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Unsupervised Deep Single‐Image Intrinsic Decomposition using Illumination‐Varying Image Sequences
(2018)Computer Graphics ForumMachine learning based Single Image Intrinsic Decomposition (SIID) methods decompose a captured scene into its albedo and shading images by using the knowledge of a large set of known and realistic ground truth decompositions. Collecting and annotating such a dataset is an approach that cannot scale to sufficient variety and realism. We free ourselves from this limitation by training on unannotated images. Our method leverages the observation ...Conference Paper -
WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionPeople detection methods are highly sensitive to occlusions between pedestrians, which are extremely frequent in many situations where cameras have to be mounted at a limited height. The reduction of camera prices allows for the generalization of static multi-camera set-ups. Using joint visual information from multiple synchronized cameras gives the opportunity to improve detection performance. In this paper, we present a new large-scale ...Conference Paper -
DARN: a Deep Adversarial Residual Network for Intrinsic Image Decomposition
(2018)2018 IEEE Winter Conference on Applications of Computer Vision (WACV)Conference Paper