14 citations · 19 across the 4 of their papers we have counts for
6 papers
FastNeRF: High-Fidelity Neural Rendering at 200FPS
Stephan J. Garbin, Marek Kowalski, Matthew Johnson +2
Recent work on Neural Radiance Fields (NeRF) showed how neural networks can be used to encode complex 3D environments that can be rendered photorealistically from novel viewpoints.…
A high fidelity synthetic face framework for computer vision
Tadas Baltrusaitis, Erroll Wood, Virginia Estellers +6
Analysis of faces is one of the core applications of computer vision, with tasks ranging from landmark alignment, head pose estimation, expression recognition, and face recognition…
High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images
Stephan J. Garbin, Marek Kowalski, Matthew Johnson +1
Generating photorealistic images of human faces at scale remains a prohibitively difficult task using computer graphics approaches. This is because these require the simulation of…
CONFIG: Controllable Neural Face Image Generation
Marek Kowalski, Stephan J. Garbin, Virginia Estellers +3
Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generativ…
Face Alignment Using K-Cluster Regression Forests With Weighted Splitting
Marek Kowalski, Jacek Naruniec
In this work we present a face alignment pipeline based on two novel methods: weighted splitting for K-cluster Regression Forests and 3D Affine Pose Regression for face shape initi…
Deep Alignment Network: A convolutional neural network for robust face alignment
Marek Kowalski, Jacek Naruniec, Tomasz Trzcinski
In this paper, we propose Deep Alignment Network (DAN), a robust face alignment method based on a deep neural network architecture. DAN consists of multiple stages, where each stag…