Publications

Kai Katsumata, Duc Minh Vo, Tatsuya Harada, Hideki Nakayama (2024). Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Kai Katsumata, Duc Minh Vo, Bei Liu, Hideki Nakayama (2024). Revisiting Latent Space of GAN Inversion for Real Image Editing. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Kai Katsumata, Duc Minh Vo, Hideki Nakayama (2024). Label Augmentation as Inter-class Data Augmentation for Conditional Image Synthesis with Imbalanced Data. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

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

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Kai Katsumata, Duc Minh Vo, Bei Liu, Hideki Nakayama (2023). Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space. arXiv preprint arXiv:2306.00241.

Kai Katsumata, Duc Minh Vo, Hideki Nakayama (2023). An Efficient 3D Gaussian Representation for Monocular/Multi-view Dynamic Scenes. arXiv preprint arXiv:2311.12897.

Kai Katsumata, Duc Minh Vo, Hideki Nakayama (2022). OSSGAN: Open-Set Semi-Supervised Image Generation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Kai Katsumata, Hideki Nakayama (2021). Semantic Image Synthesis from Inaccurate and Coarse Masks. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Kai Katsumata, Ikki Kishida, Ayako Amma, Hideki Nakayama (2021). Open-set domain generalization via metric learning. IEEE International Conference on Image Processing (ICIP).

Kai Katsumata, Ryoga Kobayashi (2020). Uncertainty Estimates in Deep Generative Models Using Gaussian Processes. International Symposium on Visual Computing.