Search Results for author: Brian Curless

Found 20 papers, 6 papers with code

Mates2Motion: Learning How Mechanical CAD Assemblies Work

no code implementations2 Aug 2022 James Noeckel, Benjamin T. Jones, Karl Willis, Brian Curless, Adriana Schulz

We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations.

3D Moments from Near-Duplicate Photos

no code implementations CVPR 2022 Qianqian Wang, Zhengqi Li, David Salesin, Noah Snavely, Brian Curless, Janne Kontkanen

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.

Motion Interpolation

FILM: Frame Interpolation for Large Motion

1 code implementation10 Feb 2022 Fitsum Reda, Janne Kontkanen, Eric Tabellion, Deqing Sun, Caroline Pantofaru, Brian Curless

Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis.

Optical Flow Estimation Video Frame Interpolation

HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video

1 code implementation CVPR 2022 Chung-Yi Weng, Brian Curless, Pratul P. Srinivasan, Jonathan T. Barron, Ira Kemelmacher-Shlizerman

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.

SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting

no code implementations ICCV 2021 Varun Jampani, Huiwen Chang, Kyle Sargent, Abhishek Kar, Richard Tucker, Michael Krainin, Dominik Kaeser, William T. Freeman, David Salesin, Brian Curless, Ce Liu

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.

Image Matting

Fabrication-Aware Reverse Engineering for Carpentry

1 code implementation21 Jul 2021 James Noeckel, Haisen Zhao, Brian Curless, Adriana Schulz

We propose a novel method to generate fabrication blueprints from images of carpentered items.

3D Reconstruction

A Light Stage on Every Desk

no code implementations ICCV 2021 Soumyadip Sengupta, Brian Curless, Ira Kemelmacher-Shlizerman, Steve Seitz

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.

Vid2Actor: Free-viewpoint Animatable Person Synthesis from Video in the Wild

no code implementations23 Dec 2020 Chung-Yi Weng, Brian Curless, Ira Kemelmacher-Shlizerman

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.

Image-to-Image Translation Translation

Real-Time High-Resolution Background Matting

2 code implementations CVPR 2021 Shanchuan Lin, Andrey Ryabtsev, Soumyadip Sengupta, Brian Curless, Steve Seitz, Ira Kemelmacher-Shlizerman

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.

Image Matting

Animating Pictures with Eulerian Motion Fields

no code implementations CVPR 2021 Aleksander Holynski, Brian Curless, Steven M. Seitz, Richard Szeliski

In this paper, we demonstrate a fully automatic method for converting a still image into a realistic animated looping video.

Image-to-Image Translation Translation

Reconstructing NBA Players

2 code implementations ECCV 2020 Luyang Zhu, Konstantinos Rematas, Brian Curless, Steve Seitz, Ira Kemelmacher-Shlizerman

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.

People as Scene Probes

no code implementations ECCV 2020 Yifan Wang, Brian Curless, Steve Seitz

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.

Depth Estimation

Background Matting: The World is Your Green Screen

1 code implementation CVPR 2020 Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steve Seitz, Ira Kemelmacher-Shlizerman

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.

Image Matting

Structure from Motion for Panorama-Style Videos

no code implementations8 Jun 2019 Chris Sweeney, Aleksander Holynski, Brian Curless, Steve M Seitz

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.

Photo Wake-Up: 3D Character Animation from a Single Photo

no code implementations CVPR 2019 Chung-Yi Weng, Brian Curless, Ira Kemelmacher-Shlizerman

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.

3D Character Animation From A Single Photo

Soccer on Your Tabletop

no code implementations CVPR 2018 Konstantinos Rematas, Ira Kemelmacher-Shlizerman, Brian Curless, Steve Seitz

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.

3D Reconstruction Depth Estimation

Discovering Point Lights With Intensity Distance Fields

no code implementations CVPR 2018 Edward Zhang, Michael F. Cohen, Brian Curless

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.

Light Field Layer Matting

no code implementations CVPR 2015 Juliet Fiss, Brian Curless, Rick Szeliski

In this paper, we use matting to separate foreground layers from light fields captured with a plenoptic camera.

Image Matting

Occluding Contours for Multi-View Stereo

no code implementations CVPR 2014 Qi Shan, Brian Curless, Yasutaka Furukawa, Carlos Hernandez, Steven M. Seitz

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.

Surface Reconstruction

Cannot find the paper you are looking for? You can Submit a new open access paper.