10 citations · 19 across the 9 of their papers we have counts for
11 papers
BindEdit: Taming Attention Leakage for Precise Multi-Object Image Editing
Chaewon Park, Soyoon Lee, Naeun Lee +3
Real image editing enables precise manipulation of visual content, yet existing methods often fail in complex multi-object scenarios, causing semantic blending, object duplication,…
Exploiting Domain Properties in Language-Driven Domain Generalization for Semantic Segmentation
Seogkyu Jeon, Kibeom Hong, Hyeran Byun
Recent domain generalized semantic segmentation (DGSS) studies have achieved notable improvements by distilling semantic knowledge from Vision-Language Models (VLMs). However, they…
Improving Diversity in Zero-Shot GAN Adaptation with Semantic Variations
Seogkyu Jeon, Bei Liu, Pilhyeon Lee +3
Training deep generative models usually requires a large amount of data. To alleviate the data collection cost, the task of zero-shot GAN adaptation aims to reuse well-trained gene…
AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networks
Kibeom Hong, Seogkyu Jeon, Junsoo Lee +6
To deliver the artistic expression of the target style, recent studies exploit the attention mechanism owing to its ability to map the local patches of the style image to the corre…
Source-free Subject Adaptation for EEG-based Visual Recognition
Pilhyeon Lee, Seogkyu Jeon, Sunhee Hwang +2
This paper focuses on subject adaptation for EEG-based visual recognition. It aims at building a visual stimuli recognition system customized for the target subject whose EEG sampl…
Exploiting Domain Transferability for Collaborative Inter-level Domain Adaptive Object Detection
Mirae Do, Seogkyu Jeon, Pilhyeon Lee +3
Domain adaptation for object detection (DAOD) has recently drawn much attention owing to its capability of detecting target objects without any annotations. To tackle the problem,…
Inter-subject Contrastive Learning for Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee, Sunhee Hwang, Jewook Lee +3
This paper tackles the problem of subject adaptive EEG-based visual recognition. Its goal is to accurately predict the categories of visual stimuli based on EEG signals with only a…
Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee, Sunhee Hwang, Seogkyu Jeon +1
This paper focuses on EEG-based visual recognition, aiming to predict the visual object class observed by a subject based on his/her EEG signals. One of the main challenges is the…
Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization
Seogkyu Jeon, Kibeom Hong, Pilhyeon Lee +2
Domain generalization aims to enhance the model robustness against domain shift without accessing the target domain. Since the available source domains for training are limited, re…
Domain-Aware Universal Style Transfer
Kibeom Hong, Seogkyu Jeon, Huan Yang +2
Style transfer aims to reproduce content images with the styles from reference images. Existing universal style transfer methods successfully deliver arbitrary styles to original i…
Continuous Face Aging Generative Adversarial Networks
Seogkyu Jeon, Pilhyeon Lee, Kibeom Hong +1
Face aging is the task aiming to translate the faces in input images to designated ages. To simplify the problem, previous methods have limited themselves only able to produce disc…