activity
20192021
most citedDVMark: A Deep Multiscale Framework for Video Watermarking

10 citations · 31 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CV20212 cited

MUSIQ: Multi-scale Image Quality Transformer

Junjie Ke, Qifei Wang, Yilin Wang +2

Image quality assessment (IQA) is an important research topic for understanding and improving visual experience. The current state-of-the-art IQA methods are based on convolutional…

cs.CV20219 cited

Adversarially Adaptive Normalization for Single Domain Generalization

Xinjie Fan, Qifei Wang, Junjie Ke +3

Single domain generalization aims to learn a model that performs well on many unseen domains with only one domain data for training. Existing works focus on studying the adversaria…

cs.CV2021

COMISR: Compression-Informed Video Super-Resolution

Yinxiao Li, Pengchong Jin, Feng Yang +3

Most video super-resolution methods focus on restoring high-resolution video frames from low-resolution videos without taking into account compression. However, most videos on the…

cs.MM202110 cited

DVMark: A Deep Multiscale Framework for Video Watermarking

Xiyang Luo, Yinxiao Li, Huiwen Chang +3

Video watermarking embeds a message into a cover video in an imperceptible manner, which can be retrieved even if the video undergoes certain modifications or distortions. Traditio…

cs.CV2021

Deep Perceptual Image Quality Assessment for Compression

Juan Carlos Mier, Eddie Huang, Hossein Talebi +2

Lossy Image compression is necessary for efficient storage and transfer of data. Typically the trade-off between bit-rate and quality determines the optimal compression level. This…

cs.CV2020

Multi-path Neural Networks for On-device Multi-domain Visual Classification

Qifei Wang, Junjie Ke, Joshua Greaves +9

Learning multiple domains/tasks with a single model is important for improving data efficiency and lowering inference cost for numerous vision tasks, especially on resource-constra…