1 citations · 2 across the 8 of their papers we have counts for
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Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation
Jungmin Ko, Jungwon Park, Jimyeong Kim +3
Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object or attribute remains a fund…
ReFlex: Text-Guided Editing of Real Images in Rectified Flow via Mid-Step Feature Extraction and Attention Adaptation
Jimyeong Kim, Jungwon Park, Yeji Song +2
Rectified Flow text-to-image models surpass diffusion models in image quality and text alignment, but adapting ReFlow for real-image editing remains challenging. We propose a new r…
Selectively Informative Description can Reduce Undesired Embedding Entanglements in Text-to-Image Personalization
Jimyeong Kim, Jungwon Park, Wonjong Rhee
In text-to-image personalization, a timely and crucial challenge is the tendency of generated images overfitting to the biases present in the reference images. We initiate our stud…
Harmonizing Visual and Textual Embeddings for Zero-Shot Text-to-Image Customization
Yeji Song, Jimyeong Kim, Wonhark Park +3
In a surge of text-to-image (T2I) models and their customization methods that generate new images of a user-provided subject, current works focus on alleviating the costs incurred…
Enhancing Contrastive Learning with Efficient Combinatorial Positive Pairing
Jaeill Kim, Duhun Hwang, Eunjung Lee +3
In the past few years, contrastive learning has played a central role for the success of visual unsupervised representation learning. Around the same time, high-performance non-con…