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Publications associées (74)

Aggregating Spatial and Photometric Context for Photometric Stereo

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

GeoNeRF: Generalizing NeRF with Geometry Priors

François Fleuret

We present GeoNeRF, a generalizable photorealistic novel view synthesis method based on neural radiance fields. Our approach consists of two main stages: a geometry reasoner and a renderer. To render a novel view, the geometry reasoner first constructs cas ...

IEEE COMPUTER SOC2022

Scene Decomposition and Relighting from Image Collections in Neural Rendering

Dongqing Wang

The focus of our research is to generate controllable photo-realistic images of real-world scenes from existing observations, i.e., the inverse rendering problem. The approaches we focus on are those through neural rendering, utilizing neural network to de ...

2022

Efficient and Accurate Physically-Based Differentiable Rendering

Delio Aleardo Vicini

Physically-based rendering algorithms generate photorealistic images of virtual scenes. By simulating light paths in a scene, complex physical effects such as shadows, reflections and volumetric scattering can be reproduced. Over the last decade, physicall ...

EPFL2022

Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

2022

Modeling specular transmission of complex fenestration systems with data-driven BSDFs

Jan Wienold

A Bidirectional Scattering Distribution Function (BSDF) describes how light from each incident direction is scattered (reflected and transmitted) by a simple or composite surface, such as a window shade. Compact, tabular BSDFs may be derived via interpolat ...

2021

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Wenzel Alban Jakob, Delio Aleardo Vicini

We introduce a novel transmittance model to improve the volumetric representation of 3D scenes. The model can represent opaque surfaces in the volumetric light transport framework. Volumetric representations are useful for complex scenes, and become increa ...

ASSOC COMPUTING MACHINERY2021

Light Path Gradients for Forward and Inverse Rendering

Tizian Lucien Zeltner

Physically based rendering is a process for photorealistic digital image synthesis and one of the core problems in computer graphics. It involves simulating the light transport, i.e. the emission, propagation, and scattering of light through a virtual scen ...

EPFL2021

A Shared Representation for Photorealistic Driving Simulators

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan, Siyuan Li

A powerful simulator highly decreases the need for real-world tests when training and evaluating autonomous vehicles. Data-driven simulators flourished with the recent advancement of conditional Generative Adversarial Networks (cGANs), providing high-fidel ...

2021

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