Search Results for author: Jongwon Choi

Found 14 papers, 4 papers with code

Adaptive Attention Link-based Regularization for Vision Transformers

no code implementations25 Nov 2022 Heegon Jin, Jongwon Choi

Although transformer networks are recently employed in various vision tasks with outperforming performance, extensive training data and a lengthy training time are required to train a model to disregard an inductive bias.

Inductive Bias

A high performance globally exponentially stable sensorless observer for the IPMSM: Theoretical and experimental results

no code implementations1 Oct 2022 Bowen Yi, Romeo Ortega, Jongwon Choi, Kwanghee Nam

In a recent paper [18] the authors proposed the first solution to the problem of designing a {\em globally exponentially stable} (GES) flux observer for the interior permanent magnet synchronous motor.


FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations

no code implementations7 Feb 2022 Yonghyun Jeong, Doyeon Kim, Youngmin Ro, Jongwon Choi

For experiments, we design new test scenarios varying from the training settings in GAN models, color manipulations, and object categories.

DeepFake Detection Face Swapping

Self-supervised GAN Detector

no code implementations12 Nov 2021 Yonghyun Jeong, Doyeon Kim, Pyounggeon Kim, Youngmin Ro, Jongwon Choi

Although the recent advancement in generative models brings diverse advantages to society, it can also be abused with malicious purposes, such as fraud, defamation, and fake news.

Observations on K-image Expansion of Image-Mixing Augmentation for Classification

no code implementations8 Oct 2021 JoonHyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi

Image-mixing augmentations (e. g., Mixup and CutMix), which typically involve mixing two images, have become the de-facto training techniques for image classification.

Adversarial Robustness Classification +1

MToFNet: Object Anti-Spoofing with Mobile Time-of-Flight Data

no code implementations6 Oct 2021 Yonghyun Jeong, Doyeon Kim, Jaehyeon Lee, Minki Hong, Solbi Hwang, Jongwon Choi

When images are recaptured on display screens, various patterns differing by the screens as known as the moir\'e patterns can be also captured in spoof images.

BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection

no code implementations16 Aug 2021 Yonghyun Jeong, Doyeon Kim, Seungjai Min, Seongho Joe, Youngjune Gwon, Jongwon Choi

The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of those images.

DeepFake Detection Face Swapping

VaB-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning

no code implementations CVPR 2021 Jongwon Choi, Kwang Moo Yi, Ji-Hoon Kim, Jinho Choo, Byoungjip Kim, Jin-Yeop Chang, Youngjune Gwon, Hyung Jin Chang

We show that our method can be applied to classification tasks on multiple different datasets -- including one that is a real-world dataset with heavy data imbalance -- significantly outperforming the state of the art.

Active Learning

Cross-modal Variational Auto-encoder with Distributed Latent Spaces and Associators

no code implementations30 May 2019 Dae Ung Jo, ByeongJu Lee, Jongwon Choi, Haanju Yoo, Jin Young Choi

We formulate the cross-modal association in Bayesian inference framework realized by a deep neural network with multiple variational auto-encoders and variational associators.

Association Bayesian Inference

Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification

1 code implementation18 Jan 2019 Youngmin Ro, Jongwon Choi, Dae Ung Jo, Byeongho Heo, Jongin Lim, Jin Young Choi

Our strategy alleviates the problem of gradient vanishing in low-level layers and robustly trains the low-level layers to fit the ReID dataset, thereby increasing the performance of ReID tasks.

Person Re-Identification Pose Estimation

Context-aware Deep Feature Compression for High-speed Visual Tracking

1 code implementation CVPR 2018 Jongwon Choi, Hyung Jin Chang, Tobias Fischer, Sangdoo Yun, Kyuewang Lee, Jiyeoup Jeong, Yiannis Demiris, Jin Young Choi

We propose a new context-aware correlation filter based tracking framework to achieve both high computational speed and state-of-the-art performance among real-time trackers.

Denoising Feature Compression +2

Attentional Correlation Filter Network for Adaptive Visual Tracking

1 code implementation IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 Jongwon Choi, Hyung Jin Chang, Sangdoo Yun, Tobias Fischer, Yiannis Demiris, Jin Young Choi

We propose a new tracking framework with an attentional mechanism that chooses a subset of the associated correlation filters for increased robustness and computational efficiency.

Visual Object Tracking Visual Tracking

Action-Decision Networks for Visual Tracking With Deep Reinforcement Learning

1 code implementation CVPR 2017 Sangdoo Yun, Jongwon Choi, Youngjoon Yoo, Kimin Yun, Jin Young Choi

In contrast to the existing trackers using deep networks, the proposed tracker is designed to achieve a light computation as well as satisfactory tracking accuracy in both location and scale.

reinforcement-learning Reinforcement Learning (RL) +1

Visual Tracking Using Attention-Modulated Disintegration and Integration

no code implementations CVPR 2016 Jongwon Choi, Hyung Jin Chang, Jiyeoup Jeong, Yiannis Demiris, Jin Young Choi

In this paper, we present a novel attention-modulated visual tracking algorithm that decomposes an object into multiple cognitive units, and trains multiple elementary trackers in order to modulate the distribution of attention according to various feature and kernel types.

Visual Tracking

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