most citedLearning to Synthesize a 4D RGBD Light Field from a Single Image

15 citations · 29 across the 4 of their papers we have counts for

collaborators

6 papers

eess.IV2019

Video from Stills: Lensless Imaging with Rolling Shutter

Nick Antipa, Patrick Oare, Emrah Bostan +2

Because image sensor chips have a finite bandwidth with which to read out pixels, recording video typically requires a trade-off between frame rate and pixel count. Compressed sens…

cs.CV20194 cited

Synthetic Defocus and Look-Ahead Autofocus for Casual Videography

Xuaner Zhang, Kevin Matzen, Vivien Nguyen +3

In cinema, large camera lenses create beautiful shallow depth of field (DOF), but make focusing difficult and expensive. Accurate cinema focus usually relies on a script and a pers…

cs.CV2019

Zoom To Learn, Learn To Zoom

Xuaner Cecilia Zhang, Qifeng Chen, Ren Ng +1

This paper shows that when applying machine learning to digital zoom for photography, it is beneficial to use real, RAW sensor data for training. Existing learning-based super-reso…

cs.CV201910 cited

Pushing the Boundaries of View Extrapolation with Multiplane Images

Pratul P. Srinivasan, Richard Tucker, Jonathan T. Barron +3

We explore the problem of view synthesis from a narrow baseline pair of images, and focus on generating high-quality view extrapolations with plausible disocclusions. Our method bu…

cs.CV2017

DiffuserCam: Lensless Single-exposure 3D Imaging

Nick Antipa, Grace Kuo, Reinhard Heckel +4

We demonstrate a compact and easy-to-build computational camera for single-shot 3D imaging. Our lensless system consists solely of a diffuser placed in front of a standard image se…

cs.CV201715 cited

Learning to Synthesize a 4D RGBD Light Field from a Single Image

Pratul P. Srinivasan, Tongzhou Wang, Ashwin Sreelal +2

We present a machine learning algorithm that takes as input a 2D RGB image and synthesizes a 4D RGBD light field (color and depth of the scene in each ray direction). For training,…