3D Curve Drawings


This is the companion website to the paper:

From Multiview Image Curves to 3D Drawings ECCV 2016
Expanded version (pdf | supplement | poster | bib)

Feel free to contact us if you need additional information or source code. Please note that this is a dynamic website that is frequently updated.


new! Code for 3D Curve Sketch now available! new!
new! CVPR 2017 paper "The Surfacing of Multiview 3D Drawings via Lofting.." accepted! new!


3D Curve Sketch

3D Curve Drawing


We have devised a number of datasets for curve-based multiview reconstruction and camera estimation algorithms, described in further detail at the end of this webpage.

See Also

Barcelona Pavillion Dataset

The first publicly available, realistic 3D curve ground truth dataset to be used in the evaluation of curve-based multiview stereo and camera estimation algorithms.

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Realistic videos rendered under 3 extreme illuminations

Sample frames of three different videos for different illumination conditions

The full curve ground truth and a useful bounding box

Mesh edges are deleted to make the desired ground truth edges explicit

Even minute objects were modeled by discarding internal mesh edges (blue below)

Camera path (blue) used to render the videos and generate ground-truth cameras

Video Samples for the Chair Sequence

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The Barcelona Pavillion is a realistic synthetic dataset we created for validating curve-based 3D SfM and stereo algorithms with control over illumination, geometry and cameras. Non-curve-based multiview stereo and SfM algorithms also benefit from this dataset, as we provide full detailed mesh ground truth.

The dataset consists of:

Vase Dataset

Real data obtained from manually marking edges on structured light scans.

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This real curve 3D groundtruth is constructed by manually deleting points of a dense point cloud obtained from structured lighting. Using the point cloud alone, the 3D edges are not identifiable with confidence. Therefore, we reproject the dense point cloud scan onto reference images during editing for disam biguating edges. The unstructured point cloud from structured lighting tends to suffer from oversmoothing, and lacks structure near edges, which we recover from the reference images registered using the ground truth camera parameters.

Red points near edges obtained from structured lighting registered to images

Points from the 3D scan that are on homogeneous regions are manually deleted. The selected points to be deleted are shown in yellow simultaneously in reference views and on the 3D scan itself, so that with confidence we know its not an edge

Cameras corresponding to the reference views (left) and zoom into the deletion process

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Synthetic Curves Dataset

Amsterdam House Dataset

coming soon!

Capitol High Dataset

coming soon!