8.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Asia Pacific Center for Theoretical PhysicsKR600 papers
- Institute for Basic ScienceKR238 papers
- Seoul National UniversityKR166 papers
- Korea Institute for Advanced StudyKR138 papers
- Korea Advanced Institute of Science and TechnologyKR103 papers
- Pohang Accelerator Laboratory91 papers
- Rutgers, The State University of New JerseyUS74 papers
- Lawrence Berkeley National LaboratoryUS67 papers
- Yonsei UniversityKR60 papers
- Korea UniversityKR57 papers
- Pusan National UniversityKR57 papers
- Sungkyunkwan UniversityKR57 papers
68 papers · 1 filter
Factorized Multi-Resolution HashGrid for Efficient Neural Radiance Fields: Execution on Edge-Devices
Kim Jun-Seong, Mingyu Kim, GeonU Kim +2
We introduce Fact-Hash, a novel parameter-encoding method for training on-device neural radiance fields. Neural Radiance Fields (NeRF) have proven pivotal in 3D representations, bu…
Polarimetric BSSRDF Acquisition of Dynamic Faces
Hyunho Ha, Inseung Hwang, Nestor Monzon +6
Acquisition and modeling of polarized light reflection and scattering help reveal the shape, structure, and physical characteristics of an object, which is increasingly important i…
Transferable polychromatic optical encoder for neural networks
Minho Choi, Jinlin Xiang, Anna Wirth-Singh +3
Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand…
P-Hologen: An End-to-End Generative Framework for Phase-Only Holograms
JooHyun Park, YuJin Jeon, HuiYong Kim +2
Holography stands at the forefront of visual technology, offering immersive, three-dimensional visualizations through the manipulation of light wave amplitude and phase. Although g…
PECI-Net: Bolus segmentation from video fluoroscopic swallowing study images using preprocessing ensemble and cascaded inference
Dougho Park, Younghun Kim, Harim Kang +7
Bolus segmentation is crucial for the automated detection of swallowing disorders in videofluoroscopic swallowing studies (VFSS). However, it is difficult for the model to accurate…
Limitations of Data-Driven Spectral Reconstruction -- An Optics-Aware Analysis
Qiang Fu, Matheus Souza, Eunsue Choi +3
Hyperspectral imaging empowers machine vision systems with the distinct capability of identifying materials through recording their spectral signatures. Recent efforts in data-driv…
Feature Unlearning for Pre-trained GANs and VAEs
Saemi Moon, Seunghyuk Cho, Dongwoo Kim
We tackle the problem of feature unlearning from a pre-trained image generative model: GANs and VAEs. Unlike a common unlearning task where an unlearning target is a subset of the…
Deep Deformable 3D Caricatures with Learned Shape Control
Yucheol Jung, Wonjong Jang, Soongjin Kim +3
A 3D caricature is an exaggerated 3D depiction of a human face. The goal of this paper is to model the variations of 3D caricatures in a compact parameter space so that we can prov…
Real-Time Video Deblurring via Lightweight Motion Compensation
Hyeongseok Son, Junyong Lee, Sunghyun Cho +1
While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead. This paper…
Reference-based Video Super-Resolution Using Multi-Camera Video Triplets
Junyong Lee, Myeonghee Lee, Sunghyun Cho +1
We propose the first reference-based video super-resolution (RefVSR) approach that utilizes reference videos for high-fidelity results. We focus on RefVSR in a triple-camera settin…
Grounded Situation Recognition with Transformers
Junhyeong Cho, Youngseok Yoon, Hyeonjun Lee +1
Grounded Situation Recognition (GSR) is the task that not only classifies a salient action (verb), but also predicts entities (nouns) associated with semantic roles and their locat…
Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang +3
Vision transformers (ViTs) have recently demonstrated state-of-the-art performance in a variety of vision tasks, replacing convolutional neural networks (CNNs). Meanwhile, since Vi…
Relational Self-Attention: What's Missing in Attention for Video Understanding
Manjin Kim, Heeseung Kwon, Chunyu Wang +2
Convolution has been arguably the most important feature transform for modern neural networks, leading to the advance of deep learning. Recent emergence of Transformer networks, wh…
Anonymization for Skeleton Action Recognition
Saemi Moon, Myeonghyeon Kim, Zhenyue Qin +2
Skeleton-based action recognition attracts practitioners and researchers due to the lightweight, compact nature of datasets. Compared with RGB-video-based action recognition, skele…
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
Minguk Kang, Woohyeon Shim, Minsu Cho +1
Conditional Generative Adversarial Networks (cGAN) generate realistic images by incorporating class information into GAN. While one of the most popular cGANs is an auxiliary classi…
FA-GAN: Feature-Aware GAN for Text to Image Synthesis
Eunyeong Jeon, Kunhee Kim, Daijin Kim
Text-to-image synthesis aims to generate a photo-realistic image from a given natural language description. Previous works have made significant progress with Generative Adversaria…
Semi-supervised Image Classification with Grad-CAM Consistency
Juyong Lee, Seunghyuk Cho
Consistency training, which exploits both supervised and unsupervised learning with different augmentations on image, is an effective method of utilizing unlabeled data in semi-sup…
Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes
Hyeongseok Son, Junyong Lee, Jonghyeop Lee +2
For the success of video deblurring, it is essential to utilize information from neighboring frames. Most state-of-the-art video deblurring methods adopt motion compensation betwee…
Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera
Hyomin Kim, Jungeon Kim, Hyeonseo Nam +2
This paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a…
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation
Hyunyoung Jung, Eunhyeok Park, Sungjoo Yoo
Self-supervised monocular depth estimation has been widely studied, owing to its practical importance and recent promising improvements. However, most works suffer from limited sup…
Iterative Filter Adaptive Network for Single Image Defocus Deblurring
Junyong Lee, Hyeongseok Son, Jaesung Rim +2
We propose a novel end-to-end learning-based approach for single image defocus deblurring. The proposed approach is equipped with a novel Iterative Filter Adaptive Network (IFAN) t…
UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation
Taehun Kim, Hyemin Lee, Daijin Kim
We propose Uncertainty Augmented Context Attention network (UACANet) for polyp segmentation which consider a uncertain area of the saliency map. We construct a modified version of…
StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation
Wonjong Jang, Gwangjin Ju, Yucheol Jung +3
We present a caricature generation framework based on shape and style manipulation using StyleGAN. Our framework, dubbed StyleCariGAN, automatically creates a realistic and detaile…
SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
Taehun Kim, Jinseong Kim, Daijin Kim
Semantic segmentation networks adopt transfer learning from image classification networks which occurs a shortage of spatial context information. For this reason, we propose Spatia…