13 papers · 1 filter
Reliev3R: Relieving Feed-forward Reconstruction from Multi-View Geometric Annotations
Youyu Chen, Junjun Jiang, Yueru Luo +4
With recent advances, Feed-forward Reconstruction Models (FFRMs) have demonstrated great potential in reconstruction quality and adaptiveness to multiple downstream tasks. However,…
UDPNet: Unleashing Depth-based Priors for Robust Image Dehazing
Zengyuan Zuo, Junjun Jiang, Gang Wu +1
Image dehazing has witnessed significant advancements with the development of deep learning models. However, most existing methods focus solely on single-modal RGB features, neglec…
Semantics and Content Matter: Towards Multi-Prior Hierarchical Mamba for Image Deraining
Zhaocheng Yu, Kui Jiang, Junjun Jiang +3
Rain significantly degrades the performance of computer vision systems, particularly in applications like autonomous driving and video surveillance. While existing deraining method…
Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
Gang Wu, Junjun Jiang, Kui Jiang +1
Unified image restoration models for diverse and mixed degradations often suffer from unstable optimization dynamics and inter-task conflicts. This paper introduces Self-Improved P…
VRS-UIE: Value-Driven Reordering Scanning for Underwater Image Enhancement
Kui Jiang, Yan Luo, Junjun Jiang +3
State Space Models (SSMs) have emerged as a promising backbone for vision tasks due to their linear complexity and global receptive field. However, in the context of Underwater Ima…
NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results
Zheng Chen, Jingkai Wang, Kai Liu +51
This paper provides a review of the NTIRE 2025 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on ge…
Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration
Gang Wu, Junjun Jiang, Kui Jiang +2
All-in-One Image Restoration (AiOIR), which addresses diverse degradation types with a unified model, presents significant challenges in designing task-aware prompts that effective…
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…
DSwinIR: Rethinking Window-based Attention for Image Restoration
Gang Wu, Junjun Jiang, Kui Jiang +2
Image restoration has witnessed significant advancements with the development of deep learning models. Transformer-based models, particularly those using window-based self-attentio…
COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian Splitting
Jiaxin Zhang, Junjun Jiang, Youyu Chen +2
Accurate object segmentation is crucial for high-quality scene understanding in the 3D vision domain. However, 3D segmentation based on 3D Gaussian Splatting (3DGS) struggles with…
DashGaussian: Optimizing 3D Gaussian Splatting in 200 Seconds
Youyu Chen, Junjun Jiang, Kui Jiang +4
3D Gaussian Splatting (3DGS) renders pixels by rasterizing Gaussian primitives, where the rendering resolution and the primitive number, concluded as the optimization complexity, d…
FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust Fusion
Pihai Sun, Junjun Jiang, Yuanqi Yao +4
Image-event joint depth estimation methods leverage complementary modalities for robust perception, yet face challenges in generalizability stemming from two factors: 1) limited an…
LLV-FSR: Exploiting Large Language-Vision Prior for Face Super-resolution
Chenyang Wang, Wenjie An, Kui Jiang +2
Existing face super-resolution (FSR) methods have made significant advancements, but they primarily super-resolve face with limited visual information, original pixel-wise space in…