5 papers
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts
Jiaxuan Li, Duc Minh Vo, Hideki Nakayama
Bias mitigation in image classification has been widely researched, and existing methods have yielded notable results. However, most of these methods implicitly assume that a given…
Revisiting Latent Space of GAN Inversion for Real Image Editing
Kai Katsumata, Duc Minh Vo, Bei Liu +1
The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quali…
Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data
Kai Katsumata, Duc Minh Vo, Tatsuya Harada +1
Label-noise or curated unlabeled data is used to compensate for the assumption of clean labeled data in training the conditional generative adversarial network; however, satisfying…
Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space
Kai Katsumata, Duc Minh Vo, Bei Liu +1
The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quali…
A-CAP: Anticipation Captioning with Commonsense Knowledge
Duc Minh Vo, Quoc-An Luong, Akihiro Sugimoto +1
Humans possess the capacity to reason about the future based on a sparse collection of visual cues acquired over time. In order to emulate this ability, we introduce a novel task c…