ahricat/ONI
Graph Machine Learning
•
Updated
Datasets:
image
imagewidth (px) 74
6.59k
| label
sequencelengths 1
4
| origin
stringclasses 5
values | english_label
sequencelengths 1
4
|
|---|---|---|---|
[
1
] | imagenet_r | [
"goldfish"
] |
|
[
1
] | imagenet_sketch | [
"goldfish"
] |
|
[
2
] | imagenet | [
"great_white_shark"
] |
|
[
2
] | imagenet_r | [
"great_white_shark"
] |
|
[
2
] | imagenet_r | [
"great_white_shark"
] |
|
[
2
] | imagenet_r | [
"great_white_shark"
] |
|
[
3
] | imagenet_sketch | [
"tiger_shark"
] |
|
[
4
] | imagenet_r | [
"hammerhead"
] |
|
[
4
] | imagenet_r | [
"hammerhead"
] |
|
[
4
] | imagenet_r | [
"hammerhead"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet | [
"electric_ray"
] |
|
[
5
] | imagenet_sketch | [
"electric_ray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_r | [
"stingray"
] |
|
[
6
] | imagenet_a | [
"stingray"
] |
|
[
6
] | imagenet_a | [
"stingray"
] |
|
[
6
] | imagenet_a | [
"stingray"
] |
|
[
6
] | imagenet_a | [
"stingray"
] |
|
[
6
] | imagenet_a | [
"stingray"
] |
|
[
6
] | imagenet_sketch | [
"stingray"
] |
|
[
6
] | imagenet_sketch | [
"stingray"
] |
|
[
9
] | imagenet_r | [
"ostrich"
] |
|
[
9
] | imagenet_r | [
"ostrich"
] |
|
[
10
] | imagenet | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
10
] | imagenet_sketch | [
"brambling"
] |
|
[
11
] | imagenet_a | [
"goldfinch"
] |
|
[
11
] | imagenet_sketch | [
"goldfinch"
] |
|
[
11
] | imagenet_sketch | [
"goldfinch"
] |
|
[
11
] | imagenet_sketch | [
"goldfinch"
] |
|
[
11
] | imagenet_sketch | [
"goldfinch"
] |
|
[
11
] | imagenet_sketch | [
"goldfinch"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
|
[
14
] | imagenet_sketch | [
"indigo_bunting"
] |
End of preview. Expand
in Dataset Viewer.
Dataset Card for "ImageNet-Hard"
Project Page - ArXiv - Paper - Github - Image Browser
Dataset Summary
ImageNet-Hard is a new benchmark that comprises 10,980 images collected from various existing ImageNet-scale benchmarks (ImageNet, ImageNet-V2, ImageNet-Sketch, ImageNet-C, ImageNet-R, ImageNet-ReaL, ImageNet-A, and ObjectNet). This dataset poses a significant challenge to state-of-the-art vision models as merely zooming in often fails to improve their ability to classify images correctly. As a result, even the most advanced models, such as CLIP-ViT-L/14@336px, struggle to perform well on this dataset, achieving a mere 2.02% accuracy.
ImageNet-Hard-4K: For the 4K version please refere to this dataset.
Dataset Distribution
Classifiers Performance
| Model | Accuracy |
|---|---|
| AlexNet | 7.34 |
| VGG-16 | 12.00 |
| ResNet-18 | 10.86 |
| ResNet-50 | 14.74 |
| ViT-B/32 | 18.52 |
| EfficientNet-B0 | 16.57 |
| EfficientNet-B7 | 23.20 |
| EfficientNet-L2-Ns | 39.00 |
| CLIP-ViT-L/14@224px | 1.86 |
| CLIP-ViT-L/14@336px | 2.02 |
| OpenCLIP-ViT-bigG-14 | 15.93 |
| OpenCLIP-ViT-L-14 | 15.60 |
Evaluation Code
- CLIP
- OpenCLIP
- Other models
Supported Tasks
image-classification: The objective of this task is to classify an image into one or more classes, selected from 1000 ImageNet categories (allowing for multiple ground-truth labels per image).
Languages
The english_label field in the dataset are in English.
Dataset Structure
Data Instances
An example looks like this:
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=575x409 at 0x7F09456B53A0>,
'label': [0],
'origin': 'imagenet_sketch',
'english_label': ['tench']
}
Data Fields
The data instances have the following fields:
- image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
- label: A List[int] collection containing the ground-truth ids.
- origin: A string containing source dataset.
- english_label: A List[str] collection containg the english labels for the ground-truth classes.
