Neural radiance fields (NeRFs) refer to a suit of deep neural networks that are used to learn
and represent objects or scenes. Generally speaking, NeRFs have five main characters …

Abstract 3D reconstruction of deformable (or non‐rigid) scenes from a set of monocular 2D
image observations is a long‐standing and actively researched area of computer vision and …

Recently, DALL-E, a multimodal transformer language model, and its variants including
diffusion models have shown high-quality text-to-image generation capabilities. However …

Text-to-image generative models often reflect the biases of the training data, leading to
unequal representations of underrepresented groups. This study investigates inclusive text …

In this paper, we introduce FitMe, a facial reflectance model and a differentiable rendering
optimization pipeline, that can be used to acquire high-fidelity renderable human avatars …

Understanding different human attributes and how they affect model behavior may become
a standard need for all model creation and usage, from traditional computer vision tasks to …

Following the remarkable success of diffusion models on image generation, recent works
have also demonstrated their impressive ability to address a number of inverse problems in …

Existing methods for capturing datasets of 3D heads in dense semantic correspondence are
slow and commonly address the problem in two separate steps; multi-view stereo (MVS) …

This paper strives to measure apparent skin color in computer vision, beyond a
unidimensional scale on skin tone. In their seminal paper Gender Shades, Buolamwini and …

Our goal is to efficiently learn personalized animatable 3D head avatars from videos that are
geometrically accurate, realistic, relightable, and compatible with current rendering systems …