5 papers · 1 filter
Linearly Constrained Diffusion Implicit Models
Vivek Jayaram, Ira Kemelmacher-Shlizerman, Steven M. Seitz +1
We introduce Linearly Constrained Diffusion Implicit Models (CDIM), a fast and accurate approach to solving noisy linear inverse problems using diffusion models. Traditional diffus…
Inverse Painting: Reconstructing The Painting Process
Bowei Chen, Yifan Wang, Brian Curless +2
Given an input painting, we reconstruct a time-lapse video of how it may have been painted. We formulate this as an autoregressive image generation problem, in which an initially b…
Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation
Xiaojuan Wang, Boyang Zhou, Brian Curless +3
We present a method for generating video sequences with coherent motion between a pair of input key frames. We adapt a pretrained large-scale image-to-video diffusion model (origin…
Infinite Texture: Text-guided High Resolution Diffusion Texture Synthesis
Yifan Wang, Aleksander Holynski, Brian L. Curless +1
We present Infinite Texture, a method for generating arbitrarily large texture images from a text prompt. Our approach fine-tunes a diffusion model on a single texture, and learns…
Don't Look at the Camera: Achieving Perceived Eye Contact
Alice Gao, Samyukta Jayakumar, Marcello Maniglia +4
We consider the question of how to best achieve the perception of eye contact when a person is captured by camera and then rendered on a 2D display. For single subjects photographe…