{"scene_parsing": {"description": "Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed.\nMIT Scene Parsing Benchmark (SceneParse150) provides a standard training and evaluation platform for the algorithms of scene parsing.\nThe data for this benchmark comes from ADE20K Dataset which contains more than 20K scene-centric images exhaustively annotated with objects and object parts.\nSpecifically, the benchmark is divided into 20K images for training, 2K images for validation, and another batch of held-out images for testing.\nThere are totally 150 semantic categories included for evaluation, which include stuffs like sky, road, grass, and discrete objects like person, car, bed.\nNote that there are non-uniform distribution of objects occuring in the images, mimicking a more natural object occurrence in daily scene.\n", "citation": "@inproceedings{zhou2017scene,\n    title={Scene Parsing through ADE20K Dataset},\n    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},\n    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},\n    year={2017}\n}\n\n@article{zhou2016semantic,\n  title={Semantic understanding of scenes through the ade20k dataset},\n  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},\n  journal={arXiv preprint arXiv:1608.05442},\n  year={2016}\n}\n", "homepage": "http://sceneparsing.csail.mit.edu/", "license": "BSD 3-Clause License", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "annotation": {"decode": true, "id": null, "_type": "Image"}, "scene_category": {"num_classes": 1055, "names": ["airport_terminal", "art_gallery", "badlands", "ball_pit", "bathroom", "beach", "bedroom", "booth_indoor", "botanical_garden", "bridge", "bullring", "bus_interior", "butte", "canyon", 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"abbey", "access_road", "air_base", "airfield", "airlock", "airplane_cabin", "airport", "entrance", "airport_ticket_counter", "alcove", "alley", "amphitheater", "amusement_arcade", "amusement_park", "anechoic_chamber", "apartment_building_outdoor", "apse_indoor", "apse_outdoor", "aquarium", "aquatic_theater", "aqueduct", "arcade", "arch", "archaelogical_excavation", "archive", "basketball", "football", "hockey", "performance", "rodeo", "soccer", "armory", "army_base", "arrival_gate_indoor", "arrival_gate_outdoor", "art_school", "art_studio", "artists_loft", "assembly_line", "athletic_field_indoor", "athletic_field_outdoor", "atrium_home", "atrium_public", "attic", "auditorium", "auto_factory", "auto_mechanics_indoor", "auto_mechanics_outdoor", "auto_racing_paddock", "auto_showroom", "backstage", "backstairs", "badminton_court_indoor", "badminton_court_outdoor", "baggage_claim", "shop", "exterior", "balcony_interior", "ballroom", "bamboo_forest", "bank_indoor", "bank_outdoor", "bank_vault", "banquet_hall", "baptistry_indoor", "baptistry_outdoor", "bar", "barbershop", "barn", "barndoor", "barnyard", "barrack", "baseball_field", "basement", "basilica", "basketball_court_indoor", "basketball_court_outdoor", "bathhouse", "batters_box", "batting_cage_indoor", "batting_cage_outdoor", "battlement", "bayou", "bazaar_indoor", "bazaar_outdoor", "beach_house", "beauty_salon", "bedchamber", "beer_garden", "beer_hall", "belfry", "bell_foundry", "berth", "berth_deck", "betting_shop", "bicycle_racks", "bindery", "biology_laboratory", "bistro_indoor", "bistro_outdoor", "bleachers_indoor", "bleachers_outdoor", "boardwalk", "boat_deck", "boathouse", "bog", "bomb_shelter_indoor", "bookbindery", "bookstore", "bow_window_indoor", "bow_window_outdoor", "bowling_alley", "box_seat", "boxing_ring", "breakroom", "brewery_indoor", "brewery_outdoor", "brickyard_indoor", "brickyard_outdoor", "building_complex", "building_facade", "bullpen", "burial_chamber", "bus_depot_indoor", 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"coast_road", "cockpit", "coffee_shop", "computer_room", "conference_center", "conference_hall", "confessional", "control_room", "control_tower_indoor", "control_tower_outdoor", "convenience_store_indoor", "convenience_store_outdoor", "corn_field", "cottage", "cottage_garden", "courthouse", "courtroom", "courtyard", "covered_bridge_interior", "crawl_space", "creek", "crevasse", "library", "cybercafe", "dacha", "dairy_indoor", "dairy_outdoor", "dam", "dance_school", "darkroom", "delicatessen", "dentists_office", "department_store", "departure_lounge", "vegetation", "desert_road", "diner_indoor", "diner_outdoor", "dinette_home", "vehicle", "dining_car", "dining_hall", "dining_room", "dirt_track", "discotheque", "distillery", "ditch", "dock", "dolmen", "donjon", "doorway_indoor", "doorway_outdoor", "dorm_room", "downtown", "drainage_ditch", "dress_shop", "dressing_room", "drill_rig", "driveway", "driving_range_indoor", "driving_range_outdoor", "drugstore", "dry_dock", "dugout", 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