b'Sangdoo Yun'

research

∙ 07/04/2023

ProPILE: Probing Privacy Leakage in Large Language Models

The rapid advancement and widespread use of large language models (LLMs)...

0 Siwon Kim, et al. ∙

research

∙ 06/20/2023

Augmenting Sub-model to Improve Main Model

Image classification has improved with the development of training techn...

0 Byeongho Heo, et al. ∙

research

∙ 05/27/2023

MPCHAT: Towards Multimodal Persona-Grounded Conversation

In order to build self-consistent personalized dialogue agents, previous...

0 Jaewoo Ahn, et al. ∙

research

∙ 05/24/2023

Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models

Advances in Large Language Models (LLMs) have inspired a surge of resear...

0 Geewook Kim, et al. ∙

research

∙ 05/24/2023

Who Wrote this Code? Watermarking for Code Generation

Large language models for code have recently shown remarkable performanc...

0 Taehyun Lee, et al. ∙

research

∙ 04/21/2023

RoCOCO: Robust Benchmark MS-COCO to Stress-test Robustness of Image-Text Matching Models

Recently, large-scale vision-language pre-training models and visual sem...

0 Seulki Park, et al. ∙

research

∙ 04/10/2023

Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild

Recovering 3D human mesh in the wild is greatly challenging as in-the-wi...

0 Gyeongsik Moon, et al. ∙

research

∙ 03/30/2023

Neglected Free Lunch – Learning Image Classifiers Using Annotation Byproducts

Supervised learning of image classifiers distills human knowledge into a...

2 Dongyoon Han, et al. ∙

research

∙ 03/21/2023

CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion

This paper proposes a novel diffusion-based model, CompoDiff, for solvin...

0 Geonmo Gu, et al. ∙

research

∙ 03/20/2023

SeiT: Storage-Efficient Vision Training with Tokens Using 1 Storage

We need billion-scale images to achieve more generalizable and ground-br...

0 Song Park, et al. ∙

research

∙ 01/29/2023

Neural Relation Graph for Identifying Problematic Data

Diagnosing and cleaning datasets are crucial for building robust machine...

0 Jang-Hyun Kim, et al. ∙

research

∙ 12/08/2022

Group Generalized Mean Pooling for Vision Transformer

Vision Transformer (ViT) extracts the final representation from either c...

0 ByungSoo Ko, et al. ∙

research

∙ 08/21/2022

A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective

We propose the first unified theoretical analysis of mixed sample data a...

18 Chanwoo Park, et al. ∙

research

∙ 06/30/2022

Exploring Temporally Dynamic Data Augmentation for Video Recognition

Data augmentation has recently emerged as an essential component of mode...

0 Taeoh Kim, et al. ∙

research

∙ 05/30/2022

Dataset Condensation via Efficient Synthetic-Data Parameterization

The great success of machine learning with massive amounts of data comes...

44 Jang-Hyun Kim, et al. ∙

research

∙ 03/08/2022

Weakly Supervised Semantic Segmentation using Out-of-Distribution Data

Weakly supervised semantic segmentation (WSSS) methods are often built o...

7 Jungbeom Lee, et al. ∙

research

∙ 02/07/2022

Dataset Condensation with Contrastive Signals

Recent studies have demonstrated that gradient matching-based dataset sy...

0 Saehyung Lee, et al. ∙

research

∙ 12/01/2021

The Majority Can Help The Minority: Context-rich Minority Oversampling for Long-tailed Classification

The problem of class imbalanced data lies in that the generalization per...

0 Seulki Park, et al. ∙

research

∙ 11/30/2021

Donut: Document Understanding Transformer without OCR

Understanding document images (e.g., invoices) has been an important res...

0 Geewook Kim, et al. ∙

research

∙ 10/08/2021

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

Image-mixing augmentations (e.g., Mixup or CutMix), which typically mix ...

0 Joonhyun Jeong, et al. ∙

research

∙ 10/06/2021

Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective

Deep neural networks (DNNs) often rely on easy-to-learn discriminatory f...

