21 citations · 37 across the 4 of their papers we have counts for
6 papers · 1 filter
Let's See Clearly: Contaminant Artifact Removal for Moving Cameras
Xiaoyu Li, Bo Zhang, Jing Liao +1
Contaminants such as dust, dirt and moisture adhering to the camera lens can greatly affect the quality and clarity of the resulting image or video. In this paper, we propose a vid…
Deep Sketch-guided Cartoon Video Inbetweening
Xiaoyu Li, Bo Zhang, Jing Liao +1
We propose a novel framework to produce cartoon videos by fetching the color information from two input keyframes while following the animated motion guided by a user sketch. The k…
Document Rectification and Illumination Correction using a Patch-based CNN
Xiaoyu Li, Bo Zhang, Jing Liao +1
We propose a novel learning method to rectify document images with various distortion types from a single input image. As opposed to previous learning-based methods, our approach s…
Blind Geometric Distortion Correction on Images Through Deep Learning
Xiaoyu Li, Bo Zhang, Pedro V. Sander +1
We propose the first general framework to automatically correct different types of geometric distortion in a single input image. Our proposed method employs convolutional neural ne…
Deep Exemplar-based Video Colorization
Bo Zhang, Mingming He, Jing Liao +4
This paper presents the first end-to-end network for exemplar-based video colorization. The main challenge is to achieve temporal consistency while remaining faithful to the refere…
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…