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Found 5 papers, 3 papers with code
Motion Inversion for Video Customization
In this research, we present a novel approach to motion customization in video generation, addressing the widespread gap in the thorough exploration of motion representation within video generative models.
Denoising Diffusion Step-aware Models
Denoising Diffusion Probabilistic Models (DDPMs) have garnered popularity for data generation across various domains.
Not All Steps are Created Equal: Selective Diffusion Distillation for Image Manipulation
Conditional diffusion models have demonstrated impressive performance in image manipulation tasks.
Decompose and Realign: Tackling Condition Misalignment in Text-to-Image Diffusion Models
The ``Decompose'' phase separates conditions based on pair relationships, computing the result individually for each pair.
Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
This work explores the use of 3D generative models to synthesize training data for 3D vision tasks.
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