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cs.CV2026

Region-Wise Correspondence Prediction between Manga Line Art Images

Yingxuan Li, Jiafeng Mao, Qianru Qiu +1

Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks such as line art colorization an…

cs.CV2025

RouteExtract: A Modular Pipeline for Extracting Routes from Paper Maps

Bjoern Kremser, Yusuke Matsui

Paper maps remain widely used for hiking and sightseeing because they contain curated trails and locally relevant annotations that are often missing from digital navigation applica…

cs.CV2024

High-Frequency Anti-DreamBooth: Robust Defense against Personalized Image Synthesis

Takuto Onikubo, Yusuke Matsui

Recently, text-to-image generative models have been misused to create unauthorized malicious images of individuals, posing a growing social problem. Previous solutions, such as Ant…

cs.CV2024

ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer

Hiroki Azuma, Yusuke Matsui, Atsuto Maki

Deep learning models achieve high accuracy in segmentation tasks among others, yet domain shift often degrades the models' performance, which can be critical in real-world scenario…

cs.CV2024

Revisiting Relevance Feedback for CLIP-based Interactive Image Retrieval

Ryoya Nara, Yu-Chieh Lin, Yuji Nozawa +4

Many image retrieval studies use metric learning to train an image encoder. However, metric learning cannot handle differences in users' preferences, and requires data to train an…

cs.CV2024

Adversarial Doodles: Interpretable and Human-drawable Attacks Provide Describable Insights

Ryoya Nara, Yusuke Matsui

DNN-based image classifiers are susceptible to adversarial attacks. Most previous adversarial attacks do not have clear patterns, making it difficult to interpret attacks' results…