Search Results for author: Konstantinos Rematas

Found 14 papers, 3 papers with code

Differentiable Visual Computing for Inverse Problems and Machine Learning

no code implementations21 Nov 2023 Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas, Krishna Murthy Jatavallabhula, Cengiz Oztireli, Tzu-Mao Li, Derek Nowrouzezahrai

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.

Urban Radiance Fields

no code implementations CVPR 2022 Konstantinos Rematas, Andrew Liu, Pratul P. Srinivasan, Jonathan T. Barron, Andrea Tagliasacchi, Thomas Funkhouser, Vittorio Ferrari

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).

3D Reconstruction Novel View Synthesis

ShaRF: Shape-conditioned Radiance Fields from a Single View

no code implementations17 Feb 2021 Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari

We demonstrate in several experiments the effectiveness of our approach in both synthetic and real images.

Disentanglement Object

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.

Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool

1 code implementation CVPR 2020 Konstantinos Rematas, Vittorio Ferrari

Finally, we show how our neural rendering framework can capture and faithfully render objects from real images and from a diverse set of classes.

Image Generation Neural Rendering

PhotoShape: Photorealistic Materials for Large-Scale Shape Collections

1 code implementation26 Sep 2018 Keunhong Park, Konstantinos Rematas, Ali Farhadi, Steven M. Seitz

Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance.

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

DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination

no code implementations27 Mar 2016 Stamatios Georgoulis, Konstantinos Rematas, Tobias Ritschel, Mario Fritz, Luc van Gool, Tinne Tuytelaars

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.

Novel Views of Objects from a Single Image

no code implementations31 Jan 2016 Konstantinos Rematas, Chuong Nguyen, Tobias Ritschel, Mario Fritz, Tinne Tuytelaars

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.

Novel View Synthesis Object

Deep Reflectance Maps

no code implementations CVPR 2016 Konstantinos Rematas, Tobias Ritschel, Mario Fritz, Efstratios Gavves, Tinne Tuytelaars

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.

Dataset Fingerprints: Exploring Image Collections Through Data Mining

no code implementations CVPR 2015 Konstantinos Rematas, Basura Fernando, Frank Dellaert, Tinne Tuytelaars

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.

Image-based Synthesis and Re-Synthesis of Viewpoints Guided by 3D Models

no code implementations CVPR 2014 Konstantinos Rematas, Tobias Ritschel, Mario Fritz, Tinne Tuytelaars

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.

Novel View Synthesis Position +1

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