The GaTech VideoContext dataset consists of over 100 groundtruth annotated outdoor videos with over 20000 frames for the task of geometric context evaluation in videos. The idea is to classify each pixel in the video stream as one of six geometric classes (sky, porous, ground, solid, object, mix). To further scale beyond this dataset, we propose a semi-supervised learning framework to expand the pool of labeled data with high confidence predictions obtained from unlabeled data. @article{VideoGeometricContext2013, author = {S. Hussain Raza and Matthias Grundmann and Irfan Essa}, title = {Geometric Context from Video}, journal = {IEEE CVPR}, year = {2013}, }

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