332 citations · 1.5k across the 59 of their papers we have counts for
21 papers · 1 filter
Towards Unified Semantic and Controllable Image Fusion: A Diffusion Transformer Approach
Jiayang Li, Chengjie Jiang, Junjun Jiang +3
Image fusion aims to blend complementary information from multiple sensing modalities, yet existing approaches remain limited in robustness, adaptability, and controllability. Most…
Survey of Multimodal Geospatial Foundation Models: Techniques, Applications, and Challenges
Liling Yang, Ning Chen, Jun Yue +5
Foundation models have transformed natural language processing and computer vision, and their impact is now reshaping remote sensing image analysis. With powerful generalization an…
NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Florin-Alexandru Vasluianu +102
This paper presents a comprehensive review of the NTIRE 2025 Low-Light Image Enhancement (LLIE) Challenge, highlighting the proposed solutions and final outcomes. The objective of…
Residual Diffusion Bridge Model for Image Restoration
Hebaixu Wang, Jing Zhang, Haoyang Chen +4
Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restoration. Most existing methods mere…
DistillMatch: Leveraging Knowledge Distillation from Vision Foundation Model for Multimodal Image Matching
Meng Yang, Fan Fan, Zizhuo Li +3
Multimodal image matching seeks pixel-level correspondences between images of different modalities, crucial for cross-modal perception, fusion and analysis. However, the significan…
LUT-Fuse: Towards Extremely Fast Infrared and Visible Image Fusion via Distillation to Learnable Look-Up Tables
Xunpeng Yi, Yibing Zhang, Xinyu Xiang +3
Current advanced research on infrared and visible image fusion primarily focuses on improving fusion performance, often neglecting the applicability on real-time fusion devices. In…
TemCoCo: Temporally Consistent Multi-modal Video Fusion with Visual-Semantic Collaboration
Meiqi Gong, Hao Zhang, Xunpeng Yi +2
Existing multi-modal fusion methods typically apply static frame-based image fusion techniques directly to video fusion tasks, neglecting inherent temporal dependencies and leading…
Towards Perfection: Building Inter-component Mutual Correction for Retinex-based Low-light Image Enhancement
Luyang Cao, Han Xu, Jian Zhang +4
In low-light image enhancement, Retinex-based deep learning methods have garnered significant attention due to their exceptional interpretability. These methods decompose images in…
GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry
Jiajun Le, Jiayi Ma
Recent progress in two-view geometry increasingly emphasizes enforcing smoothness and global consistency priors when estimating motion fields between pairs of images. However, in c…
Deep Learning Reforms Image Matching: A Survey and Outlook
Shihua Zhang, Zizhuo Li, Kaining Zhang +6
Image matching, which establishes correspondences between two images to recover 3D structure and camera geometry, is a cornerstone of computer vision and underpins a wide range of…
DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration
Hebaixu Wang, Jing Zhang, Haonan Guo +3
Diffusion models have achieved remarkable progress in universal image restoration. While existing methods speed up inference by reducing sampling steps, substantial step intervals…
Robust Fusion Controller: Degradation-aware Image Fusion with Fine-grained Language Instructions
Hao Zhang, Yanping Zha, Qingwei Zhuang +2
Current image fusion methods struggle to adapt to real-world environments encompassing diverse degradations with spatially varying characteristics. To address this challenge, we pr…
Balancing Task-invariant Interaction and Task-specific Adaptation for Unified Image Fusion
Xingyu Hu, Junjun Jiang, Chenyang Wang +3
Unified image fusion aims to integrate complementary information from multi-source images, enhancing image quality through a unified framework applicable to diverse fusion tasks. W…
CoMatch: Dynamic Covisibility-Aware Transformer for Bilateral Subpixel-Level Semi-Dense Image Matching
Zizhuo Li, Yifan Lu, Linfeng Tang +2
This prospective study proposes CoMatch, a novel semi-dense image matcher with dynamic covisibility awareness and bilateral subpixel accuracy. Firstly, observing that modeling cont…
DSPFusion: Image Fusion via Degradation and Semantic Dual-Prior Guidance
Linfeng Tang, Chunyu Li, Guoqing Wang +2
Existing fusion methods are tailored for high-quality images but struggle with degraded images captured under harsh circumstances, thus limiting the practical potential of image fu…
Selecting and Pruning: A Differentiable Causal Sequentialized State-Space Model for Two-View Correspondence Learning
Xiang Fang, Shihua Zhang, Hao Zhang +3
Two-view correspondence learning aims to discern true and false correspondences between image pairs by recognizing their underlying different information. Previous methods either t…
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery
Yansheng Li, Yuning Wu, Gong Cheng +9
Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manuall…
VideoFusion: A Spatio-Temporal Collaborative Network for Multi-modal Video Fusion
Linfeng Tang, Yeda Wang, Meiqi Gong +7
Compared to images, videos better reflect real-world acquisition and possess valuable temporal cues. However, existing multi-sensor fusion research predominantly integrates complem…
ControlFusion: A Controllable Image Fusion Framework with Language-Vision Degradation Prompts
Linfeng Tang, Yeda Wang, Zhanchuan Cai +2
Current image fusion methods struggle to address the composite degradations encountered in real-world imaging scenarios and lack the flexibility to accommodate user-specific requir…
HyperGCT: A Dynamic Hyper-GNN-Learned Geometric Constraint for 3D Registration
Xiyu Zhang, Jiayi Ma, Jianwei Guo +5
Geometric constraints between feature matches are critical in 3D point cloud registration problems. Existing approaches typically model unordered matches as a consistency graph and…
SpecDM: Hyperspectral Dataset Synthesis with Pixel-level Semantic Annotations
Wendi Liu, Pei Yang, Wenhui Hong +2
In hyperspectral remote sensing field, some downstream dense prediction tasks, such as semantic segmentation (SS) and change detection (CD), rely on supervised learning to improve…