70 citations · 119 across the 8 of their papers we have counts for
12 papers
ROGR: Relightable 3D Objects using Generative Relighting
Jiapeng Tang, Matthew Levine, Dor Verbin +5
We introduce ROGR, a novel approach that reconstructs a relightable 3D model of an object captured from multiple views, driven by a generative relighting model that simulates the e…
Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis
Christian Reiser, Stephan Garbin, Pratul P. Srinivasan +6
While surface-based view synthesis algorithms are appealing due to their low computational requirements, they often struggle to reproduce thin structures. In contrast, more expensi…
Nuvo: Neural UV Mapping for Unruly 3D Representations
Pratul P. Srinivasan, Stephan J. Garbin, Dor Verbin +2
Existing UV mapping algorithms are designed to operate on well-behaved meshes, instead of the geometry representations produced by state-of-the-art 3D reconstruction and generation…
BlendFields: Few-Shot Example-Driven Facial Modeling
Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi +5
Generating faithful visualizations of human faces requires capturing both coarse and fine-level details of the face geometry and appearance. Existing methods are either data-driven…
VolTeMorph: Realtime, Controllable and Generalisable Animation of Volumetric Representations
Stephan J. Garbin, Marek Kowalski, Virginia Estellers +5
The recent increase in popularity of volumetric representations for scene reconstruction and novel view synthesis has put renewed focus on animating volumetric content at high visu…
3D face reconstruction with dense landmarks
Erroll Wood, Tadas Baltrusaitis, Charlie Hewitt +11
Landmarks often play a key role in face analysis, but many aspects of identity or expression cannot be represented by sparse landmarks alone. Thus, in order to reconstruct faces mo…
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.…
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…
OpenEDS: Open Eye Dataset
Stephan J. Garbin, Yiru Shen, Immo Schuetz +3
We present a large scale data set, OpenEDS: Open Eye Dataset, of eye-images captured using a virtual-reality (VR) head mounted display mounted with two synchronized eyefacing camer…
Interpretable Transformations with Encoder-Decoder Networks
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov +1
Deep feature spaces have the capacity to encode complex transformations of their input data. However, understanding the relative feature-space relationship between two transformed…
Harmonic Networks: Deep Translation and Rotation Equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov +1
Translating or rotating an input image should not affect the results of many computer vision tasks. Convolutional neural networks (CNNs) are already translation equivariant: input…