Uncertainty Estimates in Deep Generative Models Using Gaussian Processes. - Kai Katsumata; Ryoga Kobayashi (ISVC (1), 2020)

Semantic Image Synthesis from Inaccurate and Coarse Masks. - Kai Katsumata; Hideki Nakayama (ICASSP, 2021)

Open-Set Domain Generalization VIA Metric Learning. - Kai Katsumata; Ikki Kishida; Ayako Amma; Hideki Nakayama (ICIP, 2021)

OSSGAN: Open-Set Semi-Supervised Image Generation. - Kai Katsumata; Duc Minh Vo; Hideki Nakayama (CVPR, 2022)

Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space. - Kai Katsumata; Duc Minh Vo; Bei Liu 001; Hideki Nakayama (CoRR, 2023)

Revisiting Latent Space of GAN Inversion for Real Image Editing. - Kai Katsumata; Duc Minh Vo; Bei Liu 001; Hideki Nakayama (CoRR, 2023)

An Efficient 3D Gaussian Representation for Monocular/Multi-view Dynamic Scenes. - Kai Katsumata; Duc Minh Vo; Hideki Nakayama (CoRR, 2023)

A Compact Dynamic 3D Gaussian Representation for Real-Time Dynamic View Synthesis. - Kai Katsumata; Duc Minh Vo; Hideki Nakayama (ECCV (86), 2024)

Large Language Models for Human-Like Autonomous Driving: A Survey. - Yun Li; Kai Katsumata; Ehsan Javanmardi; Manabu Tsukada (ITSC, 2024)

Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data. - Kai Katsumata; Duc Minh Vo; Tatsuya Harada; Hideki Nakayama (WACV, 2024)

Revisiting Latent Space of GAN Inversion for Robust Real Image Editing. - Kai Katsumata; Duc Minh Vo; Bei Liu 001; Hideki Nakayama (WACV, 2024)

Label Augmentation as Inter-class Data Augmentation for Conditional Image Synthesis with Imbalanced Data. - Kai Katsumata; Duc Minh Vo; Hideki Nakayama (WACV, 2024)