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Zhengyang Yu

2 accepted papers

2024

DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models

NeurIPS 2024poster

Recent text-to-image (T2I) personalization methods have shown great premise in teaching a diffusion model user-specified concepts given a few images for reusing the acquired concepts in a novel context. With massive efforts being dedicated to personalized generation, a promising extension is persona…

2024

IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models

ICLR 2024poster

We present a diffusion-based image morphing approach with perceptually-uniform sampling (IMPUS) that produces smooth, direct and realistic interpolations given an image pair. The embeddings of two images may lie on distinct conditioned distributions of a latent diffusion model, especially when they…