activity
20182022
most citedPANeRF: Pseudo-view Augmentation for Improved Neural Radiance Fields Based on Few-shot Inputs

4 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20224 cited

PANeRF: Pseudo-view Augmentation for Improved Neural Radiance Fields Based on Few-shot Inputs

Young Chun Ahn, Seokhwan Jang, Sungheon Park +2

The method of neural radiance fields (NeRF) has been developed in recent years, and this technology has promising applications for synthesizing novel views of complex scenes. Howev…

cs.CV20201 cited

Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations

Sungheon Park, Minsik Lee, Nojun Kwak

We propose a novel framework for training neural networks which is capable of learning 3D information of non-rigid objects when only 2D annotations are available as ground truths.…

cs.CV20191 cited

Pose estimator and tracker using temporal flow maps for limbs

Jihye Hwang, Jieun Lee, Sungheon Park +1

For human pose estimation in videos, it is significant how to use temporal information between frames. In this paper, we propose temporal flow maps for limbs (TML) and a multi-stri…

cs.SD2018

Music Source Separation Using Stacked Hourglass Networks

Sungheon Park, Taehoon Kim, Kyogu Lee +1

In this paper, we propose a simple yet effective method for multiple music source separation using convolutional neural networks. Stacked hourglass network, which was originally de…

cs.CV2018

3D Human Pose Estimation with Relational Networks

Sungheon Park, Nojun Kwak

In this paper, we propose a novel 3D human pose estimation algorithm from a single image based on neural networks. We adopted the structure of the relational networks in order to c…