Search Results for author:
Found 14 papers, 3 papers with code
Image-based Synthesis and Re-Synthesis of Viewpoints Guided by 3D Models
We propose a technique to use the structural information extracted from a set of 3D models of an object class to improve novel-view synthesis for images showing unknown instances of this class.
Dataset Fingerprints: Exploring Image Collections Through Data Mining
As the amount of visual data increases, so does the need for summarization tools that can be used to explore large image collections and to quickly get familiar with their content.
Deep Reflectance Maps
Undoing the image formation process and therefore decomposing appearance into its intrinsic properties is a challenging task due to the under-constraint nature of this inverse problem.
Novel Views of Objects from a Single Image
We propose a technique to use the structural information extracted from a 3D model that matches the image object in terms of viewpoint and shape.
DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination
In this paper we are extracting surface reflectance and natural environmental illumination from a reflectance map, i. e. from a single 2D image of a sphere of one material under one illumination.
What Is Around The Camera?
How much does a single image reveal about the environment it was taken in?
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.
PhotoShape: Photorealistic Materials for Large-Scale Shape Collections
Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance.
Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool
Finally, we show how our neural rendering framework can capture and faithfully render objects from real images and from a diverse set of classes.
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.
From Points to Multi-Object 3D Reconstruction
We propose a method to detect and reconstruct multiple 3D objects from a single RGB image.
ShaRF: Shape-conditioned Radiance Fields from a Single View
We demonstrate in several experiments the effectiveness of our approach in both synthetic and real images.
Urban Radiance Fields
The goal of this work is to perform 3D reconstruction and novel view synthesis from data captured by scanning platforms commonly deployed for world mapping in urban outdoor environments (e. g., Street View).
Differentiable Visual Computing for Inverse Problems and Machine Learning
This approach is predicated by neural network differentiability, the requirement that analytic derivatives of a given problem's task metric can be computed with respect to neural network's parameters.
