Juan Raúl Padrón Griffe

Epale! I am a Marie Sklodowska-Curie fellow of the EU Project PRIME and a PhD candidate at the Graphics and Imaging Lab (Universidad de Zaragoza). My PhD thesis under the supervision of Prof. Adolfo Muñoz and Adrian Jarabo focuses on developing theory and methods for accurate and efficient rendering of complex volumetric appearances. Previously, I obtained my Bachelor degree in Computer Science (2015) at the Central University of Venezuela. Later, I received my Master degree in Informatics (2020) at the Technical University of Munich. During my Master studies I focused mostly on the Computer Graphics and Vision subjects, where I was fortunate enough to be advised by Prof. Matthias Niessner and Dr. Justus Thies at the Visual Computing lab to conduct my research on 3D Scanning and Neural Rendering.

I am a computer scientist enthusiastic about the intersection of realistic image synthesis, graphics-based vision and machine learning for the digital acquisition, representation and understanding of the visual world. I am currently interested in pushing the state of the art on physically-based rendering of complex multi-scale materials like biological tissues. In my research, I rely on powerful tools like Monte Carlo simulation and gradient-based optimization. In the long term, I believe the combination of powerful forward models (simulation algorithms) and inverse models (gradient-based models) could be impactful in other interesting domains too like computational biology.

Projects

Snake Skin Rendering (CEIG 2023)

Multilayered appearance model based on the anatomy of the snake skin capable of reproducing the main appearance features on snake colors such as the highly specular iridescent colors and dark diffuse skin. The material was implemented as a BSDF layered material inside the popular physically-based renderer Mitsuba.

1 minute read

Face Relighting In The Wild

Given an arbitrary portrait image and a target lighting as inputs, the algorithm generates the relight version of the portrait image under the target lighting conditions.

2 minute read

Neural Relighting

Extension of the Deferred Neural Rendering pipeline to perform relighting tasks. This is a new paradigm for image synthesis that combines the traditional graphics pipeline with learnable Neural Textures.

1 minute read

RGB-D Reconstruction for Mixed Reality

Real-time mixed reality game using marker-less tracking and 3D reconstruction based on Kinect Fusion pipeline and several Unity modules.

1 minute read

Game Capture

C++ library for the extraction of ground truth labels and the internal game states of video games to train computer vision models for autonomous driving applications.

2 minute read