Search Results for author:
Found 21 papers, 13 papers with code
Gravitationally Lensed Black Hole Emission Tomography
In this work, we propose BH-NeRF, a novel tomography approach that leverages gravitational lensing to recover the continuous 3D emission field near a black hole.
PlenOctrees for Real-time Rendering of Neural Radiance Fields
We introduce a method to render Neural Radiance Fields (NeRFs) in real time using PlenOctrees, an octree-based 3D representation which supports view-dependent effects.
R-SLAM: Optimizing Eye Tracking From Rolling Shutter Video of the Retina
We present a method for optimization-based recovery of eye motion from rolling shutter video of the retina.
Learned Initializations for Optimizing Coordinate-Based Neural Representations
Coordinate-based neural representations have shown significant promise as an alternative to discrete, array-based representations for complex low dimensional signals.
Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy
Miniature fluorescence microscopes are a standard tool in systems biology.
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
We show that passing input points through a simple Fourier feature mapping enables a multilayer perceptron (MLP) to learn high-frequency functions in low-dimensional problem domains.
Portrait Shadow Manipulation
We propose a way to explicitly encode facial symmetry and show that our dataset and training procedure enable the model to generalize to images taken in the wild.
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Our algorithm represents a scene using a fully-connected (non-convolutional) deep network, whose input is a single continuous 5D coordinate (spatial location $(x, y, z)$ and viewing direction $(\theta, \phi)$) and whose output is the volume density and view-dependent emitted radiance at that spatial location.
Video from Stills: Lensless Imaging with Rolling Shutter
Here, we propose using multiplexing optics to spatially compress the scene, enabling information about the whole scene to be sampled from a row of sensor pixels, which can be read off quickly via a rolling shutter CMOS sensor.
Synthetic Defocus and Look-Ahead Autofocus for Casual Videography
We present a system that synthetically renders refocusable video from a deep DOF video shot with a smartphone, and analyzes future video frames to deliver context-aware autofocus for the current frame.
Zoom To Learn, Learn To Zoom
We show how to obtain the ground-truth data with optically zoomed images and contribute a dataset, SR-RAW, for real-world computational zoom.
Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
We present a practical and robust deep learning solution for capturing and rendering novel views of complex real world scenes for virtual exploration.
Pushing the Boundaries of View Extrapolation with Multiplane Images
We present a theoretical analysis showing how the range of views that can be rendered from an MPI increases linearly with the MPI disparity sampling frequency, as well as a novel MPI prediction procedure that theoretically enables view extrapolations of up to $4\times$ the lateral viewpoint movement allowed by prior work.
StegaStamp: Invisible Hyperlinks in Physical Photographs
Printed and digitally displayed photos have the ability to hide imperceptible digital data that can be accessed through internet-connected imaging systems.
Single Image Reflection Separation with Perceptual Losses
Our loss function includes two perceptual losses: a feature loss from a visual perception network, and an adversarial loss that encodes characteristics of images in the transmission layers.
Burst Denoising with Kernel Prediction Networks
We present a technique for jointly denoising bursts of images taken from a handheld camera.
Aperture Supervision for Monocular Depth Estimation
We present a novel method to train machine learning algorithms to estimate scene depths from a single image, by using the information provided by a camera's aperture as supervision.
DiffuserCam: Lensless Single-exposure 3D Imaging
We demonstrate a compact and easy-to-build computational camera for single-shot 3D imaging.
Learning to Synthesize a 4D RGBD Light Field from a Single Image
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).
Light Field Blind Motion Deblurring
We study the problem of deblurring light fields of general 3D scenes captured under 3D camera motion and present both theoretical and practical contributions.
Oriented Light-Field Windows for Scene Flow
2D spatial image windows are used for comparing pixel values in computer vision applications such as correspondence for optical flow and 3D reconstruction, bilateral filtering, and image segmentation.
