1.6k citations · 4.9k across the 61 of their papers we have counts for
76 papers
3D Motion Magnification: Visualizing Subtle Motions with Time Varying Radiance Fields
Brandon Y. Feng, Hadi Alzayer, Michael Rubinstein +2
Motion magnification helps us visualize subtle, imperceptible motion. However, prior methods only work for 2D videos captured with a fixed camera. We present a 3D motion magnificat…
Background Prompting for Improved Object Depth
Manel Baradad, Yuanzhen Li, Forrester Cole +4
Estimating the depth of objects from a single image is a valuable task for many vision, robotics, and graphics applications. However, current methods often fail to produce accurate…
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision
Ayush Tewari, Tianwei Yin, George Cazenavette +5
Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenario…
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention
Guangxuan Xiao, Tianwei Yin, William T. Freeman +2
Diffusion models excel at text-to-image generation, especially in subject-driven generation for personalized images. However, existing methods are inefficient due to the subject-sp…
Muse: Text-To-Image Generation via Masked Generative Transformers
Huiwen Chang, Han Zhang, Jarred Barber +9
We present Muse, a text-to-image Transformer model that achieves state-of-the-art image generation performance while being significantly more efficient than diffusion or autoregres…
Can Shadows Reveal Biometric Information?
Safa C. Medin, Amir Weiss, Frédo Durand +2
We study the problem of extracting biometric information of individuals by looking at shadows of objects cast on diffuse surfaces. We show that the biometric information leakage fr…