7 citations · 7 across the 5 of their papers we have counts for
5 papers
FSID: Fully Synthetic Image Denoising via Procedural Scene Generation
Gyeongmin Choe, Beibei Du, Seonghyeon Nam +3
For low-level computer vision and image processing ML tasks, training on large datasets is critical for generalization. However, the standard practice of relying on real-world imag…
HIME: Efficient Headshot Image Super-Resolution with Multiple Exemplars
Xiaoyu Xiang, Jon Morton, Fitsum A Reda +6
A promising direction for recovering the lost information in low-resolution headshot images is utilizing a set of high-resolution exemplars from the same identity. Complementary im…
Learning Spatio-Temporal Downsampling for Effective Video Upscaling
Xiaoyu Xiang, Yapeng Tian, Vijay Rengarajan +3
Downsampling is one of the most basic image processing operations. Improper spatio-temporal downsampling applied on videos can cause aliasing issues such as moiré patterns in space…
Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-Resolution
Xiaoyu Xiang, Yapeng Tian, Yulun Zhang +3
In this paper, we address the space-time video super-resolution, which aims at generating a high-resolution (HR) slow-motion video from a low-resolution (LR) and low frame rate (LF…
Feature-Align Network with Knowledge Distillation for Efficient Denoising
Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan +6
We propose an efficient neural network for RAW image denoising. Although neural network-based denoising has been extensively studied for image restoration, little attention has bee…