activity
20152022
most citedWeakly Supervised Learning of Instance Segmentation with Inter-pixel Relations

68 citations · 118 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2022★ 9 cited

Real-Time Video Deblurring via Lightweight Motion Compensation

Hyeongseok Son, Junyong Lee, Sunghyun Cho +1

While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead. This paper…

cs.CV2022★ 38 cited

Reference-based Video Super-Resolution Using Multi-Camera Video Triplets

Junyong Lee, Myeonghee Lee, Sunghyun Cho +1

We propose the first reference-based video super-resolution (RefVSR) approach that utilizes reference videos for high-fidelity results. We focus on RefVSR in a triple-camera settin…

cs.CV2022

MSSNet: Multi-Scale-Stage Network for Single Image Deblurring

Kiyeon Kim, Seungyong Lee, Sunghyun Cho

Most of traditional single image deblurring methods before deep learning adopt a coarse-to-fine scheme that estimates a sharp image at a coarse scale and progressively refines it a…

cs.CV2022

Realistic Blur Synthesis for Learning Image Deblurring

Jaesung Rim, Geonung Kim, Jungeon Kim +3

Training learning-based deblurring methods demands a tremendous amount of blurred and sharp image pairs. Unfortunately, existing synthetic datasets are not realistic enough, and de…

cs.CV2019★ 68 cited

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations

Jiwoon Ahn, Sunghyun Cho, Suha Kwak

This paper presents a novel approach for learning instance segmentation with image-level class labels as supervision. Our approach generates pseudo instance segmentation labels of…

cs.CV2016

Convergence Analysis of MAP based Blur Kernel Estimation

Sunghyun Cho, Seungyong Lee

One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly…

cs.HC2015★ 3 cited

PanoSwarm: Collaborative and Synchronized Multi-Device Panoramic Photography

Yan Wang, Sunghyun Cho, Jue Wang +1

Taking a picture has been traditionally a one-persons task. In this paper we present a novel system that allows multiple mobile devices to work collaboratively in a synchronized fa…