Search Results for author:
Found 25 papers, 6 papers with code
Occluding Contours for Multi-View Stereo
The proposed approach outperforms state of the art MVS techniques for challenging Internet datasets, yielding dramatic quality improvements both around object contours and in surface detail.
Light Field Layer Matting
In this paper, we use matting to separate foreground layers from light fields captured with a plenoptic camera.
Discovering Point Lights With Intensity Distance Fields
Given the geometry, materials, and illuminated appearance of the scene, the light localization problem is to completely recover the number, positions, and intensities of the lights.
Soccer on Your Tabletop
We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewer or through an Augmented Reality device.
Photo Wake-Up: 3D Character Animation from a Single Photo
The key contributions of this paper are: 1) an application of viewing and animating humans in single photos in 3D, 2) a novel 2D warping method to deform a posable template body model to fit the person's complex silhouette to create an animatable mesh, and 3) a method for handling partial self occlusions.
Structure from Motion for Panorama-Style Videos
We present a novel Structure from Motion pipeline that is capable of reconstructing accurate camera poses for panorama-style video capture without prior camera intrinsic calibration.
Background Matting: The World is Your Green Screen
To bridge the domain gap to real imagery with no labeling, we train another matting network guided by the first network and by a discriminator that judges the quality of composites.
Ranked #1 on
Image Matting
on Adobe Matting
People as Scene Probes
By analyzing the motion of people and other objects in a scene, we demonstrate how to infer depth, occlusion, lighting, and shadow information from video taken from a single camera viewpoint.
Reconstructing NBA Players
Based on these models, we introduce a new method that takes as input a single photo of a clothed player in any basketball pose and outputs a high resolution mesh and 3D pose for that player.
Animating Pictures with Eulerian Motion Fields
In this paper, we demonstrate a fully automatic method for converting a still image into a realistic animated looping video.
Real-Time High-Resolution Background Matting
We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU.
No Shadow Left Behind: Removing Objects and their Shadows using Approximate Lighting and Geometry
Removing objects from images is a challenging problem that is important for many applications, including mixed reality.
Vid2Actor: Free-viewpoint Animatable Person Synthesis from Video in the Wild
At the core of our method is a volumetric 3D human representation reconstructed with a deep network trained on input video, enabling novel pose/view synthesis.
A Light Stage on Every Desk
Whereas existing light stages require expensive, room-scale spherical capture gantries and exist in only a few labs in the world, we demonstrate how to acquire useful data from a normal TV or desktop monitor.
Fabrication-Aware Reverse Engineering for Carpentry
We propose a novel method to generate fabrication blueprints from images of carpentered items.
SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting
We present SLIDE, a modular and unified system for single image 3D photography that uses a simple yet effective soft layering strategy to better preserve appearance details in novel views.
HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video
Our method optimizes for a volumetric representation of the person in a canonical T-pose, in concert with a motion field that maps the estimated canonical representation to every frame of the video via backward warps.
FILM: Frame Interpolation for Large Motion
Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis.
Ranked #2 on
Video Frame Interpolation
on Xiph-4k
3D Moments from Near-Duplicate Photos
As output, we produce a video that smoothly interpolates the scene motion from the first photo to the second, while also producing camera motion with parallax that gives a heightened sense of 3D.
Mates2Motion: Learning How Mechanical CAD Assemblies Work
We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations.
PersonNeRF: Personalized Reconstruction from Photo Collections
We present PersonNeRF, a method that takes a collection of photos of a subject (e. g. Roger Federer) captured across multiple years with arbitrary body poses and appearances, and enables rendering the subject with arbitrary novel combinations of viewpoint, body pose, and appearance.
Controllable Light Diffusion for Portraits
We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination.
Total Selfie: Generating Full-Body Selfies
We present a method to generate full-body selfies from photographs originally taken at arms length.
Animating Street View
We present a system that automatically brings street view imagery to life by populating it with naturally behaving, animated pedestrians and vehicles.
Generative Powers of Ten
We present a method that uses a text-to-image model to generate consistent content across multiple image scales, enabling extreme semantic zooms into a scene, e. g., ranging from a wide-angle landscape view of a forest to a macro shot of an insect sitting on one of the tree branches.
