|
--- |
|
dataset_info: |
|
features: |
|
- name: image |
|
dtype: |
|
image: |
|
mode: RGB |
|
- name: label |
|
dtype: |
|
class_label: |
|
names: |
|
'0': /a/abbey |
|
'1': /a/airplane_cabin |
|
'2': /a/airport_terminal |
|
'3': /a/alley |
|
'4': /a/amphitheater |
|
'5': /a/amusement_arcade |
|
'6': /a/amusement_park |
|
'7': /a/anechoic_chamber |
|
'8': /a/apartment_building/outdoor |
|
'9': /a/apse/indoor |
|
'10': /a/aquarium |
|
'11': /a/aqueduct |
|
'12': /a/arch |
|
'13': /a/archive |
|
'14': /a/arrival_gate/outdoor |
|
'15': /a/art_gallery |
|
'16': /a/art_school |
|
'17': /a/art_studio |
|
'18': /a/assembly_line |
|
'19': /a/athletic_field/outdoor |
|
'20': /a/atrium/public |
|
'21': /a/attic |
|
'22': /a/auditorium |
|
'23': /a/auto_factory |
|
'24': /b/badlands |
|
'25': /b/badminton_court/indoor |
|
'26': /b/baggage_claim |
|
'27': /b/bakery/shop |
|
'28': /b/balcony/exterior |
|
'29': /b/balcony/interior |
|
'30': /b/ball_pit |
|
'31': /b/ballroom |
|
'32': /b/bamboo_forest |
|
'33': /b/banquet_hall |
|
'34': /b/bar |
|
'35': /b/barn |
|
'36': /b/barndoor |
|
'37': /b/baseball_field |
|
'38': /b/basement |
|
'39': /b/basilica |
|
'40': /b/basketball_court/outdoor |
|
'41': /b/bathroom |
|
'42': /b/batters_box |
|
'43': /b/bayou |
|
'44': /b/bazaar/indoor |
|
'45': /b/bazaar/outdoor |
|
'46': /b/beach |
|
'47': /b/beauty_salon |
|
'48': /b/bedroom |
|
'49': /b/berth |
|
'50': /b/biology_laboratory |
|
'51': /b/bistro/indoor |
|
'52': /b/boardwalk |
|
'53': /b/boat_deck |
|
'54': /b/boathouse |
|
'55': /b/bookstore |
|
'56': /b/booth/indoor |
|
'57': /b/botanical_garden |
|
'58': /b/bow_window/indoor |
|
'59': /b/bow_window/outdoor |
|
'60': /b/bowling_alley |
|
'61': /b/boxing_ring |
|
'62': /b/brewery/indoor |
|
'63': /b/bridge |
|
'64': /b/building_facade |
|
'65': /b/bullring |
|
'66': /b/burial_chamber |
|
'67': /b/bus_interior |
|
'68': /b/butchers_shop |
|
'69': /b/butte |
|
'70': /c/cabin/outdoor |
|
'71': /c/cafeteria |
|
'72': /c/campsite |
|
'73': /c/campus |
|
'74': /c/canal/natural |
|
'75': /c/canal/urban |
|
'76': /c/candy_store |
|
'77': /c/canyon |
|
'78': /c/car_interior/backseat |
|
'79': /c/car_interior/frontseat |
|
'80': /c/carrousel |
|
'81': /c/casino/indoor |
|
'82': /c/castle |
|
'83': /c/catacomb |
|
'84': /c/cathedral/indoor |
|
'85': /c/cathedral/outdoor |
|
'86': /c/cavern/indoor |
|
'87': /c/cemetery |
|
'88': /c/chalet |
|
'89': /c/cheese_factory |
|
'90': /c/chemistry_lab |
|
'91': /c/chicken_coop/indoor |
|
'92': /c/chicken_coop/outdoor |
|
'93': /c/childs_room |
|
'94': /c/church/indoor |
|
'95': /c/church/outdoor |
|
'96': /c/classroom |
|
'97': /c/clean_room |
|
'98': /c/cliff |
|
'99': /c/cloister/indoor |
|
'100': /c/closet |
|
'101': /c/clothing_store |
|
'102': /c/coast |
|
'103': /c/cockpit |
|
'104': /c/coffee_shop |
|
'105': /c/computer_room |
|
'106': /c/conference_center |
|
'107': /c/conference_room |
|
'108': /c/construction_site |
|
'109': /c/control_room |
|
'110': /c/control_tower/outdoor |
|
'111': /c/corn_field |
|
'112': /c/corral |
|
'113': /c/corridor |
|
'114': /c/cottage_garden |
|
'115': /c/courthouse |
|
'116': /c/courtroom |
|
'117': /c/courtyard |
|
'118': /c/covered_bridge/exterior |
|
'119': /c/creek |
|
'120': /c/crevasse |
|
'121': /c/crosswalk |
|
'122': /c/cubicle/office |
|
'123': /d/dam |
