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Found 9 papers, 3 papers with code
Plug-and-Play Diffusion Distillation
Furthermore, once trained, our guide model can be applied to various fine-tuned, domain-specific versions of the base diffusion model without the need for additional training: this "plug-and-play" functionality drastically improves inference computation while maintaining the visual fidelity of generated images.
Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models
To address the challenge of one-shot video motion customization, we propose Customize-A-Video that models the motion from a single reference video and adapts it to new subjects and scenes with both spatial and temporal varieties.
Circuit-centric Genetic Algorithm (CGA) for Analog and Radio-Frequency Circuit Optimization
This paper presents an automated method for optimizing parameters in analog/high-frequency circuits, aiming to maximize performance parameters of a radio-frequency (RF) receiver.
Attribute Based Interpretable Evaluation Metrics for Generative Models
In this context, we propose a new evaluation protocol that measures the divergence of a set of generated images from the training set regarding the distribution of attribute strengths as follows.
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Remarkably, our discovered local latent basis enables image editing capabilities by moving $\mathbf{x}_t$, the latent space of DMs, along the basis vector at specific timesteps.
Training-free Content Injection using h-space in Diffusion Models
Instead, our method manipulates intermediate features within a feed-forward generative process.
Unsupervised Discovery of Semantic Latent Directions in Diffusion Models
Despite the success of diffusion models (DMs), we still lack a thorough understanding of their latent space.
Diffusion Models already have a Semantic Latent Space
To address the problem, we propose asymmetric reverse process (Asyrp) which discovers the semantic latent space in frozen pretrained diffusion models.
FurryGAN: High Quality Foreground-aware Image Synthesis
Foreground-aware image synthesis aims to generate images as well as their foreground masks.
