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cs.CV2025

Probabilistic Language-Image Pre-Training

Sanghyuk Chun, Wonjae Kim, Song Park +1

Vision-language models (VLMs) embed aligned image-text pairs into a joint space but often rely on deterministic embeddings, assuming a one-to-one correspondence between images and…

cs.CV2025

Emergence of Text Readability in Vision Language Models

Jaeyoo Park, Sanghyuk Chun, Wonjae Kim +2

We investigate how the ability to recognize textual content within images emerges during the training of Vision-Language Models (VLMs). Our analysis reveals a critical phenomenon:…

cs.CV2025

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)…

cs.CV2024

HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts

Wonjae Kim, Sanghyuk Chun, Taekyung Kim +2

In an era where the volume of data drives the effectiveness of self-supervised learning, the specificity and clarity of data semantics play a crucial role in model training. Addres…

cs.CV2024

CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion

Geonmo Gu, Sanghyuk Chun, Wonjae Kim +3

This paper proposes a novel diffusion-based model, CompoDiff, for solving zero-shot Composed Image Retrieval (ZS-CIR) with latent diffusion. This paper also introduces a new synthe…