|
'124': /d/delicatessen |
|
'125': /d/dentists_office |
|
'126': /d/desert/sand |
|
'127': /d/desert/vegetation |
|
'128': /d/diner/indoor |
|
'129': /d/diner/outdoor |
|
'130': /d/dinette/home |
|
'131': /d/dinette/vehicle |
|
'132': /d/dining_car |
|
'133': /d/dining_room |
|
'134': /d/discotheque |
|
'135': /d/dock |
|
'136': /d/doorway/outdoor |
|
'137': /d/dorm_room |
|
'138': /d/driveway |
|
'139': /d/driving_range/outdoor |
|
'140': /d/drugstore |
|
'141': /e/electrical_substation |
|
'142': /e/elevator/door |
|
'143': /e/elevator/interior |
|
'144': /e/elevator_shaft |
|
'145': /e/engine_room |
|
'146': /e/escalator/indoor |
|
'147': /e/excavation |
|
'148': /f/factory/indoor |
|
'149': /f/fairway |
|
'150': /f/fastfood_restaurant |
|
'151': /f/field/cultivated |
|
'152': /f/field/wild |
|
'153': /f/fire_escape |
|
'154': /f/fire_station |
|
'155': /f/firing_range/indoor |
|
'156': /f/fishpond |
|
'157': /f/florist_shop/indoor |
|
'158': /f/food_court |
|
'159': /f/forest/broadleaf |
|
'160': /f/forest/needleleaf |
|
'161': /f/forest_path |
|
'162': /f/forest_road |
|
'163': /f/formal_garden |
|
'164': /f/fountain |
|
'165': /g/galley |
|
'166': /g/game_room |
|
'167': /g/garage/indoor |
|
'168': /g/garbage_dump |
|
'169': /g/gas_station |
|
'170': /g/gazebo/exterior |
|
'171': /g/general_store/indoor |
|
'172': /g/general_store/outdoor |
|
'173': /g/gift_shop |
|
'174': /g/golf_course |
|
'175': /g/greenhouse/indoor |
|
'176': /g/greenhouse/outdoor |
|
'177': /g/gymnasium/indoor |
|
'178': /h/hangar/indoor |
|
'179': /h/hangar/outdoor |
|
'180': /h/harbor |
|
'181': /h/hayfield |
|
'182': /h/heliport |
|
'183': /h/herb_garden |
|
'184': /h/highway |
|
'185': /h/hill |
|
'186': /h/home_office |
|
'187': /h/hospital |
|
'188': /h/hospital_room |
|
'189': /h/hot_spring |
|
'190': /h/hot_tub/outdoor |
|
'191': /h/hotel/outdoor |
|
'192': /h/hotel_room |
|
'193': /h/house |
|
'194': /h/hunting_lodge/outdoor |
|
'195': /i/ice_cream_parlor |
|
'196': /i/ice_floe |
|
'197': /i/ice_shelf |
|
'198': /i/ice_skating_rink/indoor |
|
'199': /i/ice_skating_rink/outdoor |
|
'200': /i/iceberg |
|
'201': /i/igloo |
|
'202': /i/industrial_area |
|
'203': /i/inn/outdoor |
|
'204': /i/islet |
|
'205': /j/jacuzzi/indoor |
|
'206': /j/jail/indoor |
|
'207': /j/jail_cell |
|
'208': /j/jewelry_shop |
|
'209': /k/kasbah |
|
'210': /k/kennel/indoor |
|
'211': /k/kennel/outdoor |
|
'212': /k/kindergarden_classroom |
|
'213': /k/kitchen |
|
'214': /k/kitchenette |
|
'215': /l/labyrinth/outdoor |
|
'216': /l/lake/natural |
|
'217': /l/landfill |
|
'218': /l/landing_deck |
|
'219': /l/laundromat |
|
'220': /l/lecture_room |
|
'221': /l/library/indoor |
|
'222': /l/library/outdoor |
|
'223': /l/lido_deck/outdoor |
|
'224': /l/lift_bridge |
|
'225': /l/lighthouse |
|
'226': /l/limousine_interior |
|
'227': /l/living_room |
|
'228': /l/lobby |
|
'229': /l/lock_chamber |
|
'230': /l/locker_room |
|
'231': /m/mansion |
|
'232': /m/manufactured_home |
|
'233': /m/market/indoor |
|
'234': /m/market/outdoor |
|
'235': /m/marsh |
|
'236': /m/martial_arts_gym |
|
'237': /m/mausoleum |
|
'238': /m/medina |
|
'239': /m/moat/water |
|
'240': /m/monastery/outdoor |
|
'241': /m/mosque/indoor |
|
'242': /m/mosque/outdoor |
|
'243': /m/motel |
|
'244': /m/mountain |
|
'245': /m/mountain_snowy |
