5 citations · 5 across the 3 of their papers we have counts for
9 papers
FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolution
Zhengxue Wang, Zhiqiang Yan, Yuan Wu +3
We introduce FoundDSR, a generalizable foundation model for robust depth reconstruction across unseen data distributions using RGB-D pairs. FoundDSR begins with a guided 2D Gaussia…
Multi-Order Matching Network for Alignment-Free Depth Super-Resolution
Zhengxue Wang, Zhiqiang Yan, Yuan Wu +3
Recent guided depth super-resolution methods are premised on the assumption of strict spatial alignment between depth and RGB, achieving high-quality depth reconstruction. However,…
Transformer-Progressive Mamba Network for Lightweight Image Super-Resolution
Sichen Guo, Wenjie Li, Yuanyang Liu +3
Recently, Mamba-based super-resolution (SR) methods have demonstrated the ability to capture global receptive fields with linear complexity, addressing the quadratic computational…
Self-Supervised Selective-Guided Diffusion Model for Old-Photo Face Restoration
Wenjie Li, Xiangyi Wang, Heng Guo +2
Old-photo face restoration poses significant challenges due to compounded degradations such as breakage, fading, and severe blur. Existing pre-trained diffusion-guided methods eith…
FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution
Siyu Xu, Wenjie Li, Guangwei Gao +3
Face super-resolution (FSR) under limited computational budgets remains challenging. Existing methods often treat all facial pixels equally, leading to suboptimal resource allocati…
DORNet: A Degradation Oriented and Regularized Network for Blind Depth Super-Resolution
Zhengxue Wang, Zhiqiang Yan, Jinshan Pan +3
Recent RGB-guided depth super-resolution methods have achieved impressive performance under the assumption of fixed and known degradation (e.g., bicubic downsampling). However, in…
HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenes
Changfeng Feng, Zhenyuan Chen, Xiang Li +5
Object detection from aerial platforms under adverse atmospheric conditions, particularly haze, is paramount for robust drone autonomy. Yet, this domain remains largely underexplor…
Attention-Guided Multi-scale Interaction Network for Face Super-Resolution
Xujie Wan, Wenjie Li, Guangwei Gao +3
Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid network…
Scene Prior Filtering for Depth Super-Resolution
Zhengxue Wang, Zhiqiang Yan, Ming-Hsuan Yang +4
Multi-modal fusion serves as a cornerstone for successful depth map super-resolution. However, commonly used fusion strategies, such as addition and concatenation, fall short of ef…