50 citations · 69 across the 8 of their papers we have counts for
8 papers
Dual Inverse Degradation Network for Real-World SDRTV-to-HDRTV Conversion
Kepeng Xu, Li Xu, Gang He +4
In this study, we address the emerging necessity of converting Standard Dynamic Range Television (SDRTV) content into High Dynamic Range Television (HDRTV) in light of the limited…
SDRTV-to-HDRTV Conversion via Spatial-Temporal Feature Fusion
Kepeng Xu, Li Xu, Gang He +4
HDR(High Dynamic Range) video can reproduce realistic scenes more realistically, with a wider gamut and broader brightness range. HDR video resources are still scarce, and most vid…
AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
Furkan Kınlı, Sami Menteş, Barış Özcan +30
This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…
SDRTV-to-HDRTV via Hierarchical Dynamic Context Feature Mapping
Gang He, Kepeng Xu, Li Xu +4
In this work, we address the task of SDR videos to HDR videos(SDRTV-to-HDRTV). Previous approaches use global feature modulation for SDRTV-to-HDRTV. Feature modulation scales and s…
Global Priors Guided Modulation Network for Joint Super-Resolution and Inverse Tone-Mapping
Gang He, Shaoyi Long, Li Xu +5
Joint super-resolution and inverse tone-mapping (SR-ITM) aims to enhance the visual quality of videos that have quality deficiencies in resolution and dynamic range. This problem a…
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw +85
This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conj…
Transcoded Video Restoration by Temporal Spatial Auxiliary Network
Li Xu, Gang He, Jinjia Zhou +4
In most video platforms, such as Youtube, and TikTok, the played videos usually have undergone multiple video encodings such as hardware encoding by recording devices, software enc…
RR-DnCNN v2.0: Enhanced Restoration-Reconstruction Deep Neural Network for Down-Sampling Based Video Coding
Man M. Ho, Jinjia Zhou, Gang He
Integrating deep learning techniques into the video coding framework gains significant improvement compared to the standard compression techniques, especially applying super-resolu…