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"this kitchen seems to have been burnt all appliances are burned",
"A dirty and very dark and scary kitchen. ",
"a kitchen that has some stoves in it"
] | an old dirty kitchen with a stove and oven | 0.625 |
|
d73295935b243a57f922ca2ddccaacfc | [
"A man wearing ties and rainbow sun glasses",
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"The man smiles wearing two colorful ties and oversized glasses.",
"A man with a large tie, a hat, and sunglasses.",
"A laughing German man at a party wearing ridiculous ties and sunglasses hams it up for the camera. "
] | a man wearing a tie | 0.4375 |
|
2ad4b325f0d41815ed95c493fbb139b8 | [
"A woman wading through water holding a surfboard.",
"A woman carries a surfboard into the ocean.",
"there are many surfers riding waves in the water",
"A woman carrying a surfboard out into the ocean.",
"A couple of people on surf boards on a beach."
] | a woman in a wet suit carrying a surfboard into the ocean. | 0.9 |
|
c863a56d86011f678a4f505504cd0283 | [
"A red living room filled with furniture and two windows.",
"A living room painted red with black couches and coffee tables",
"A living room with red walls and dark furniture, with light streaming in two windows.",
"A view of a room that has two windows and a blue couch.",
"A modern living room with very unique furniture."
] | a living room with a couch and a coffee table | 1 |
|
bb767a94d427d52ba8d93fb5cdfd2405 | [
"A zebra in captivity grazing in its exhibit.",
"The zebra is eating grass in his habitat.",
"A zebra grazing in an enclosure with trees in the background.",
"A zebra brazing on green grass next to a pile of rocks.",
"A zebra eating grass inside a fenced in area. "
] | a black and white photo of a bathroom | 0 |
|
e6ffec2517e90649b09c03066b6c5795 | [
"MTA F train comes rolling through the bridge tracks.",
"A gray and black train passing under a metal tunnel.",
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"A train on a track under a metal archway.",
"An American commuter train crossing a city bridge"
] | a train is going under a bridge in a city | 1 |
|
f2ef4c9d634a53a8b510b328110bdbe1 | [
"A man riding skis down a snow covered ski slope.",
"Man skiing in a black coat down a snowy mountain.",
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"a man skiing by himself through the snow",
"A snow skier is going through the glassy snow."
] | a man riding skis down a snowy slope | 1 |
|
39869768fc9d15c10b36c7fac43a4d3c | [
"Two motorbikes outside of a glass window with a bike next to them.",
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"THREE MOTORCYCLES PARKED OUTSIDE OF A STORE FRONT.",
"Two motorcycles parked outside a building on a busy street.",
"two motorcycles and a bicycle and some windows"
] | a couple of motorcycles parked next to each other | 0.714286 |
|
a252224ca0cc729b54691eddfea84f0e | [
"A bathroom showing the bathtub and the sink and mirror.",
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"A simple bathroom with tile surrounds and green floor."
] | a bathroom with a sink and a bathtub | 0.75 |
|
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"A man is sitting on top of an elephant in the water."
] | a man riding on top of an elephant in the water | 0.7 |
|
a86fd5cbad09f061242424c8638741e8 | [
"The view of a bathroom with a wall mounted sink.",
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"A white sink in a small, tiled bathroom."
] | three dogs laying on a bed in a room | 0 |
|
056c3d8422340e9586c11b6dd9b194ac | [
"A couple sitting on the back of a flatbed holding a dog.",
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] | a silver chain link fence | 0 |
|
6aaf8a84a2199d549c05c5c81c8ee1a8 | [
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] | a beach with many people and buildings in the background. | 0.5 |
|
03cf9414e8242926d74f375f3b3fe4eb | [
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"a man on a surfboard surfing a wave"
] | a man riding a wave on a surfboard in the ocean | 0.75 |
|
906210ce9b117943c3173a160387b266 | [
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"A nicely manicured yard with rows of flowers going up a hill.",
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] | a tree in a field | 0.5 |
|
81b3364f3896faa98a3427b645ef1d96 | [
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] | a white plate topped with mashed potatoes, carrots and gravy | 1 |
|
756d98609f28d7025f511a5ba66b0a1e | [
"A snowboard sitting on a hard wood floor.",
"A SKATE BOARD WITH PANANADS ON IT ",
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] | a skateboard with a picture of a panda on it | 0.5 |
|
0a27a2450a93babb60dddaf3cd473f31 | [
"A clock reads almost 3 o clock above a dining room table",
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|
c0431f1ab0da3c1b3afaf299273219ac | [
"Many sail boats sail through the water in a row",
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] | a black and white bird standing on the ground | 0 |
|
d2a7ec90b45c2626986e7bcc2387cad8 | [
"A counter filled with fried donuts line up in rows.",
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|
eb1998f7a80d7273a2ed708a1f01af24 | [
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] | a woman is riding two dolphins in a pool | 0.75 |
|
a20737ed7d44683b75428ad2de176d9d | [
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] | a herd of sheep grazing on a lush green field. | 1 |
|
d95371dc6835590ab3dac0472af51a95 | [
"People at a museum looking at some pottery",
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] | a man wearing glasses | 0.75 |
|
1ecc28bd449e8e3da1497d0fd793e6c2 | [
"A bathroom with a glassed in tub, toilet and sink",
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] | this is a bathroom | 1 |
|
896f3bb18a7f10a2c51b092d047b5748 | [
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"A person drying a paper mache ball with a blow dryer.",
"Person doing crafts with a hair dryer and newspapers."
