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Facebook Reality Labs has launched the Scene Understanding and Modeling (SUMO) Challenge, which targets development of comprehensive 3D scene understanding and modeling algorithms. The challenge has been developed by a team of computer vision researchers at
Facebook together with collaborators from Stanford, Princeton and Virginia Tech.
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The goal of the SUMO challenge is to generate an instance-based 3D representation of an indoor scene given only a 360-degree RGB-D image taken from a single viewpoint. The generated scene is modeled by a collection of elements, each of which represents one
object, such as a wall, the floor, or a chair. <br>
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Participants can join in any of the three increasingly detailed and difficult performance tracks: the bounding boxes track, in which the scene is represented by a collection of oriented bounding boxes; the voxels track, where the scene is a collection of oriented
voxel grids; and the meshes track, where the scene is a collection of textured surface meshes.
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Participants will be evaluated on their ability to consistently infer the correct geometry, pose, appearance and semantics of the elements in each scene.<br>
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The challenge will run until November 16th, 2018. The top winners in each track will receive prizes, including cash rewards and NVIDIA Titan X GPUs. Winners will be announced at the SUMO Challenge Workshop on December 2nd at ACCV 2018, where they will present
their results.<br>
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For more information, visit the <a href="https://sumochallenge.org/">SUMO Challenge web site</a>.
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