189 citations · 256 across the 9 of their papers we have counts for
12 papers
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
Nataniel Ruiz, Yuanzhen Li, Varun Jampani +6
Personalization has emerged as a prominent aspect within the field of generative AI, enabling the synthesis of individuals in diverse contexts and styles, while retaining high-fide…
Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image
Shumian Xin, Neal Wadhwa, Tianfan Xue +5
We present a method that takes as input a single dual-pixel image, and simultaneously estimates the image's defocus map -- the amount of defocus blur at each pixel -- and recovers…
Zoom-to-Inpaint: Image Inpainting with High-Frequency Details
Soo Ye Kim, Kfir Aberman, Nori Kanazawa +6
Although deep learning has enabled a huge leap forward in image inpainting, current methods are often unable to synthesize realistic high-frequency details. In this paper, we propo…
Learned Dual-View Reflection Removal
Simon Niklaus, Xuaner Cecilia Zhang, Jonathan T. Barron +4
Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconv…
Learning to Autofocus
Charles Herrmann, Richard Strong Bowen, Neal Wadhwa +4
Autofocus is an important task for digital cameras, yet current approaches often exhibit poor performance. We propose a learning-based approach to this problem, and provide a reali…
DuNet: Learning Depth Estimation from Dual-Cameras and Dual-Pixels
Yinda Zhang, Neal Wadhwa, Sergio Orts-Escolano +3
Computational stereo has reached a high level of accuracy, but degrades in the presence of occlusions, repeated textures, and correspondence errors along edges. We present a novel…