6 Luca Scimeca, et al. ∙

research

∙ 10/03/2021

Progressive Transmission and Inference of Deep Learning Models

Modern image files are usually progressively transmitted and provide a p...

0 Youngsoo Lee, et al. ∙

research

∙ 07/28/2021

Normalization Matters in Weakly Supervised Object Localization

Weakly-supervised object localization (WSOL) enables finding an object u...

5 Jeesoo Kim, et al. ∙

research

∙ 03/30/2021

Rethinking Spatial Dimensions of Vision Transformers

Vision Transformer (ViT) extends the application range of transformers f...

6 Byeongho Heo, et al. ∙

research

∙ 01/13/2021

Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels

ImageNet has been arguably the most popular image classification benchma...

21 Sangdoo Yun, et al. ∙

research

∙ 12/07/2020

VideoMix: Rethinking Data Augmentation for Video Classification

State-of-the-art video action classifiers often suffer from overfitting....

0 Sangdoo Yun, et al. ∙

research

∙ 07/02/2020

ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network

This paper addresses representational bottleneck in a network and propos...

0 Dongyoon Han, et al. ∙

research

∙ 06/15/2020

Slowing Down the Weight Norm Increase in Momentum-based Optimizers

Normalization techniques, such as batch normalization (BN), have led to ...

16 Byeongho Heo, et al. ∙

research

∙ 03/09/2020

An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods

Despite apparent human-level performances of deep neural networks (DNN),...

13 Sanghyuk Chun, et al. ∙

research

∙ 10/15/2019

Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling

We propose a generic confidence-based approximation that can be plugged ...

16 YoungJoon Yoo, et al. ∙

research

∙ 10/07/2019

Learning De-biased Representations with Biased Representations

Many machine learning algorithms are trained and evaluated by splitting ...

25 Hyojin Bahng, et al. ∙

research

∙ 08/12/2019

Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold

This paper proposes a new high dimensional regression method by merging ...

8 YoungJoon Yoo, et al. ∙

research

∙ 06/15/2019

EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse

In this paper, we propose a new multi-scale face detector having an extr...

0 YoungJoon Yoo, et al. ∙

research

∙ 05/13/2019

CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features

Regional dropout strategies have been proposed to enhance the performanc...

0 Sangdoo Yun, et al. ∙

research

∙ 04/03/2019

Character Region Awareness for Text Detection

Scene text detection methods based on neural networks have emerged recen...

0 Youngmin Baek, et al. ∙

research

∙ 04/03/2019

What is wrong with scene text recognition model comparisons? dataset and model analysis

Many new proposals for scene text recognition (STR) models have been int...

0 Jeonghun Baek, et al. ∙

research

∙ 04/03/2019

A Comprehensive Overhaul of Feature Distillation

We investigate the design aspects of feature distillation methods achiev...

0 Byeongho Heo, et al. ∙

research

∙ 12/12/2018

Concentrated-Comprehensive Convolutions for lightweight semantic segmentation

The semantic segmentation requires a lot of computational cost. The dila...

8 Hyojin Park, et al. ∙

research

∙ 11/08/2018

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

An activation boundary for a neuron refers to a separating hyperplane th...

0 Byeongho Heo, et al. ∙

research

∙ 05/15/2018

Knowledge Distillation with Adversarial Samples Supporting Decision Boundary

Many recent works on knowledge distillation have provided ways to transf...

0 Byeongho Heo, et al. ∙

research

∙ 05/15/2018

Improving Knowledge Distillation with Supporting Adversarial Samples

Many recent works on knowledge distillation have provided ways to transf...

0 Byeongho Heo, et al. ∙

research

∙ 03/28/2018

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

We propose a new context-aware correlation filter based tracking framewo...

0 Jongwon Choi, et al. ∙

research

∙ 11/27/2017

Butterfly Effect: Bidirectional Control of Classification Performance by Small Additive Perturbation

This paper proposes a new algorithm for controlling classification resul...

0 YoungJoon Yoo, et al. ∙

research

∙ 03/31/2017

Unsupervised Holistic Image Generation from Key Local Patches

We introduce a new problem of generating an image based on a small numbe...

0 Donghoon Lee, et al. ∙

Sangdoo Yun

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