activity
20202022
most citedImage Compression with Encoder-Decoder Matched Semantic Segmentation

39 citations · 54 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Interactive Image Manipulation with Complex Text Instructions

Ryugo Morita, Zhiqiang Zhang, Man M. Ho +1

Recently, text-guided image manipulation has received increasing attention in the research field of multimedia processing and computer vision due to its high flexibility and contro…

cs.MM2021

Real-time FPGA Design for OMP Targeting 8K Image Reconstruction

Jiayao Xu, Chen Fu, Zhiqiang Zhang +1

During the past decade, implementing reconstruction algorithms on hardware has been at the center of much attention in the field of real-time reconstruction in Compressed Sensing (…

eess.IV20213 cited

CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation

Bowen Huang, Xiao Yan, Jinjia Zhou +1

Most deep network methods for compressive sensing reconstruction suffer from the black-box characteristic of DNN. In this paper, a deep neural network with interpretable motion est…

cs.MM20213 cited

RCLC: ROI-based joint conventional and learning video compression

Trinh Man Hoang, Jinjia Zhou

COVID-19 leads to the high demand for remote interactive systems ever seen. One of the key elements of these systems is video streaming, which requires a very high network bandwidt…

cs.CV2021

Deep Photo Scan: Semi-Supervised Learning for dealing with the real-world degradation in Smartphone Photo Scanning

Man M. Ho, Jinjia Zhou

Physical photographs now can be conveniently scanned by smartphones and stored forever as a digital version, yet the scanned photos are not restored well. One solution is to train…

eess.IV202139 cited

Image Compression with Encoder-Decoder Matched Semantic Segmentation

Trinh Man Hoang, Jinjia Zhou, Yibo Fan

In recent years, layered image compression is demonstrated to be a promising direction, which encodes a compact representation of the input image and apply an up-sampling network t…