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Shoichiro Takeda

7 accepted papers

2026

Difference Vector Equalization for Robust Fine-tuning of Vision-Language Models

AAAI 2026technical

Contrastive pre-trained vision-language models, such as CLIP, demonstrate strong generalization abilities in zero-shot classification by leveraging embeddings extracted from image and text encoders. This paper aims to robustly fine-tune these vision-language models on in-distribution (ID) data witho

Cited by 0SourcePDFScholar
2023

Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff

ICCV 2023poster

This paper addresses the tradeoff between standard accuracy on clean examples and robustness against adversarial examples in deep neural networks (DNNs). Although adversarial training (AT) improves robustness, it degrades the standard accuracy, thus yielding the tradeoff. To mitigate this tradeoff…

Cited by 7PDFScholar
2022

Bilateral Video Magnification Filter

CVPR 2022poster

Eulerian video magnification (EVM) has progressed to magnify subtle motions with a target frequency even under the presence of large motions of objects. However, existing EVM methods often fail to produce desirable results in real videos due to (1) mis-extracting subtle motions with a non-target fre…

Cited by 11PDFScholar
2019

Video Magnification in the Wild Using Fractional Anisotropy in Temporal Distribution

CVPR 2019poster

Video magnification methods can magnify and reveal subtle changes invisible to the naked eye. However, in such subtle changes, meaningful ones caused by physical and natural phenomena are mixed with non-meaningful ones caused by photographic noise. Therefore, current methods often produce noisy and…

Cited by 32PDFScholar
2018

Jerk-Aware Video Acceleration Magnification

CVPR 2018poster

Video magnification reveals subtle changes invisible to the naked eye, but such tiny yet meaningful changes are often hidden under large motions: small deformation of the muscles in doing sports, or tiny vibrations of strings in ukulele playing. For magnifying subtle changes under large motions, vid…

Cited by 42SourcePDFScholar