) camera capture brightness changes as asynchronous "events" instead of frames, offering advanced application on m…
Vision-Language Gradient Descent-driven All-in-One Deep Unfolding Networks
Haijin Zeng, Xiangming Wang, Yongyong Chen +2
Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environ…
Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS Demosaicing
Shiyang Zhou, Haijin Zeng, Yunfan Lu +5
Quad Bayer demosaicing is the central challenge for enabling the widespread application of Hybrid Event-based Vision Sensors (HybridEVS). Although existing learning-based methods t…
Generative Model-Assisted Demosaicing for Cross-multispectral Cameras
Jiahui Luo, Kai Feng, Haijin Zeng +1
As a crucial part of the spectral filter array (SFA)-based multispectral imaging process, spectral demosaicing has exploded with the proliferation of deep learning techniques. Howe…
Global Graph Propagation with Hierarchical Information Transfer for Incomplete Contrastive Multi-view Clustering
Guoqing Chao, Kaixin Xu, Xijiong Xie +1
Incomplete multi-view clustering has become one of the important research problems due to the extensive missing multi-view data in the real world. Although the existing methods hav…
OTLRM: Orthogonal Learning-based Low-Rank Metric for Multi-Dimensional Inverse Problems
Xiangming Wang, Haijin Zeng, Jiaoyang Chen +3
In real-world scenarios, complex data such as multispectral images and multi-frame videos inherently exhibit robust low-rank property. This property is vital for multi-dimensional…
MambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging
Zhenghao Pan, Haijin Zeng, Jiezhang Cao +3
Color video snapshot compressive imaging (SCI) employs computational imaging techniques to capture multiple sequential video frames in a single Bayer-patterned measurement. With th…
Cross-Scan Mamba with Masked Training for Robust Spectral Imaging
Wenzhe Tian, Haijin Zeng, Yin-Ping Zhao +3
Snapshot Compressive Imaging (SCI) enables fast spectral imaging but requires effective decoding algorithms for hyperspectral image (HSI) reconstruction from compressed measurement…
LLEMamba: Low-Light Enhancement via Relighting-Guided Mamba with Deep Unfolding Network
Xuanqi Zhang, Haijin Zeng, Jinwang Pan +2
Transformer-based low-light enhancement methods have yielded promising performance by effectively capturing long-range dependencies in a global context. However, their elevated com…
MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results
Yaqi Wu, Zhihao Fan, Xiaofeng Chu +46
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algor…
DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Model
Zhenghao Pan, Haijin Zeng, Jiezhang Cao +2
This paper endeavors to advance the precision of snapshot compressive imaging (SCI) reconstruction for multispectral image (MSI). To achieve this, we integrate the advantageous att…
Hyper-Laplacian Regularized Concept Factorization in Low-rank Tensor Space for Multi-view Clustering
Zixiao Yu, Lele Fu, Zhiling Cai +1
Tensor-oriented multi-view subspace clustering has achieved significant strides in assessing high-order correlations and improving clustering analysis of multi-view data. Neverthel…
MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing
Haijin Zeng, Kai Feng, Shaoguang Huang +5
Hyperspectral imaging systems that use multispectral filter arrays (MSFA) capture only one spectral component in each pixel. Hyperspectral demosaicing is used to recover the non-me…