] | a person using a blow dryer on a paper ball | 0.7 |
|
2f9001d06708f18142635e923155f954 | [
"Two boys with glove and helmet playing baseball",
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"A boy in a blue tries to catch a baseball while a boy with a red helmet slides to touch the base.",
"A man standing next to a base holding a catchers mitt."
] | a couple of women standing in front of an oven | 0 |
|
49cc06aa5f84b06fe845cafad7aab6b9 | [
"A woman is wearing a dress and standing next to a man and a white car.",
"A bride and a groom standing beside a car l",
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"A woman and a man standing next to a car",
"A bride andgroom are standing next to their wedding car.",
"a couple with a car on a black and white picture",
"A bride and groom resting on a car on their wedding day .",
"A bride and groom pose outside of a vintage car.",
"A bride in a beautiful gown and her groom lean against their gayly decorated luxury car.",
"A man and a woman dressing in wedding clothes lean against a vintage car."
] | a black and white photo of a bride and groom posing next to a car | 0.892857 |
|
af17d2c3060bedda46c2df865ac0bf52 | [
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] | a group of people sitting on the grass holding sandwiches | 0.5 |
|
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] | a keyboard that is sitting on a table | 0.625 |
|
00aea5741c6a6b6f806e97428a1b66ff | [
"A woman standing in the grass with tattoos on her legs.",
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"A group of people's legs, with one person's legs featuring writing",
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"Woman with a black skirt with skin graffiti on back legs ",
"The tattoos really stand out for all to see.",
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] | the legs of a woman | 0.75 |
|
da998a1c4dba9455013d1c0008a094d6 | [
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] | a pile of blue and white fruit sitting on a table | 0.3125 |
|
c36a40c607ce9856eb3c1b3305df5477 | [
"A man running with a baseball bat in his hand.",
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] | a baseball player is running to first base | 0.5 |
|
cf828817338e9152087466c589324f78 | [
"a white plate with rice carrots and various other food",
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] | a bowl of rice and vegetables. | 1 |
|
b7159d2fd13f8e474af69613ed6e9e92 | [
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"A fireplace in a house with shelves on either sides.",
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] | a person riding a snowboard in the snow | 0 |
|
8dcf03ab9a9cf8cb677d77d72298a643 | [
"A group of children eat cake with adults standing in the background.",
"Three girls eating cake with group of people in the background.",
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"children eating cake before a green table clothed table."
] | a black purse sitting on top of a white table. | 0 |
|
719fd3e0510facf063d35e9307951a85 | [
"A person riding skis across a snow covered hillside.",
"a man in all black skiing on the snow",
"A person in black jacket cross country skiing up a hill.",
"A man is going up a snowy hill on skis.",
"A bunch of people that are cross country skiing up a curved trail."
] | a person riding skis down a snow covered hill | 0.678571 |
|
efb18ef2e354b2f998c25d2a5a2193df | [
"A pair of fathers and sons playing outdoors in the daytime.",
"a group of children are outside playing in the grass",
"A group of people on a grass field.",
"THERE ARE CHLDREN OUT ON THE GRASS PLAYING GAMES",
"A group of people standing on top of a lush green field."
] | a group of people standing on top of a lush green field. | 0.714286 |
End of preview. Expand
in Data Studio
Nebula Dataset
[ACCV 2024] DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioning
Usage
>>> from datasets import load_dataset
>>> nebula = load_dataset("Ka2ukiMatsuda/Nebula")
>>> print(nebula)
DatasetDict({
train: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 26382
})
valid: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 3298
})
test: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 3298
})
})
Citation
@inproceedings{matsuda2024deneb,
title={DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioning},
author={Kazuki Matsuda and Yuiga Wada and Komei Sugiura},
booktitle={Proceedings of the Asian Conference on Computer Vision (ACCV)},
year={2024},
pages={3570--3586}
}
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