Hyunwoo J. Kim

research

∙ 09/06/2023

Distribution-Aware Prompt Tuning for Vision-Language Models

Pre-trained vision-language models (VLMs) have shown impressive performa...

0 Eulrang Cho, et al. ∙

research

∙ 08/29/2023

Read-only Prompt Optimization for Vision-Language Few-shot Learning

In recent years, prompt tuning has proven effective in adapting pre-trai...

0 Dongjun Lee, et al. ∙

research

∙ 08/23/2023

Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification

Interpretability is a crucial factor in building reliable models for var...

0 Injae Kim, et al. ∙

research

∙ 08/23/2023

Semantic-Aware Implicit Template Learning via Part Deformation Consistency

Learning implicit templates as neural fields has recently shown impressi...

0 Sihyeon Kim, et al. ∙

research

∙ 08/18/2023

Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models

Video Question Answering (VideoQA) is a challenging task that entails co...

0 Dohwan Ko, et al. ∙

research

∙ 03/29/2023

Self-positioning Point-based Transformer for Point Cloud Understanding

Transformers have shown superior performance on various computer vision ...

0 Jinyoung Park, et al. ∙

research

∙ 03/23/2023

MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models

Foundation models have shown outstanding performance and generalization ...

0 Dohwan Ko, et al. ∙

research

∙ 03/20/2023

k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment

The application of modern machine learning to retinal image analyses off...

0 Minkyu Jeon, et al. ∙

research

∙ 03/05/2023

Semantic-aware Occlusion Filtering Neural Radiance Fields in the Wild

We present a learning framework for reconstructing neural scene represen...

0 Jaewon Lee, et al. ∙

research

∙ 02/03/2023

Robust Camera Pose Refinement for Multi-Resolution Hash Encoding

Multi-resolution hash encoding has recently been proposed to reduce the ...

0 Hwan Heo, et al. ∙

research

∙ 02/02/2023

Domain Generalization Emerges from Dreaming

Recent studies have proven that DNNs, unlike human vision, tend to explo...

0 Hwan Heo, et al. ∙

research

∙ 12/02/2022

Relation-aware Language-Graph Transformer for Question Answering

Question Answering (QA) is a task that entails reasoning over natural la...

0 Jinyoung Park, et al. ∙

research

∙ 10/15/2022

Invertible Monotone Operators for Normalizing Flows

Normalizing flows model probability distributions by learning invertible...

0 Byeongkeun Ahn, et al. ∙

research

∙ 10/14/2022

TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers

Mixup is a commonly adopted data augmentation technique for image classi...

1 Hyeong Kyu Choi, et al. ∙

research

∙ 10/13/2022

SageMix: Saliency-Guided Mixup for Point Clouds

Data augmentation is key to improving the generalization ability of deep...

0 Sanghyeok Lee, et al. ∙

research

∙ 06/29/2022

Deformable Graph Transformer

Transformer-based models have been widely used and achieved state-of-the...

6 Jinyoung Park, et al. ∙

research

∙ 06/09/2022

Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction

Graph Neural Networks (GNNs) have been widely applied to various fields ...

0 Seongjun Yun, et al. ∙

research

∙ 04/11/2022

Consistency Learning via Decoding Path Augmentation for Transformers in Human Object Interaction Detection

Human-Object Interaction detection is a holistic visual recognition task...

1 Jihwan Park, et al. ∙

research

∙ 03/31/2022

Video-Text Representation Learning via Differentiable Weak Temporal Alignment

Learning generic joint representations for video and text by a supervise...

0 Dohwan Ko, et al. ∙

research

∙ 03/26/2022

Metropolis-Hastings Data Augmentation for Graph Neural Networks

Graph Neural Networks (GNNs) often suffer from weak-generalization due t...

46 Hyeonjin Park, et al. ∙

research

∙ 01/05/2022

Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones

We aim to detect and identify multiple objects using multiple cameras an...

23 Chongkeun Paik, et al. ∙

research

∙ 12/29/2021

Deformable Graph Convolutional Networks

Graph neural networks (GNNs) have significantly improved the representat...

0 Jinyoung Park, et al. ∙

research

∙ 10/11/2021

Point Cloud Augmentation with Weighted Local Transformations

Despite the extensive usage of point clouds in 3D vision, relatively lim...

0 Sihyeon Kim, et al. ∙

research

∙ 06/11/2021

Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs

Graph Neural Networks (GNNs) have been widely applied to various fields ...

0 Seongjun Yun, et al. ∙

research

∙ 04/28/2021

HOTR: End-to-End Human-Object Interaction Detection with Transformers

Human-Object Interaction (HOI) detection is a task of identifying "a set...

0 Bumsoo Kim, et al. ∙

research

∙ 03/01/2021

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning

In recent years, graph neural networks (GNNs) have been widely adopted i...

0 Dasol Hwang, et al. ∙

research

∙ 10/20/2020

Robust Neural Networks inspired by Strong Stability Preserving Runge-Kutta methods

Deep neural networks have achieved state-of-the-art performance in a var...

0 Byungjoo Kim, et al. ∙

research

∙ 07/16/2020

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs

Graph neural networks have shown superior performance in a wide range of...

26 Dasol Hwang, et al. ∙

research

∙ 11/29/2019

Unpaired Image Translation via Adaptive Convolution-based Normalization

Disentangling content and style information of an image has played an im...

4 Wonwoong Cho, et al. ∙

research

∙ 04/07/2019

ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification

Deep convolutional neural networks have achieved remarkable success in c...

0 Yunyang Xiong, et al. ∙

research

∙ 11/20/2017

Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective

Recent results in coupled or temporal graphical models offer schemes for...

0 Ronak Mehta, et al. ∙

Hyunwoo J. Kim

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