5 papers
Reference-Free Image Quality Assessment for Virtual Try-On via Human Feedback
Yuki Hirakawa, Takashi Wada, Ryotaro Shimizu +6
As virtual try-on (VTON) systems become increasingly important in fashion e-commerce, there is a growing need for reliable reference-free evaluation methods, since ground-truth ima…
Listening without Looking: Modality Bias in Audio-Visual Captioning
Yuchi Ishikawa, Toranosuke Manabe, Tatsuya Komatsu +1
Audio-visual captioning aims to generate holistic scene descriptions by jointly modeling sound and vision. While recent methods have improved performance through sophisticated moda…
Language-Guided Contrastive Audio-Visual Masked Autoencoder with Automatically Generated Audio-Visual-Text Triplets from Videos
Yuchi Ishikawa, Shota Nakada, Hokuto Munakata +3
In this paper, we propose Language-Guided Contrastive Audio-Visual Masked Autoencoders (LG-CAV-MAE) to improve audio-visual representation learning. LG-CAV-MAE integrates a pretrai…
Pre-training with Synthetic Patterns for Audio
Yuchi Ishikawa, Tatsuya Komatsu, Yoshimitsu Aoki
In this paper, we propose to pre-train audio encoders using synthetic patterns instead of real audio data. Our proposed framework consists of two key elements. The first one is Mas…
Data Collection-free Masked Video Modeling
Yuchi Ishikawa, Masayoshi Kondo, Yoshimitsu Aoki
Pre-training video transformers generally requires a large amount of data, presenting significant challenges in terms of data collection costs and concerns related to privacy, lice…