1.5k citations · 8.4k across the 21 of their papers we have counts for
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eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang +10
Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusio…
Disentangling Random and Cyclic Effects in Time-Lapse Sequences
Erik Härkönen, Miika Aittala, Tuomas Kynkäänniemi +3
Time-lapse image sequences offer visually compelling insights into dynamic processes that are too slow to observe in real time. However, playing a long time-lapse sequence back as…
Generating Long Videos of Dynamic Scenes
Tim Brooks, Janne Hellsten, Miika Aittala +6
We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods…
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila +1
We argue that the theory and practice of diffusion-based generative models are currently unnecessarily convoluted and seek to remedy the situation by presenting a design space that…
The Role of ImageNet Classes in Fréchet Inception Distance
Tuomas Kynkäänniemi, Tero Karras, Miika Aittala +2
Fréchet Inception Distance (FID) is the primary metric for ranking models in data-driven generative modeling. While remarkably successful, the metric is known to sometimes disagree…