|
'246': /m/movie_theater/indoor |
|
'247': /m/museum/indoor |
|
'248': /m/music_store |
|
'249': /m/music_studio |
|
'250': /n/nuclear_power_plant/outdoor |
|
'251': /n/nursery |
|
'252': /o/oast_house |
|
'253': /o/observatory/outdoor |
|
'254': /o/ocean |
|
'255': /o/office |
|
'256': /o/office_building |
|
'257': /o/oil_refinery/outdoor |
|
'258': /o/oilrig |
|
'259': /o/operating_room |
|
'260': /o/orchard |
|
'261': /o/outhouse/outdoor |
|
'262': /p/pagoda |
|
'263': /p/palace |
|
'264': /p/pantry |
|
'265': /p/park |
|
'266': /p/parking_garage/indoor |
|
'267': /p/parking_garage/outdoor |
|
'268': /p/parking_lot |
|
'269': /p/parlor |
|
'270': /p/pasture |
|
'271': /p/patio |
|
'272': /p/pavilion |
|
'273': /p/pharmacy |
|
'274': /p/phone_booth |
|
'275': /p/physics_laboratory |
|
'276': /p/picnic_area |
|
'277': /p/pilothouse/indoor |
|
'278': /p/planetarium/outdoor |
|
'279': /p/playground |
|
'280': /p/playroom |
|
'281': /p/plaza |
|
'282': /p/podium/indoor |
|
'283': /p/podium/outdoor |
|
'284': /p/pond |
|
'285': /p/poolroom/establishment |
|
'286': /p/poolroom/home |
|
'287': /p/power_plant/outdoor |
|
'288': /p/promenade_deck |
|
'289': /p/pub/indoor |
|
'290': /p/pulpit |
|
'291': /p/putting_green |
|
'292': /r/racecourse |
|
'293': /r/raceway |
|
'294': /r/raft |
|
'295': /r/railroad_track |
|
'296': /r/rainforest |
|
'297': /r/reception |
|
'298': /r/recreation_room |
|
'299': /r/residential_neighborhood |
|
'300': /r/restaurant |
|
'301': /r/restaurant_kitchen |
|
'302': /r/restaurant_patio |
|
'303': /r/rice_paddy |
|
'304': /r/riding_arena |
|
'305': /r/river |
|
'306': /r/rock_arch |
|
'307': /r/rope_bridge |
|
'308': /r/ruin |
|
'309': /r/runway |
|
'310': /s/sandbar |
|
'311': /s/sandbox |
|
'312': /s/sauna |
|
'313': /s/schoolhouse |
|
'314': /s/sea_cliff |
|
'315': /s/server_room |
|
'316': /s/shed |
|
'317': /s/shoe_shop |
|
'318': /s/shopfront |
|
'319': /s/shopping_mall/indoor |
|
'320': /s/shower |
|
'321': /s/skatepark |
|
'322': /s/ski_lodge |
|
'323': /s/ski_resort |
|
'324': /s/ski_slope |
|
'325': /s/sky |
|
'326': /s/skyscraper |
|
'327': /s/slum |
|
'328': /s/snowfield |
|
'329': /s/squash_court |
|
'330': /s/stable |
|
'331': /s/stadium/baseball |
|
'332': /s/stadium/football |
|
'333': /s/stage/indoor |
|
'334': /s/staircase |
|
'335': /s/street |
|
'336': /s/subway_interior |
|
'337': /s/subway_station/platform |
|
'338': /s/supermarket |
|
'339': /s/sushi_bar |
|
'340': /s/swamp |
|
'341': /s/swimming_pool/indoor |
|
'342': /s/swimming_pool/outdoor |
|
'343': /s/synagogue/indoor |
|
'344': /s/synagogue/outdoor |
|
'345': /t/television_studio |
|
'346': /t/temple/east_asia |
|
'347': /t/temple/south_asia |
|
'348': /t/tennis_court/indoor |
|
'349': /t/tennis_court/outdoor |
|
'350': /t/tent/outdoor |
|
'351': /t/theater/indoor_procenium |
|
'352': /t/theater/indoor_seats |
|
'353': /t/thriftshop |
|
'354': /t/throne_room |
|
'355': /t/ticket_booth |
|
'356': /t/toll_plaza |
|
'357': /t/topiary_garden |
|
'358': /t/tower |
|
'359': /t/toyshop |
|
'360': /t/track/outdoor |
|
'361': /t/train_railway |
|
'362': /t/train_station/platform |
|
'363': /t/tree_farm |
|
'364': /t/tree_house |
|
'365': /t/trench |
|
'366': /u/underwater/coral_reef |
|
'367': /u/utility_room |
|
'368': /v/valley |
|
'369': /v/van_interior |
|
