3 papers
cs.CV2026
SCoRe: Clean Image Generation from Diffusion Models Trained on Noisy Images
Yuta Matsuzaki, Seiichi Uchida, Shumpei Takezaki
Diffusion models trained on noisy datasets often reproduce high-frequency training artifacts, significantly degrading generation quality. To address this, we propose SCoRe (Spectra…
cs.CV2017
cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey
Hirokatsu Kataoka, Soma Shirakabe, Yun He +14
The paper gives futuristic challenges disscussed in the cvpaper.challenge. In 2015 and 2016, we thoroughly study 1,600+ papers in several conferences/journals such as CVPR/ICCV/ECC…
cs.CV2017
Could you guess an interesting movie from the posters?: An evaluation of vision-based features on movie poster database
Yuta Matsuzaki, Kazushige Okayasu, Takaaki Imanari +5
In this paper, we aim to estimate the Winner of world-wide film festival from the exhibited movie poster. The task is an extremely challenging because the estimation must be done w…