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Found 6 papers, 3 papers with code
MonoHair: High-Fidelity Hair Modeling from a Monocular Video
For the interior, we employ a data-driven, multi-view 3D hair reconstruction method.
AniDress: Animatable Loose-Dressed Avatar from Sparse Views Using Garment Rigging Model
In this paper, we introduce AniDress, a novel method for generating animatable human avatars in loose clothes using very sparse multi-view videos (4-8 in our setting).
NeuralReshaper: Single-image Human-body Retouching with Deep Neural Networks
In this paper, we present NeuralReshaper, a novel method for semantic reshaping of human bodies in single images using deep generative networks.
Domain Adaptation on Point Clouds via Geometry-Aware Implicits
Here we propose a simple yet effective method for unsupervised domain adaptation on point clouds by employing a self-supervised task of learning geometry-aware implicits, which plays two critical roles in one shot.
DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis
We describe a method for unpaired realistic depth synthesis that learns diverse variations from the real-world depth scans and ensures geometric consistency between the synthetic and synthesized depth.
DeepSketchHair: Deep Sketch-based 3D Hair Modeling
The key enablers of our system are two carefully designed neural networks, namely, S2ONet, which converts an input sketch to a dense 2D hair orientation field; and O2VNet, which maps the 2D orientation field to a 3D vector field.
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