Jonghee Back

According to our database, Jonghee Back authored at least 7 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Target-Aware Image Denoising for Inverse Monte Carlo Rendering.

Jeongmin Gu, Jonghee Back, Sung-Eui Yoon, Bochang Moon

ACM Trans. Graph., July, 2024

2023

Input-Dependent Uncorrelated Weighting for Monte Carlo Denoising.

Jonghee Back, Binh-Son Hua, Toshiya Hachisuka, Bochang Moon

Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

Robust Image Denoising of No-Flash Images Guided by Consistent Flash Images.

Geunwoo Oh, Jonghee Back, Jae-Pil Heo, Bochang Moon

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Self-Supervised Post-Correction for Monte Carlo Denoising.

Jonghee Back, Binh-Son Hua, Toshiya Hachisuka, Bochang Moon

Proceedings of the SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, August 7, 2022

2020

Deep combiner for independent and correlated pixel estimates.

Jonghee Back, Binh-Son Hua, Toshiya Hachisuka, Bochang Moon

ACM Trans. Graph., 2020

2019

Gradient Outlier Removal for Gradient-Domain Path Tracing.

Saerom Ha, Sojin Oh, Jonghee Back, Sung-Eui Yoon, Bochang Moon

Comput. Graph. Forum, 2019

2018

Feature Generation for Adaptive Gradient-Domain Path Tracing.

Jonghee Back, Sung-Eui Yoon, Bochang Moon

Comput. Graph. Forum, 2018