ETHZ CVL RueMonge 2014

by No License

ETHZ CVL RueMonge 2014

This ETHZ CVL RueMonge 2014 dataset used for 3D reconstruction and semantic mesh labelling for urban scene understanding.It was first published in [1] and please cite[1] if you use any of its data or source code.[1] Learning Where To Classify In Multi-View Semantic Segmentation, H. Riemenschneider, A. Bodis-Szomoru, J. Weissenberg, L. Van Gool, ECCV 2014The dataset comes with the following data:2D images for training and testing, labelled in 8 classes3D mesh (faces, vertices) as a 3D representationIndex files for faces to pixels in each imageTraining / testing splits as txt filesSample files for classification resultsSample source code for loading and evaluation (see below)This sample source code allows the following functionsEvaluate 2D/3D labeling results by (classwise or PASCAL IOU) accuracy.Examples for loading 2D image data into the 3D mesh (color, labels, probabilities)Fusion of multiview data by the SUMALL principle (see paper)Mesh labelling optimization via a graphcut approach.Various helper toolsThis dataset allows the evaluation of semantic classification methods in the following tasks:TASK 1 - Image Labelling - vanilla 2d img labelling taskTASK 2 - Mesh Labelling - collect or reason in 3d to label meshTASK 3 - Pointcloud Labelling - collect or reason in 3d to label point cloud / meshTASK 4 - View selection - reason which images to skip for features & classification via view reduction (ECCV paper)TASK 5 - Scene Coverage - reason which images to skip for features & classification via scene coverage (ECCV paper)The protocol for training / testing is:2D Training images are 113 files in 2D (see above: north side)2D Testing images are the 119 (labelled) images (south side) (on pixel level)3D Training images are 113 files (see above: north side)3D Testing images are 119 (labelled) and 202 RGB images (south side) (on mesh face)http://varcity.eu/3dchallenge/

Dataset Attributes

Label SVG
Categories3D, Reconstruction, Architecture, Paris, Benchmark, Source, Code, Urban, Outdoor, Pointcloud, Mesh