Concept

Shadow mapping

Publications associées (38)

Privacy-Enhancing Optical Embeddings for Lensless Classification

Martin Vetterli, Eric Bezzam, Matthieu Martin Jean-André Simeoni

Lensless imaging can provide visual privacy due to the highly multiplexed characteristic of its measurements. However, this alone is a weak form of security, as various adversarial attacks can be designed to invert the one-to-many scene mapping of such cam ...

2022

Nanobridge Stencil Enabling High Resolution Arbitrarily Shaped Metallic Thin Films on Various Substrates

Jürgen Brugger, Giovanni Boero, Yi-Chiang Sun

Stencil lithography (SL), which uses a perforated membrane as a reusable shadow mask to locally add material patterns on substrates provides a simple but versatile approach for the fabrication of functional devices on a large variety of substrate materials ...

WILEY2022

Texture mapping and IFC material retrievement for virtual reality applications

Sergi Aguacil Moreno, Laurent Deschamps, Sebastian Duque Mahecha, Alexandre Denis Stoll

Most current software support the Industry Foundation Classes (IFC) transfer of Building Information Models (BIMs) to applications enabling Virtual Reality (VR) navigation (BuildingSMART, 2020; Kiviniemi, Tarandi, Karlshøj, Bell, and Karud, 2008; Poljanšek ...

2021

DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation

François Fleuret, Camilla Carta

We present DepthInSpace, a self-supervised deep-learning method for depth estimation using a structured-light camera. The design of this method is motivated by the commercial use case of embedded depth sensors in nowadays smartphones. We first propose to u ...

IEEE2021

Radiative Backpropagation: An Adjoint Method for Lightning-Fast Differentiable Rendering

Wenzel Alban Jakob, Sébastien Nicolas Speierer, Merlin Eléazar Nimier-David

Physically based differentiable rendering has recently evolved into a powerful tool for solving inverse problems involving light. Methods in this area perform a differentiable simulation of the physical process of light transport and scattering to estimate ...

ASSOC COMPUTING MACHINERY2020

Reparameterizing Discontinuous Integrands for Differentiable Rendering

Wenzel Alban Jakob, Guillaume Rémi Bruno Loubet

Differentiable rendering has recently opened the door to a number of challenging inverse problems involving photorealistic images, such as computational material design and scattering-aware reconstruction of geometry and materials from photographs. Differe ...

ASSOC COMPUTING MACHINERY2019

3D Box Proposals from a Single Monocular Image of an Indoor Scene

Mathieu Salzmann, Wei Zhuo

Modern object detection methods typically rely on bounding box proposals as input. While initially popularized in the 2D case, this idea has received increasing attention for 3D bounding boxes. Nevertheless, existing 3D box proposal techniques all assume h ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

Learning to Reconstruct Texture-less Deformable Surfaces from a Single View

Pascal Fua, Mathieu Salzmann, Jan Bednarík

Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an open problem, a ...

2018

Learning to Reconstruct Texture-less Deformable Surfaces from a Single View

Pascal Fua, Mathieu Salzmann, Jan Bednarík

IEEE2018

A Novel Representation of Parts for Accurate 3D Object Detection and Tracking in Monocular Images

Pascal Fua, Vincent Lepetit, Kwang Moo Yi, Alberto Crivellaro, Yannick Verdie, Mahdi Rad

We present a method that estimates in real-time and under challenging conditions the 3D pose of a known object. Our method relies only on grayscale images since depth cameras fail on metallic objects; it can handle poorly textured objects, and cluttered, c ...

2015

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