2 citations · 2 across the 7 of their papers we have counts for
7 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,…
ASemConsist: Adaptive Semantic Feature Control for Training-Free Identity-Consistent Generation
Shin Seong Kim, Minjung Shin, Hyunin Cho +1
Recent text-to-image diffusion models have significantly improved visual quality and text alignment. However, generating a sequence of images while preserving consistent character…
MVCustom: Multi-View Customized Diffusion via Geometric Latent Rendering and Completion
Minjung Shin, Hyunin Cho, Sooyeon Go +2
Multi-view generation with camera pose control and prompt-based customization are both essential elements for achieving controllable generative models. However, existing multi-view…
Eye-for-an-eye: Appearance Transfer with Semantic Correspondence in Diffusion Models
Sooyeon Go, Kyungmook Choi, Minjung Shin +1
As pre-trained text-to-image diffusion models have become a useful tool for image synthesis, people want to specify the results in various ways. This paper tackles training-free ap…
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…
BallGAN: 3D-aware Image Synthesis with a Spherical Background
Minjung Shin, Yunji Seo, Jeongmin Bae +4
3D-aware GANs aim to synthesize realistic 3D scenes such that they can be rendered in arbitrary perspectives to produce images. Although previous methods produce realistic images,…
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…