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haoweiz

2 accepted papers

2024

DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization

NeurIPS 2024poster

Diffusion models have achieved remarkable progress in the field of image generation due to their outstanding capabilities. However, these models require substantial computing resources because of the multi-step denoising process during inference. While traditional pruning methods have been employed…

Cited by 2SourcePDFScholar
2024

Distribution-Aware Data Expansion with Diffusion Models

NeurIPS 2024poster

The scale and quality of a dataset significantly impact the performance of deep models. However, acquiring large-scale annotated datasets is both a costly and time-consuming endeavor. To address this challenge, dataset expansion technologies aim to automatically augment datasets, unlocking the full…