1 citations · 1 across the 4 of their papers we have counts for
4 papers
Efficiency without Compromise: CLIP-aided Text-to-Image GANs with Increased Diversity
Yuya Kobayashi, Yuhta Takida, Takashi Shibuya +1
Recently, Generative Adversarial Networks (GANs) have been successfully scaled to billion-scale large text-to-image datasets. However, training such models entails a high training…
Forging and Removing Latent-Noise Diffusion Watermarks Using a Single Image
Anubhav Jain, Yuya Kobayashi, Naoki Murata +6
Watermarking techniques are vital for protecting intellectual property and preventing fraudulent use of media. Most previous watermarking schemes designed for diffusion models embe…
DisMix: Disentangling Mixtures of Musical Instruments for Source-level Pitch and Timbre Manipulation
Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi +8
Existing work on pitch and timbre disentanglement has been mostly focused on single-instrument music audio, excluding the cases where multiple instruments are presented. To fill th…
On the Language Encoder of Contrastive Cross-modal Models
Mengjie Zhao, Junya Ono, Zhi Zhong +7
Contrastive cross-modal models such as CLIP and CLAP aid various vision-language (VL) and audio-language (AL) tasks. However, there has been limited investigation of and improvemen…