papers

Publications (18)

cs.CV2024

RealFill: Reference-Driven Generation for Authentic Image Completion

Luming Tang, Nataniel Ruiz, Qinghao Chu +8

Recent advances in generative imagery have brought forth outpainting and inpainting models that can produce high-quality, plausible image content in unknown regions. However, the c…

cs.CV2020

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

Magic Insert: Style-Aware Drag-and-Drop

Nataniel Ruiz, Yuanzhen Li, Neal Wadhwa +4

We present Magic Insert, a method for dragging-and-dropping subjects from a user-provided image into a target image of a different style in a physically plausible manner while matc…

cs.CV2020

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…