120 citations · 907 across the 57 of their papers we have counts for
8 papers · 1 filter
Gated Context Aggregation Network for Image Dehazing and Deraining
Dongdong Chen, Mingming He, Qingnan Fan +5
Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of leveraging traditional low-level or handcrafted image priors as the restoration constraints, e.…
CariGANs: Unpaired Photo-to-Caricature Translation
Kaidi Cao, Jing Liao, Lu Yuan
Facial caricature is an art form of drawing faces in an exaggerated way to convey humor or sarcasm. In this paper, we propose the first Generative Adversarial Network (GAN) for unp…
Deep Video-Based Performance Cloning
Kfir Aberman, Mingyi Shi, Jing Liao +3
We present a new video-based performance cloning technique. After training a deep generative network using a reference video capturing the appearance and dynamics of a target actor…
Deep Exemplar-based Colorization
Mingming He, Dongdong Chen, Jing Liao +2
We propose the first deep learning approach for exemplar-based local colorization. Given a reference color image, our convolutional neural network directly maps a grayscale image t…
Arbitrary Style Transfer with Deep Feature Reshuffle
Shuyang Gu, Congliang Chen, Jing Liao +1
This paper introduces a novel method by reshuffling deep features (i.e., permuting the spacial locations of a feature map) of the style image for arbitrary style transfer. We theor…
Neural Best-Buddies: Sparse Cross-Domain Correspondence
Kfir Aberman, Jing Liao, Mingyi Shi +3
Correspondence between images is a fundamental problem in computer vision, with a variety of graphics applications. This paper presents a novel method for sparse cross-domain corre…
Stylize Aesthetic QR Code
Mingliang Xu, Hao Su, Yafei Li +5
With the continued proliferation of smart mobile devices, Quick Response (QR) code has become one of the most-used types of two-dimensional code in the world. Aiming at beautifying…
Stereoscopic Neural Style Transfer
Dongdong Chen, Lu Yuan, Jing Liao +2
This paper presents the first attempt at stereoscopic neural style transfer, which responds to the emerging demand for 3D movies or AR/VR. We start with a careful examination of ap…