110 citations · 136 across the 7 of their papers we have counts for
9 papers · 1 filter
LightLab: Controlling Light Sources in Images with Diffusion Models
Nadav Magar, Amir Hertz, Eric Tabellion +4
We present a simple, yet effective diffusion-based method for fine-grained, parametric control over light sources in an image. Existing relighting methods either rely on multiple i…
ObjectMate: A Recurrence Prior for Object Insertion and Subject-Driven Generation
Daniel Winter, Asaf Shul, Matan Cohen +4
This paper introduces a tuning-free method for both object insertion and subject-driven generation. The task involves composing an object, given multiple views, into a scene specif…
ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning
David Junhao Zhang, Roni Paiss, Shiran Zada +7
Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided…
Unbounded: A Generative Infinite Game of Character Life Simulation
Jialu Li, Yuanzhen Li, Neal Wadhwa +5
We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired b…
Null-text Inversion for Editing Real Images using Guided Diffusion Models
Ron Mokady, Amir Hertz, Kfir Aberman +2
Recent text-guided diffusion models provide powerful image generation capabilities. Currently, a massive effort is given to enable the modification of these images using text only…
Deep Saliency Prior for Reducing Visual Distraction
Kfir Aberman, Junfeng He, Yossi Gandelsman +5
Using only a model that was trained to predict where people look at images, and no additional training data, we can produce a range of powerful editing effects for reducing distrac…