'370': /v/vegetable_garden |
|
'371': /v/veranda |
|
'372': /v/veterinarians_office |
|
'373': /v/viaduct |
|
'374': /v/videostore |
|
'375': /v/village |
|
'376': /v/vineyard |
|
'377': /v/volcano |
|
'378': /v/volleyball_court/indoor |
|
'379': /v/volleyball_court/outdoor |
|
'380': /w/waiting_room |
|
'381': /w/warehouse/indoor |
|
'382': /w/water_tower |
|
'383': /w/waterfall/block |
|
'384': /w/waterfall/fan |
|
'385': /w/waterfall/plunge |
|
'386': /w/watering_hole |
|
'387': /w/wave |
|
'388': /w/wet_bar |
|
'389': /w/wheat_field |
|
'390': /w/wind_farm |
|
'391': /w/windmill |
|
'392': /w/wine_cellar/barrel_storage |
|
'393': /w/wine_cellar/bottle_storage |
|
'394': /w/wrestling_ring/indoor |
|
'395': /y/yard |
|
'396': /y/youth_hostel |
|
splits: |
|
- name: train |
|
num_bytes: 46351432884.22 |
|
num_examples: 108754 |
|
download_size: 39510197247 |
|
dataset_size: 46351432884.22 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
task_categories: |
|
- image-classification |
|
language: |
|
- en |
|
tags: |
|
- princeton |
|
pretty_name: SUN397 |
|
size_categories: |
|
- 100K<n<1M |
|
paperswithcode_id: sun397 |
|
multilinguality: |
|
- monolingual |
|
annotations_creators: |
|
- expert-generated |
|
--- |
|
|
|
# Scene UNderstanding 397 — SUN397 |
|
|
|
[](https://vision.princeton.edu/projects/2010/SUN/) |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [SUN Database: Scene Categorization Benchmark](https://vision.princeton.edu/projects/2010/SUN/) |
|
|
|
## Description |
|
|
|
Scene categorization is a fundamental problem in computer vision. |
|
However, scene understanding research has been constrained by the limited scope of currently-used databases which do not capture the full variety of scene categories. |
|
Whereas standard databases for object categorization contain hundreds of different classes of objects, the largest available dataset of scene categories contains only 15 classes. |
|
In this paper we propose the extensive Scene UNderstanding (SUN) database that contains 899 categories and 130,519 images. |
|
We use 397 well-sampled categories to evaluate numerous state-of-the-art algorithms for scene recognition and establish new bounds of performance. |
|
We measure human scene classification performance on the SUN database and compare this with computational methods. |
|
|
|
## Citations |
|
|
|
```bibtex |
|
@inproceedings{5539970, |
|
title = {SUN database: Large-scale scene recognition from abbey to zoo}, |
|
author = {Xiao, Jianxiong and Hays, James and Ehinger, Krista A. and Oliva, Aude and Torralba, Antonio}, |
|
year = 2010, |
|
booktitle = {2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, |
|
volume = {}, |
|
number = {}, |
|
pages = {3485--3492}, |
|
doi = {10.1109/CVPR.2010.5539970}, |
|
keywords = {Sun;Large-scale systems;Layout;Humans;Image databases;Computer vision;Anthropometry;Bridges;Legged locomotion;Spatial databases} |
|
} |
|
@article{Xiao2014SUNDE, |
|
title = {SUN Database: Exploring a Large Collection of Scene Categories}, |
|
author = {Jianxiong Xiao and Krista A. Ehinger and James Hays and Antonio Torralba and Aude Oliva}, |
|
year = 2014, |
|
journal = {International Journal of Computer Vision}, |
|
volume = 119, |
|
pages = {3--22}, |
|
url = {https://api.semanticscholar.org/CorpusID:10224573} |
|
} |
|
``` |
