517 citations · 622 across the 5 of their papers we have counts for
5 papers
Generative Neural Fields by Mixtures of Neural Implicit Functions
Tackgeun You, Mijeong Kim, Jungtaek Kim +1
We propose a novel approach to learning the generative neural fields represented by linear combinations of implicit basis networks. Our algorithm learns basis networks in the form…
Domain-Specific Batch Normalization for Unsupervised Domain Adaptation
Woong-Gi Chang, Tackgeun You, Seonguk Seo +2
We propose a novel unsupervised domain adaptation framework based on domain-specific batch normalization in deep neural networks. We aim to adapt to both domains by specializing ba…
Bayesian Optimization with Approximate Set Kernels
Jungtaek Kim, Michael McCourt, Tackgeun You +2
We propose a practical Bayesian optimization method over sets, to minimize a black-box function that takes a set as a single input. Because set inputs are permutation-invariant, tr…
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization
Hyeonwoo Noh, Tackgeun You, Jonghwan Mun +1
Overfitting is one of the most critical challenges in deep neural networks, and there are various types of regularization methods to improve generalization performance. Injecting n…
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network
Seunghoon Hong, Tackgeun You, Suha Kwak +1
We propose an online visual tracking algorithm by learning discriminative saliency map using Convolutional Neural Network (CNN). Given a CNN pre-trained on a large-scale image repo…