3 papers
cs.CV2026
Can We Change the Stroke Size for Easier Diffusion?
Yunwei Bai, Ying Kiat Tan, Yao Shu +1
Diffusion models can be challenged in the low signal-to-noise regime, where they have to make pixel-level predictions despite the presence of high noise. The geometric intuition is…
cs.CV2026
1S-DAug: One-Shot Data Augmentation for Robust Few-Shot Generalization
Yunwei Bai, Ying Kiat Tan, Yao Shu +1
Few-shot learning (FSL) challenges model generalization to novel classes based on just a few shots of labeled examples, a testbed where traditional test-time augmentations fail to…
cs.CV2024
FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation
Yunwei Bai, Ying Kiat Tan, Shiming Chen +2
Few-shot learning (FSL) commonly requires a model to identify images (queries) that belong to classes unseen during training, based on a few labelled samples of the new classes (su…