168 citations · 1.8k across the 114 of their papers we have counts for
14 papers · 1 filter
Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration
Zhibo Chen, Jianxin Lin, Tiankuang Zhou +1
Face restoration from low resolution and noise is important for applications of face analysis recognition. However, most existing face restoration models omit the multiple scale is…
Learning based Facial Image Compression with Semantic Fidelity Metric
Zhibo Chen, Tianyu He
Surveillance and security scenarios usually require high efficient facial image compression scheme for face recognition and identification. While either traditional general image c…
Learned Scalable Image Compression with Bidirectional Context Disentanglement Network
Zhizheng Zhang, Zhibo Chen, Jianxin Lin +1
In this paper, we propose a learned scalable/progressive image compression scheme based on deep neural networks (DNN), named Bidirectional Context Disentanglement Network (BCD-Net)…
Densely Semantically Aligned Person Re-Identification
Zhizheng Zhang, Cuiling Lan, Wenjun Zeng +1
We propose a densely semantically aligned person re-identification framework. It fundamentally addresses the body misalignment problem caused by pose/viewpoint variations, imperfec…
Hybrid Distortion Aggregated Visual Comfort Assessment for Stereoscopic Image Retargeting
Ya Zhou, Zhibo Chen, Weiping Li
Visual comfort is a quite important factor in 3D media service. Few research efforts have been carried out in this area especially in case of 3D content retargeting which may intro…
Unsupervised Single Image Deraining with Self-supervised Constraints
Xin Jin, Zhibo Chen, Jianxin Lin +2
Most existing single image deraining methods require learning supervised models from a large set of paired synthetic training data, which limits their generality, scalability and p…
Distribution Discrepancy Maximization for Image Privacy Preserving
Sen Liu, Jianxin Lin, Zhibo Chen
With the rapid increase in online photo sharing activities, image obfuscation algorithms become particularly important for protecting the sensitive information in the shared photos…
DeepIR: A Deep Semantics Driven Framework for Image Retargeting
Jianxin Lin, Tiankuang Zhou, Zhibo Chen
We present \emph{Deep Image Retargeting} (\emph{DeepIR}), a coarse-to-fine framework for content-aware image retargeting. Our framework first constructs the semantic structure of i…
Locating earthquakes with a network of seismic stations via a deep learning method
Xiong Zhang, Jie Zhang, Congcong Yuan +3
The accurate and automated determination of earthquake locations is still a challenging endeavor. However, such information is critical for monitoring seismic activity and assessin…
Visual Comfort Assessment for Stereoscopic Image Retargeting
Ya Zhou, Wei Zhou, Ping An +1
In recent years, visual comfort assessment (VCA) for 3D/stereoscopic content has aroused extensive attention. However, much less work has been done on the perceptual evaluation of…
Multi-Scale Face Restoration with Sequential Gating Ensemble Network
Jianxin Lin, Tiankuang Zhou, Zhibo Chen
Restoring face images from distortions is important in face recognition applications and is challenged by multiple scale issues, which is still not well-solved in research area. In…
Conditional Image-to-Image Translation
Jianxin Lin, Yingce Xia, Tao Qin +2
Image-to-image translation tasks have been widely investigated with Generative Adversarial Networks (GANs) and dual learning. However, existing models lack the ability to control t…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael Ong +26
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle c…
Learning for Video Compression
Zhibo Chen, Tianyu He, Xin Jin +1
One key challenge to learning-based video compression is that motion predictive coding, a very effective tool for video compression, can hardly be trained into a neural network. In…