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ResearchDoom and CocoDoom: Learning Computer Vision with Games

2016-10-07 · A. Mahendran, H. Bilen, J. F. Henriques, A. Vedaldi

In this short note we introduce ResearchDoom, an implementation of the Doom first-person shooter that can extract detailed metadata from the game. We also introduce the CocoDoom dataset, a collection of pre-recorded data extracted from Doom gaming sessions along with annotations in the MS Coco format. ResearchDoom and CocoDoom can be used to train and evaluate a variety of computer vision methods such as object recognition, detection and segmentation at the level of instances and categories, tracking, ego-motion estimation, monocular depth estimation and scene segmentation. The code and data are available at http://www.robots.ox.ac.uk/~vgg/research/researchdoom.

📄 PDF Abstract BibTeX arXiv:1610.02431

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Tasks

Depth EstimationMonocular Depth EstimationMotion EstimationObject RecognitionScene SegmentationSegmentation

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