51 citations · 56 across the 34 of their papers we have counts for
11 papers · 1 filter
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…
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training
Yuanqi Yao, Gang Wu, Kui Jiang +4
Learning a self-supervised Monocular Depth Estimation (MDE) model with great generalization remains significantly challenging. Despite the success of adversarial augmentation in th…
A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trends
Junjun Jiang, Zengyuan Zuo, Gang Wu +2
Image restoration (IR) seeks to recover high-quality images from degraded observations caused by a wide range of factors, including noise, blur, compression, and adverse weather. W…
MCGS: Multiview Consistency Enhancement for Sparse-View 3D Gaussian Radiance Fields
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Radiance fields represented by 3D Gaussians excel at synthesizing novel views, offering both high training efficiency and fast rendering. However, with sparse input views, the lack…
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
Xin Jin, Chunle Guo, Xiaoming Li +39
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…
Spatial Annealing for Efficient Few-shot Neural Rendering
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Neural Radiance Fields (NeRF) with hybrid representations have shown impressive capabilities for novel view synthesis, delivering high efficiency. Nonetheless, their performance si…
The Third Monocular Depth Estimation Challenge
Jaime Spencer, Fabio Tosi, Matteo Poggi +38
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-…
SGCNeRF: Few-Shot Neural Rendering via Sparse Geometric Consistency Guidance
Yuru Xiao, Xianming Liu, Deming Zhai +3
Neural Radiance Field (NeRF) technology has made significant strides in creating novel viewpoints. However, its effectiveness is hampered when working with sparsely available views…
Exploiting Self-Supervised Constraints in Image Super-Resolution
Gang Wu, Junjun Jiang, Kui Jiang +1
Recent advances in self-supervised learning, predominantly studied in high-level visual tasks, have been explored in low-level image processing. This paper introduces a novel self-…
OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition
Yuchen Pan, Junjun Jiang, Kui Jiang +3
Depression Recognition (DR) poses a considerable challenge, especially in the context of the growing concerns surrounding privacy. Traditional automatic diagnosis of DR technology…
Unveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios
Jialei Xu, Xianming Liu, Junjun Jiang +4
Monocular depth estimation from RGB images plays a pivotal role in 3D vision. However, its accuracy can deteriorate in challenging environments such as nighttime or adverse weather…