most citedReducing Information Bottleneck for Weakly Supervised Semantic Segmentation

22 citations · 39 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2022

ANNA: Enhanced Language Representation for Question Answering

Changwook Jun, Hansol Jang, Myoseop Sim +4

Pre-trained language models have brought significant improvements in performance in a variety of natural language processing tasks. Most existing models performing state-of-the-art…

cs.CV20227 cited

Perception Prioritized Training of Diffusion Models

Jooyoung Choi, Jungbeom Lee, Chaehun Shin +3

Diffusion models learn to restore noisy data, which is corrupted with different levels of noise, by optimizing the weighted sum of the corresponding loss terms, i.e., denoising sco…

cs.CV202122 cited

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation

Jungbeom Lee, Jooyoung Choi, Jisoo Mok +1

Weakly supervised semantic segmentation produces pixel-level localization from class labels; however, a classifier trained on such labels is likely to focus on a small discriminati…

cs.CV20218 cited

FICGAN: Facial Identity Controllable GAN for De-identification

Yonghyun Jeong, Jooyoung Choi, Sungwon Kim +5

In this work, we present Facial Identity Controllable GAN (FICGAN) for not only generating high-quality de-identified face images with ensured privacy protection, but also detailed…

cs.CV20212 cited

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

Jooyoung Choi, Sungwon Kim, Yonghyun Jeong +2

Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in unconditional image generation. However, due to the stochasticity of the generative process in…

cs.LG2021

Toward Spatially Unbiased Generative Models

Jooyoung Choi, Jungbeom Lee, Yonghyun Jeong +1

Recent image generation models show remarkable generation performance. However, they mirror strong location preference in datasets, which we call spatial bias. Therefore, generator…