Abstract
We investigate how data fidelity and diversity jointly affect visual recognition performance. Through systematic synthetic data curation, we demonstrate training-free improvements and show that synthetic data can effectively complement real data to enhance recognition systems.
Authors
Disheng Liu, Tuo Liang, Yu Yin