25 citations · 32 across the 11 of their papers we have counts for
12 papers
Trajectory-aware Shifted State Space Models for Online Video Super-Resolution
Qiang Zhu, Xiandong Meng, Yuxian Jiang +5
Online video super-resolution (VSR) is an important technique for many real-world video processing applications, which aims to restore the current high-resolution video frame based…
Compressed Video Super-Resolution based on Hierarchical Encoding
Yuxuan Jiang, Siyue Teng, Qiang Zhu +6
This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting s…
Blind Video Super-Resolution based on Implicit Kernels
Qiang Zhu, Yuxuan Jiang, Shuyuan Zhu +3
Blind video super-resolution (BVSR) is a low-level vision task which aims to generate high-resolution videos from low-resolution counterparts in unknown degradation scenarios. Exis…
FCVSR: A Frequency-aware Method for Compressed Video Super-Resolution
Qiang Zhu, Fan Zhang, Feiyu Chen +3
Compressed video super-resolution (SR) aims to generate high-resolution (HR) videos from the corresponding low-resolution (LR) compressed videos. Recently, some compressed video SR…
Texture-guided Coding for Deep Features
Lei Xiong, Xin Luo, Zihao Wang +3
With the rapid development of machine vision technology in recent years, many researchers have begun to focus on feature compression that is better suited for machine vision tasks.…
Multiple Latent Space Mapping for Compressed Dark Image Enhancement
Yi Zeng, Zhengning Wang, Yuxuan Liu +6
Dark image enhancement aims at converting dark images to normal-light images. Existing dark image enhancement methods take uncompressed dark images as inputs and achieve great perf…
Learning to Kindle the Starlight
Yu Yuan, Jiaqi Wu, Lindong Wang +4
Capturing highly appreciated star field images is extremely challenging due to light pollution, the requirements of specialized hardware, and the high level of photographic skills…
OL-DN: Online learning based dual-domain network for HEVC intra frame quality enhancement
Renwei Yang, Shuyuan Zhu, Xiaozhen Zheng +1
Convolution neural network (CNN) based methods offer effective solutions for enhancing the quality of compressed image and video. However, these methods ignore using the raw data t…
Luminance-Guided Chrominance Image Enhancement for HEVC Intra Coding
Hewei Liu, Renwei Yang, Shuyuan Zhu +2
In this paper, we propose a luminance-guided chrominance image enhancement convolutional neural network for HEVC intra coding. Specifically, we firstly develop a gated recursive as…
Cross-Block Difference Guided Fast CU Partition for VVC Intra Coding
Hewei Liu, Shuyuan Zhu, Ruiqin Xiong +2
In this paper, we propose a new fast CU partition algorithm for VVC intra coding based on cross-block difference. This difference is measured by the gradient and the content of sub…
Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure
Xiandong Meng, Xuan Deng, Shuyuan Zhu +1
In this paper, we propose a quality enhancement network of versatile video coding (VVC) compressed videos by jointly exploiting spatial details and temporal structure (SDTS). The p…
MGANet: A Robust Model for Quality Enhancement of Compressed Video
Xiandong Meng, Xuan Deng, Shuyuan Zhu +4
In video compression, most of the existing deep learning approaches concentrate on the visual quality of a single frame, while ignoring the useful priors as well as the temporal in…