Zobrazeno 1 - 10
of 619 461
pro vyhledávání: '"Yoon, AS"'
Novel view synthesis (NVS) aims to generate images at arbitrary viewpoints using multi-view images, and recent insights from neural radiance fields (NeRF) have contributed to remarkable improvements. Recently, studies on generalizable NeRF (G-NeRF) h
Externí odkaz:
http://arxiv.org/abs/2410.00672
Diffusion based Semantic Outlier Generation via Nuisance Awareness for Out-of-Distribution Detection
Autor:
Yoon, Suhee, Yoon, Sanghyu, Lee, Hankook, Sim, Ye Seul, Choi, Sungik, Lee, Kyungeun, Cho, Hye-Seung, Lim, Woohyung
Out-of-distribution (OOD) detection, which determines whether a given sample is part of the in-distribution (ID), has recently shown promising results through training with synthetic OOD datasets. Nonetheless, existing methods often produce outliers
Externí odkaz:
http://arxiv.org/abs/2408.14841
Autor:
Yoon, Hee Suk, Yoon, Eunseop, Tee, Joshua Tian Jin, Zhang, Kang, Heo, Yu-Jung, Chang, Du-Seong, Yoo, Chang D.
Multimodal Dialogue Response Generation (MDRG) is a recently proposed task where the model needs to generate responses in texts, images, or a blend of both based on the dialogue context. Due to the lack of a large-scale dataset specifically for this
Externí odkaz:
http://arxiv.org/abs/2408.05926
Test-Time Adaptation (TTA) has emerged as a crucial solution to the domain shift challenge, wherein the target environment diverges from the original training environment. A prime exemplification is TTA for Automatic Speech Recognition (ASR), which e
Externí odkaz:
http://arxiv.org/abs/2408.05769
Autor:
Yoon, Terri, Han, Myung Joon
To investigate the detailed magnetic properties of a recently discovered superconducting nickelate Nd6Ni5O12, we performed the first-principles electronic structure calculation based on density functional theory. The band dispersion, electronic charg
Externí odkaz:
http://arxiv.org/abs/2410.00851
Autor:
Kim, Jangyeong, Kang, Donggoo, Choi, Junyoung, Wi, Jeonga, Gwon, Junho, Bae, Jiun, Yoon, Dumim, Han, Junghyun
Text-to-texture generation has recently attracted increasing attention, but existing methods often suffer from the problems of view inconsistencies, apparent seams, and misalignment between textures and the underlying mesh. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2409.19989
Autor:
Yoon, Siyeop, Hu, Rui, Wang, Yuang, Tivnan, Matthew, Son, Young-don, Wu, Dufan, Li, Xiang, Kim, Kyungsang, Li, Quanzheng
PET imaging is a powerful modality offering quantitative assessments of molecular and physiological processes. The necessity for PET denoising arises from the intrinsic high noise levels in PET imaging, which can significantly hinder the accurate int
Externí odkaz:
http://arxiv.org/abs/2410.00184
In our study, we explore methods for detecting unwanted content lurking in visual datasets. We provide a theoretical analysis demonstrating that a model capable of successfully partitioning visual data can be obtained using only textual data. Based o
Externí odkaz:
http://arxiv.org/abs/2409.19840
In latent diffusion models (LDMs), denoising diffusion process efficiently takes place on latent space whose dimension is lower than that of pixel space. Decoder is typically used to transform the representation in latent space to that in pixel space
Externí odkaz:
http://arxiv.org/abs/2409.18442
The world is moving towards clean and renewable energy sources, such as wind energy, in an attempt to reduce greenhouse gas emissions that contribute to global warming. To enhance the analysis and storage of wind data, we introduce a deep learning fr
Externí odkaz:
http://arxiv.org/abs/2409.17367