Click here to see the full list of ImageNet class labels mapping:
| id | Class |
|---|---|
| 0 | tench, Tinca tinca |
| 1 | goldfish, Carassius auratus |
| 2 | great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias |
| 3 | tiger shark, Galeocerdo cuvieri |
| 4 | hammerhead, hammerhead shark |
| 5 | electric ray, crampfish, numbfish, torpedo |
| 6 | stingray |
| 7 | cock |
| 8 | hen |
| 9 | ostrich, Struthio camelus |
| 10 | brambling, Fringilla montifringilla |
| 11 | goldfinch, Carduelis carduelis |
| 12 | house finch, linnet, Carpodacus mexicanus |
| 13 | junco, snowbird |
| 14 | indigo bunting, indigo finch, indigo bird, Passerina cyanea |
| 15 | robin, American robin, Turdus migratorius |
| 16 | bulbul |
| 17 | jay |
| 18 | magpie |
| 19 | chickadee |
| 20 | water ouzel, dipper |
| 21 | kite |
| 22 | bald eagle, American eagle, Haliaeetus leucocephalus |
| 23 | vulture |
| 24 | great grey owl, great gray owl, Strix nebulosa |
| 25 | European fire salamander, Salamandra salamandra |
| 26 | common newt, Triturus vulgaris |
| 27 | eft |
| 28 | spotted salamander, Ambystoma maculatum |
| 29 | axolotl, mud puppy, Ambystoma mexicanum |
| 30 | bullfrog, Rana catesbeiana |
| 31 | tree frog, tree-frog |
| 32 | tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui |
| 33 | loggerhead, loggerhead turtle, Caretta caretta |
| 34 | leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea |
| 35 | mud turtle |
| 36 | terrapin |
| 37 | box turtle, box tortoise |
| 38 | banded gecko |
| 39 | common iguana, iguana, Iguana iguana |
| 40 | American chameleon, anole, Anolis carolinensis |
| 41 | whiptail, whiptail lizard |
| 42 | agama |
| 43 | frilled lizard, Chlamydosaurus kingi |
| 44 | alligator lizard |
| 45 | Gila monster, Heloderma suspectum |
| 46 | green lizard, Lacerta viridis |
| 47 | African chameleon, Chamaeleo chamaeleon |
| 48 | Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis |
| 49 | African crocodile, Nile crocodile, Crocodylus niloticus |
| 50 | American alligator, Alligator mississipiensis |
| 51 | triceratops |
| 52 | thunder snake, worm snake, Carphophis amoenus |
| 53 | ringneck snake, ring-necked snake, ring snake |
| 54 | hognose snake, puff adder, sand viper |
| 55 | green snake, grass snake |
| 56 | king snake, kingsnake |
| 57 | garter snake, grass snake |
| 58 | water snake |
| 59 | vine snake |
| 60 | night snake, Hypsiglena torquata |
| 61 | boa constrictor, Constrictor constrictor |
| 62 | rock python, rock snake, Python sebae |
| 63 | Indian cobra, Naja naja |
| 64 | green mamba |
| 65 | sea snake |
| 66 | horned viper, cerastes, sand viper, horned asp, Cerastes cornutus |
| 67 | diamondback, diamondback rattlesnake, Crotalus adamanteus |
| 68 | sidewinder, horned rattlesnake, Crotalus cerastes |
| 69 | trilobite |
| 70 | harvestman, daddy longlegs, Phalangium opilio |
| 71 | scorpion |
| 72 | black and gold garden spider, Argiope aurantia |
| 73 | barn spider, Araneus cavaticus |
| 74 | garden spider, Aranea diademata |
| 75 | black widow, Latrodectus mactans |
| 76 | tarantula |
| 77 | wolf spider, hunting spider |
| 78 | tick |
| 79 | centipede |
| 80 | black grouse |
| 81 | ptarmigan |
| 82 | ruffed grouse, partridge, Bonasa umbellus |
| 83 | prairie chicken, prairie grouse, prairie fowl |
| 84 | peacock |
| 85 | quail |
| 86 | partridge |
| 87 | African grey, African gray, Psittacus erithacus |
| 88 | macaw |
| 89 | sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita |
| 90 | lorikeet |
| 91 | coucal |
| 92 | bee eater |
| 93 | hornbill |
| 94 | hummingbird |
| 95 | jacamar |
| 96 | toucan |
| 97 | drake |
| 98 | red-breasted merganser, Mergus serrator |
