3 papers
cs.CV2025
Uniformity First: Uniformity-aware Test-time Adaptation of Vision-language Models against Image Corruption
Kazuki Adachi, Shin'ya Yamaguchi, Tomoki Hamagami
Pre-trained vision-language models such as contrastive language-image pre-training (CLIP) have demonstrated a remarkable generalizability, which has enabled a wide range of applica…
cs.LG2025
Test-time Adaptation for Regression by Subspace Alignment
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai +1
This paper investigates test-time adaptation (TTA) for regression, where a regression model pre-trained in a source domain is adapted to an unknown target distribution with unlabel…
cs.CV2024
Latent Denoising Diffusion GAN: Faster sampling, Higher image quality
Luan Thanh Trinh, Tomoki Hamagami
Diffusion models are emerging as powerful solutions for generating high-fidelity and diverse images, often surpassing GANs under many circumstances. However, their slow inference s…