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Found 9 papers, 1 papers with code
A Local Appearance Model for Volumetric Capture of Diverse Hairstyle
In this paper, we present a novel method for creating high-fidelity avatars with diverse hairstyles.
Drivable Avatar Clothing: Faithful Full-Body Telepresence with Dynamic Clothing Driven by Sparse RGB-D Input
Clothing is an important part of human appearance but challenging to model in photorealistic avatars.
NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation
The capture and animation of human hair are two of the major challenges in the creation of realistic avatars for the virtual reality.
Dressing Avatars: Deep Photorealistic Appearance for Physically Simulated Clothing
The key idea is to introduce a neural clothing appearance model that operates on top of explicit geometry: at training time we use high-fidelity tracking, whereas at animation time we rely on physically simulated geometry.
HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capture
Capturing and rendering life-like hair is particularly challenging due to its fine geometric structure, the complex physical interaction and its non-trivial visual appearance. Yet, hair is a critical component for believable avatars.
Modeling Clothing as a Separate Layer for an Animatable Human Avatar
To address these difficulties, we propose a method to build an animatable clothed body avatar with an explicit representation of the clothing on the upper body from multi-view captured videos.
Learning Compositional Radiance Fields of Dynamic Human Heads
In addition, we show that the learned dynamic radiance field can be used to synthesize novel unseen expressions based on a global animation code.
Batteries, camera, action! Learning a semantic control space for expressive robot cinematography
First, we generate a database of video clips with a diverse range of shots in a photo-realistic simulator, and use hundreds of participants in a crowd-sourcing framework to obtain scores for a set of semantic descriptors for each clip.
MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video
A differentiable renderer is utilized to align our captured shapes to the input frames by minimizing the difference in both silhouette, segmentation, and texture.
