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Related Experiment Video

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Optic Nerve Sheath Point of Care Ultrasound: Image Acquisition

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Neural Opacity Point Cloud.

Cen Wang, Minye Wu, Ziyu Wang

IEEE Transactions on Pattern Analysis and Machine Intelligence

|April 20, 2020

Summary

This summary is machine-generated.

Scanning fuzzy objects like hair or fur is challenging. Our new neural rendering technique, Neural Opacity Point Cloud (NOPC), enables high-quality 3D rendering of these difficult-to-scan items from any viewpoint.

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Area of Science:

Computer Vision
Computer Graphics
Machine Learning

Background:

3D scanning of objects with complex, fine details like hair, fur, or feathers remains a significant challenge.
Existing active and passive 3D scanning technologies struggle to capture the intricate geometry and appearance of such fuzzy surfaces accurately.

Purpose of the Study:

To introduce a novel neural rendering (NR) technique, Neural Opacity Point Cloud (NOPC), for high-quality 3D rendering of fuzzy objects.
To enable photorealistic rendering of challenging objects from arbitrary viewpoints, overcoming limitations of current 3D scanning methods.

Main Methods:

NOPC utilizes a learning-based approach to extract geometric, appearance, and opacity features from 3D point clouds.
A U-Net based neural renderer processes these features, handling noisy and incomplete geometry while preserving translation equivariance.
The method maps extracted 3D features to virtual viewpoints for novel view synthesis.

Main Results:

NOPC successfully produces photorealistic renderings of fuzzy objects, including hair and fur.
Experiments were conducted on both existing and newly created datasets, demonstrating the technique's effectiveness.
The method performs well with inputs from multi-view setups, such as turntable systems.

Conclusions:

Neural Opacity Point Cloud (NOPC) offers a practical and effective solution for rendering fuzzy objects, a long-standing problem in 3D computer vision and graphics.
This neural rendering technique significantly advances the ability to capture and visualize complex, fine-detail objects in 3D.