20 citations · 26 across the 7 of their papers we have counts for
7 papers
S3VD: Semantic-Guidance Spatio-Temporal Scanning for Video Deraining
Kui Jiang, Yiang Chen, Yan Luo +3
Heavy rainfall severely degrades outdoor videos by corrupting high-frequency details and introducing motion blur, critically undermining the reliability of visual tasks. Recently,…
NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Suhang Yao +95
This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…
The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Kai Liu, Haoyang Yue, Zeli Lin +65
This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The challenge aims to recover high…
VDEGaussian: Video Diffusion Enhanced 4D Gaussian Splatting for Dynamic Urban Scenes Modeling
Yuru Xiao, Zihan Lin, Chao Lu +7
Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine…
GroupedMixer: An Entropy Model with Group-wise Token-Mixers for Learned Image Compression
Daxin Li, Yuanchao Bai, Kai Wang +3
Transformer-based entropy models have gained prominence in recent years due to their superior ability to capture long-range dependencies in probability distribution estimation comp…
Dynamic Association Learning of Self-Attention and Convolution in Image Restoration
Kui Jiang, Xuemei Jia, Wenxin Huang +3
CNNs and Self attention have achieved great success in multimedia applications for dynamic association learning of self-attention and convolution in image restoration. However, CNN…
Face Hallucination via Split-Attention in Split-Attention Network
Tao Lu, Yuanzhi Wang, Yanduo Zhang +4
Recently, convolutional neural networks (CNNs) have been widely employed to promote the face hallucination due to the ability to predict high-frequency details from a large number…