5 papers
Multi-modal Knowledge Preserving Adapter for Embedding Backward Compatibility
Jaeseok Byun, Gukyeong Kwon, Han-Kai Hsu +4
Upgrading embedding models typically requires expensive database re-indexing, as new query embeddings are incompatible with existing database embeddings. While Backward Compatible…
An Efficient Post-hoc Framework for Reducing Task Discrepancy of Text Encoders for Composed Image Retrieval
Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim +2
Composed Image Retrieval (CIR) aims to retrieve a target image based on a reference image and conditioning text, enabling controllable image searches. The mainstream Zero-Shot (ZS)…
MAFA: Managing False Negatives for Vision-Language Pre-training
Jaeseok Byun, Dohoon Kim, Taesup Moon
We consider a critical issue of false negatives in Vision-Language Pre-training (VLP), a challenge that arises from the inherent many-to-many correspondence of image-text pairs in…
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training
Jaeseok Byun, Taebaek Hwang, Jianlong Fu +1
Most of the currently existing vision and language pre-training (VLP) methods have mainly focused on how to extract and align vision and text features. In contrast to the mainstrea…
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise
Jaeseok Byun, Sungmin Cha, Taesup Moon
We consider the challenging blind denoising problem for Poisson-Gaussian noise, in which no additional information about clean images or noise level parameters is available. Partic…