| 99 | goose |
| 100 | black swan, Cygnus atratus |
| 101 | tusker |
| 102 | echidna, spiny anteater, anteater |
| 103 | platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus |
| 104 | wallaby, brush kangaroo |
| 105 | koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus |
| 106 | wombat |
| 107 | jellyfish |
| 108 | sea anemone, anemone |
| 109 | brain coral |
| 110 | flatworm, platyhelminth |
| 111 | nematode, nematode worm, roundworm |
| 112 | conch |
| 113 | snail |
| 114 | slug |
| 115 | sea slug, nudibranch |
| 116 | chiton, coat-of-mail shell, sea cradle, polyplacophore |
| 117 | chambered nautilus, pearly nautilus, nautilus |
| 118 | Dungeness crab, Cancer magister |
| 119 | rock crab, Cancer irroratus |
| 120 | fiddler crab |
| 121 | king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica |
| 122 | American lobster, Northern lobster, Maine lobster, Homarus americanus |
| 123 | spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish |
| 124 | crayfish, crawfish, crawdad, crawdaddy |
| 125 | hermit crab |
| 126 | isopod |
| 127 | white stork, Ciconia ciconia |
| 128 | black stork, Ciconia nigra |
| 129 | spoonbill |
| 130 | flamingo |
| 131 | little blue heron, Egretta caerulea |
| 132 | American egret, great white heron, Egretta albus |
| 133 | bittern |
| 134 | crane |
| 135 | limpkin, Aramus pictus |
| 136 | European gallinule, Porphyrio porphyrio |
| 137 | American coot, marsh hen, mud hen, water hen, Fulica americana |
| 138 | bustard |
| 139 | ruddy turnstone, Arenaria interpres |
| 140 | red-backed sandpiper, dunlin, Erolia alpina |
| 141 | redshank, Tringa totanus |
| 142 | dowitcher |
| 143 | oystercatcher, oyster catcher |
| 144 | pelican |
| 145 | king penguin, Aptenodytes patagonica |
| 146 | albatross, mollymawk |
| 147 | grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus |
| 148 | killer whale, killer, orca, grampus, sea wolf, Orcinus orca |
| 149 | dugong, Dugong dugon |
| 150 | sea lion |
| 151 | Chihuahua |
| 152 | Japanese spaniel |
| 153 | Maltese dog, Maltese terrier, Maltese |
| 154 | Pekinese, Pekingese, Peke |
| 155 | Shih-Tzu |
| 156 | Blenheim spaniel |
| 157 | papillon |
| 158 | toy terrier |
| 159 | Rhodesian ridgeback |
| 160 | Afghan hound, Afghan |
| 161 | basset, basset hound |
| 162 | beagle |
| 163 | bloodhound, sleuthhound |
| 164 | bluetick |
| 165 | black-and-tan coonhound |
| 166 | Walker hound, Walker foxhound |
| 167 | English foxhound |
| 168 | redbone |
| 169 | borzoi, Russian wolfhound |
| 170 | Irish wolfhound |
| 171 | Italian greyhound |
| 172 | whippet |
| 173 | Ibizan hound, Ibizan Podenco |
| 174 | Norwegian elkhound, elkhound |
| 175 | otterhound, otter hound |
| 176 | Saluki, gazelle hound |
| 177 | Scottish deerhound, deerhound |
| 178 | Weimaraner |
| 179 | Staffordshire bullterrier, Staffordshire bull terrier |
| 180 | American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier |
| 181 | Bedlington terrier |
| 182 | Border terrier |
| 183 | Kerry blue terrier |
| 184 | Irish terrier |
| 185 | Norfolk terrier |
| 186 | Norwich terrier |
| 187 | Yorkshire terrier |
| 188 | wire-haired fox terrier |
| 189 | Lakeland terrier |
| 190 | Sealyham terrier, Sealyham |
| 191 | Airedale, Airedale terrier |
| 192 | cairn, cairn terrier |
| 193 | Australian terrier |
| 194 | Dandie Dinmont, Dandie Dinmont terrier |
| 195 | Boston bull, Boston terrier |
| 196 | miniature schnauzer |
| 197 | giant schnauzer |
| 198 | standard schnauzer |
| 199 | Scotch terrier, Scottish terrier, Scottie |
| 200 | Tibetan terrier, chrysanthemum dog |
| 201 | silky terrier, Sydney silky |
| 202 | soft-coated wheaten terrier |
