activity
20172020
most citedA Comprehensive Benchmark for Single Image Compression Artifacts Reduction

95 citations · 120 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2020★ 1 cited

An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal

Sifeng Xia, Kunchangtai Liang, Wenhan Yang +2

In this paper, we study a new problem arising from the emerging MPEG standardization effort Video Coding for Machine (VCM), which aims to bridge the gap between visual feature comp…

eess.IV2020★ 20 cited

Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering

Dezhao Wang, Sifeng Xia, Wenhan Yang +1

In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filter. For (1), we design a deep…

eess.IV2019★ 95 cited

A Comprehensive Benchmark for Single Image Compression Artifacts Reduction

Jiaying Liu, Dong Liu, Wenhan Yang +3

We present a comprehensive study and evaluation of existing single image compression artifacts removal algorithms, using a new 4K resolution benchmark including diversified foregro…

cs.CV2019★ 2 cited

Deep Reference Generation with Multi-Domain Hierarchical Constraints for Inter Prediction

Jiaying Liu, Sifeng Xia, Wenhan Yang

Inter prediction is an important module in video coding for temporal redundancy removal, where similar reference blocks are searched from previously coded frames and employed to pr…

cs.MM2018★ 1 cited

A Group Variational Transformation Neural Network for Fractional Interpolation of Video Coding

Sifeng Xia, Wenhan Yang, Yueyu Hu +2

Motion compensation is an important technology in video coding to remove the temporal redundancy between coded video frames. In motion compensation, fractional interpolation is use…

cs.CV2017★ 1 cited

Dual Recovery Network with Online Compensation for Image Super-Resolution

Sifeng Xia, Wenhan Yang, Jiaying Liu +1

Image super-resolution (SR) methods essentially lead to a loss of some high-frequency (HF) information when predicting high-resolution (HR) images from low-resolution (LR) images w…