Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR1.2k papers
- The University of TokyoJP1.2k papers
- Panjab UniversityIN1.2k papers
- Centre National de la Recherche ScientifiqueFR1.1k papers
- Sungkyunkwan UniversityKR1.1k papers
- Wayne State UniversityUS990 papers
- Korea UniversityKR986 papers
- National Taiwan UniversityTW970 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT941 papers
- Kyungpook National UniversityKR930 papers
- University of Science and Technology of ChinaCN930 papers
- University of Tennessee at KnoxvilleUS920 papers
17 papers · 2 filters
Fixed-length Bit-string Representation of Fingerprint by Normalized Local Structures
Jun Beom Kho, Andrew B. J. Teoh, Wonjune Lee +1
In this paper, we propose a method to represent a fingerprint image by an ordered, fixed-length bit-string providing improved accuracy performance, faster matching time and compres…
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Seonghyeon Nam, Yunji Kim, Seon Joo Kim
This paper addresses the problem of manipulating images using natural language description. Our task aims to semantically modify visual attributes of an object in an image accordin…
Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolutional Neural Networks
Sung Ho Kang, Kiwan Jeon, Hak-Jin Kim +2
Background: Three-dimensional (3D) cephalometric analysis using computerized tomography data has been rapidly adopted for dysmorphosis and anthropometry. Several different approach…
Perfect match: Improved cross-modal embeddings for audio-visual synchronisation
Soo-Whan Chung, Joon Son Chung, Hong-Goo Kang
This paper proposes a new strategy for learning powerful cross-modal embeddings for audio-to-video synchronization. Here, we set up the problem as one of cross-modal retrieval, whe…
MAMNet: Multi-path Adaptive Modulation Network for Image Super-Resolution
Jun-Hyuk Kim, Jun-Ho Choi, Manri Cheon +1
In recent years, single image super-resolution (SR) methods based on deep convolutional neural networks (CNNs) have made significant progress. However, due to the non-adaptive natu…
Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification
Cheng-Yaw Low, Jaewoo Park, Andrew Beng-Jin Teoh
Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pa…
Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim, Stephen Lin, Sangryul Jeon +2
We present recurrent transformer networks (RTNs) for obtaining dense correspondences between semantically similar images. Our networks accomplish this through an iterative process…
Depth Reconstruction of Translucent Objects from a Single Time-of-Flight Camera using Deep Residual Networks
Seongjong Song, Hyunjung Shim
We propose a novel approach to recovering the translucent objects from a single time-of-flight (ToF) depth camera using deep residual networks. When recording the translucent objec…
Generative adversarial network-based image super-resolution using perceptual content losses
Manri Cheon, Jun-Hyuk Kim, Jun-Ho Choi +1
In this paper, we propose a deep generative adversarial network for super-resolution considering the trade-off between perception and distortion. Based on good performance of a rec…
PARN: Pyramidal Affine Regression Networks for Dense Semantic Correspondence
Sangryul Jeon, Seungryong Kim, Dongbo Min +1
This paper presents a deep architecture for dense semantic correspondence, called pyramidal affine regression networks (PARN), that estimates locally-varying affine transformation…
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously
Kyungjune Baek, Duhyeon Bang, Hyunjung Shim
We propose a novel framework for simultaneously generating and manipulating the face images with desired attributes. While the state-of-the-art attribute editing technique has achi…
Generative Adversarial Networks for Unsupervised Object Co-localization
Junsuk Choe, Joo Hyun Park, Hyunjung Shim
This paper introduces a novel approach for unsupervised object co-localization using Generative Adversarial Networks (GANs). GAN is a powerful tool that can implicitly learn unknow…
Discriminator Feature-based Inference by Recycling the Discriminator of GANs
Duhyeon Bang, Seoungyoon Kang, Hyunjung Shim
Generative adversarial networks (GANs)successfully generate high quality data by learning amapping from a latent vector to the data. Various studies assert that the latent space of…
MGGAN: Solving Mode Collapse using Manifold Guided Training
Duhyeon Bang, Hyunjung Shim
Mode collapse is a critical problem in training generative adversarial networks. To alleviate mode collapse, several recent studies introduce new objective functions, network archi…
EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth from Light Field Images
Changha Shin, Hae-Gon Jeon, Youngjin Yoon +2
Light field cameras capture both the spatial and the angular properties of light rays in space. Due to its property, one can compute the depth from light fields in uncontrolled lig…
Calcium Removal From Cardiac CT Images Using Deep Convolutional Neural Network
Siming Yan, Feng Shi, Yuhua Chen +5
Coronary calcium causes beam hardening and blooming artifacts on cardiac computed tomography angiography (CTA) images, which lead to overestimation of lumen stenosis and reduction…
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang, Hyunjung Shim
Despite the success of generative adversarial networks (GANs) for image generation, the trade-off between visual quality and image diversity remains a significant issue. This paper…