Publications associées (141)

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

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

Using raytraverse to render high accuracy images

Stephen William Wasilewski

Raytraverse is a python based software that helps to efficiently organize and guide the sampling of a lighting simulation within a scene. Radiance is embedded within Raytraverse to provide accurate and efficient solutions for each sampled ray. This talk wi ...
2023

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Bryan German Pantoja Rosero

Current post-earthquake damage assessment methodologies are not only time-consuming but also subjective in nature and difficult to document. Recent advancements in artificial intelligence and technological devices make it possible to accomplish this task a ...
EPFL2023

NEMTO: Neural Environment Matting for Novel View and Relighting Synthesis of Transparent Objects

We propose NEMTO, the first end-to-end neural render- ing pipeline to model 3D transparent objects with complex geometry and unknown indices of refraction. Commonly used appearance modeling such as the Disney BSDF model cannot accurately address this chall ...
IEEE/CVF International Conference on Computer Vision (ICCV)2023

Dr.Jit: A Just-In-Time Compiler for Differentiable Rendering

Wenzel Alban Jakob, Nicolas Julien Roussel, Delio Aleardo Vicini, Sébastien Nicolas Speierer

Dr.Jit is a new just-in-time compiler for physically based rendering and its derivative. Dr.Jit expedites research on these topics in two ways: first, it traces high-level simulation code (e.g., written in Python) and aggressively simplifies and specialize ...
ASSOC COMPUTING MACHINERY2022

Differentiable Signed Distance Function Rendering

Wenzel Alban Jakob, Delio Aleardo Vicini, Sébastien Nicolas Speierer

Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...
ASSOC COMPUTING MACHINERY2022

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

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