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of 8
pro vyhledávání: '"Kim, Geonung"'
With the recent growth of video-based Social Network Service (SNS) platforms, the demand for video editing among common users has increased. However, video editing can be challenging due to the temporally-varying factors such as camera movement and m
Externí odkaz:
http://arxiv.org/abs/2410.07600
As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by these I2I mode
Externí odkaz:
http://arxiv.org/abs/2401.17547
We introduce POP3D, a novel framework that creates a full $360^\circ$-view 3D model from a single image. POP3D resolves two prominent issues that limit the single-view reconstruction. Firstly, POP3D offers substantial generalizability to arbitrary ca
Externí odkaz:
http://arxiv.org/abs/2309.10279
While 3D GANs have recently demonstrated the high-quality synthesis of multi-view consistent images and 3D shapes, they are mainly restricted to photo-realistic human portraits. This paper aims to extend 3D GANs to a different, but meaningful visual
Externí odkaz:
http://arxiv.org/abs/2211.16798
Few-shot domain adaptation to multiple domains aims to learn a complex image distribution across multiple domains from a few training images. A na\"ive solution here is to train a separate model for each domain using few-shot domain adaptation method
Externí odkaz:
http://arxiv.org/abs/2211.14554
Autor:
Kim, Geonung, Kang, Kyoungkook, Kim, Seongtae, Lee, Hwayoon, Kim, Sehoon, Kim, Jonghyun, Baek, Seung-Hwan, Cho, Sunghyun
For realistic and vivid colorization, generative priors have recently been exploited. However, such generative priors often fail for in-the-wild complex images due to their limited representation space. In this paper, we propose BigColor, a novel col
Externí odkaz:
http://arxiv.org/abs/2207.09685
Training learning-based deblurring methods demands a tremendous amount of blurred and sharp image pairs. Unfortunately, existing synthetic datasets are not realistic enough, and deblurring models trained on them cannot handle real blurred images effe
Externí odkaz:
http://arxiv.org/abs/2202.08771
Autor:
Kim, Geonung
Publikováno v:
日本語・日本文化研究. 29:330-339
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::da9312ba76f0400a6625e7c85b2d628a
https://hdl.handle.net/11094/73718
https://hdl.handle.net/11094/73718
