The author proposes a novel pipeline utilizing a diffusion model to address long-tail recognition challenges, achieving state-of-the-art results on various datasets. The approach involves training the diffusion model on the original dataset for sample generation and subsequent classifier training.
Long-tail recognition challenges can be addressed effectively by utilizing a diffusion model trained on the original dataset for sample generation, leading to improved classifier performance.
새로운 파이프라인을 제안하여 장단기 인식을 위한 확산 모델을 유용하게 만드는 방법