312 citations · 340 across the 9 of their papers we have counts for
11 papers
Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures
Marcel C. Bühler, Gengyan Li, Erroll Wood +13
Volumetric modeling and neural radiance field representations have revolutionized 3D face capture and photorealistic novel view synthesis. However, these methods often require hund…
Preface: A Data-driven Volumetric Prior for Few-shot Ultra High-resolution Face Synthesis
Marcel C. Bühler, Kripasindhu Sarkar, Tanmay Shah +8
NeRFs have enabled highly realistic synthesis of human faces including complex appearance and reflectance effects of hair and skin. These methods typically require a large number o…
Controllable Light Diffusion for Portraits
David Futschik, Kelvin Ritland, James Vecore +5
We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination. Inspired…
Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos
Ziqian Bai, Feitong Tan, Zeng Huang +12
We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achie…
VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relighting
Feitong Tan, Sean Fanello, Abhimitra Meka +6
We propose VoLux-GAN, a generative framework to synthesize 3D-aware faces with convincing relighting. Our main contribution is a volumetric HDRI relighting method that can efficien…
NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis
Zuria Bauer, Zuoyue Li, Sergio Orts-Escolano +3
Building upon the recent progress in novel view synthesis, we propose its application to improve monocular depth estimation. In particular, we propose a novel training method split…
Advances in Neural Rendering
Ayush Tewari, Justus Thies, Ben Mildenhall +14
Synthesizing photo-realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are ge…
UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments
Pablo Martinez-Gonzalez, Sergiu Oprea, John Alejandro Castro-Vargas +4
Synthetic data generation has become essential in last years for feeding data-driven algorithms, which surpassed traditional techniques performance in almost every computer vision…
H-GAN: the power of GANs in your Hands
Sergiu Oprea, Giorgos Karvounas, Pablo Martinez-Gonzalez +7
We present HandGAN (H-GAN), a cycle-consistent adversarial learning approach implementing multi-scale perceptual discriminators. It is designed to translate synthetic images of han…
A Review on Deep Learning Techniques for Video Prediction
Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia +4
The ability to predict, anticipate and reason about future outcomes is a key component of intelligent decision-making systems. In light of the success of deep learning in computer…
UnrealROX: An eXtremely Photorealistic Virtual Reality Environment for Robotics Simulations and Synthetic Data Generation
Pablo Martinez-Gonzalez, Sergiu Oprea, Alberto Garcia-Garcia +3
Data-driven algorithms have surpassed traditional techniques in almost every aspect in robotic vision problems. Such algorithms need vast amounts of quality data to be able to work…