EyeNeRF: A Hybrid Representation for Photorealistic Synthesis, Animation and Relighting of Human Eyes
Gengyan Li (1, 2), Abhimitra Meka (1), Franziska M\"uller (1),, Marcel C. B\"uhler (2), Otmar Hilliges (2), Thabo Beeler (1) ((1) Google, Inc., (2) ETH Z\"urich)

TL;DR
This paper introduces EyeNeRF, a hybrid 3D model combining explicit and implicit representations to achieve photorealistic synthesis, animation, and relighting of human eyes with minimal capture equipment.
Contribution
The paper presents a novel hybrid geometry and appearance model that effectively captures and renders the complex eye region, enabling high-fidelity animation and relighting from sparse data.
Findings
High-fidelity gaze synthesis under unseen lighting
Photorealistic rendering of eye reflections and refraction
Effective modeling of eye and periocular region with minimal equipment
Abstract
A unique challenge in creating high-quality animatable and relightable 3D avatars of people is modeling human eyes. The challenge of synthesizing eyes is multifold as it requires 1) appropriate representations for the various components of the eye and the periocular region for coherent viewpoint synthesis, capable of representing diffuse, refractive and highly reflective surfaces, 2) disentangling skin and eye appearance from environmental illumination such that it may be rendered under novel lighting conditions, and 3) capturing eyeball motion and the deformation of the surrounding skin to enable re-gazing. These challenges have traditionally necessitated the use of expensive and cumbersome capture setups to obtain high-quality results, and even then, modeling of the eye region holistically has remained elusive. We present a novel geometry and appearance representation that enables…
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