| 203 | West Highland white terrier |
| 204 | Lhasa, Lhasa apso |
| 205 | flat-coated retriever |
| 206 | curly-coated retriever |
| 207 | golden retriever |
| 208 | Labrador retriever |
| 209 | Chesapeake Bay retriever |
| 210 | German short-haired pointer |
| 211 | vizsla, Hungarian pointer |
| 212 | English setter |
| 213 | Irish setter, red setter |
| 214 | Gordon setter |
| 215 | Brittany spaniel |
| 216 | clumber, clumber spaniel |
| 217 | English springer, English springer spaniel |
| 218 | Welsh springer spaniel |
| 219 | cocker spaniel, English cocker spaniel, cocker |
| 220 | Sussex spaniel |
| 221 | Irish water spaniel |
| 222 | kuvasz |
| 223 | schipperke |
| 224 | groenendael |
| 225 | malinois |
| 226 | briard |
| 227 | kelpie |
| 228 | komondor |
| 229 | Old English sheepdog, bobtail |
| 230 | Shetland sheepdog, Shetland sheep dog, Shetland |
| 231 | collie |
| 232 | Border collie |
| 233 | Bouvier des Flandres, Bouviers des Flandres |
| 234 | Rottweiler |
| 235 | German shepherd, German shepherd dog, German police dog, alsatian |
| 236 | Doberman, Doberman pinscher |
| 237 | miniature pinscher |
| 238 | Greater Swiss Mountain dog |
| 239 | Bernese mountain dog |
| 240 | Appenzeller |
| 241 | EntleBucher |
| 242 | boxer |
| 243 | bull mastiff |
| 244 | Tibetan mastiff |
| 245 | French bulldog |
| 246 | Great Dane |
| 247 | Saint Bernard, St Bernard |
| 248 | Eskimo dog, husky |
| 249 | malamute, malemute, Alaskan malamute |
| 250 | Siberian husky |
| 251 | dalmatian, coach dog, carriage dog |
| 252 | affenpinscher, monkey pinscher, monkey dog |
| 253 | basenji |
| 254 | pug, pug-dog |
| 255 | Leonberg |
| 256 | Newfoundland, Newfoundland dog |
| 257 | Great Pyrenees |
| 258 | Samoyed, Samoyede |
| 259 | Pomeranian |
| 260 | chow, chow chow |
| 261 | keeshond |
| 262 | Brabancon griffon |
| 263 | Pembroke, Pembroke Welsh corgi |
| 264 | Cardigan, Cardigan Welsh corgi |
| 265 | toy poodle |
| 266 | miniature poodle |
| 267 | standard poodle |
| 268 | Mexican hairless |
| 269 | timber wolf, grey wolf, gray wolf, Canis lupus |
| 270 | white wolf, Arctic wolf, Canis lupus tundrarum |
| 271 | red wolf, maned wolf, Canis rufus, Canis niger |
| 272 | coyote, prairie wolf, brush wolf, Canis latrans |
| 273 | dingo, warrigal, warragal, Canis dingo |
| 274 | dhole, Cuon alpinus |
| 275 | African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus |
| 276 | hyena, hyaena |
| 277 | red fox, Vulpes vulpes |
| 278 | kit fox, Vulpes macrotis |
| 279 | Arctic fox, white fox, Alopex lagopus |
| 280 | grey fox, gray fox, Urocyon cinereoargenteus |
| 281 | tabby, tabby cat |
| 282 | tiger cat |
| 283 | Persian cat |
| 284 | Siamese cat, Siamese |
| 285 | Egyptian cat |
| 286 | cougar, puma, catamount, mountain lion, painter, panther, Felis concolor |
| 287 | lynx, catamount |
| 288 | leopard, Panthera pardus |
| 289 | snow leopard, ounce, Panthera uncia |
| 290 | jaguar, panther, Panthera onca, Felis onca |
| 291 | lion, king of beasts, Panthera leo |
| 292 | tiger, Panthera tigris |
| 293 | cheetah, chetah, Acinonyx jubatus |
| 294 | brown bear, bruin, Ursus arctos |
| 295 | American black bear, black bear, Ursus americanus, Euarctos americanus |
| 296 | ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus |
| 297 | sloth bear, Melursus ursinus, Ursus ursinus |
| 298 | mongoose |
| 299 | meerkat, mierkat |
| 300 | tiger beetle |
| 301 | ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle |
| 302 | ground beetle, carabid beetle |
| 303 | long-horned beetle, longicorn, longicorn beetle |
| 304 | leaf beetle, chrysomelid |
| 305 | dung beetle |
| 306 | rhinoceros beetle |
| 307 | weevil |
| 308 | fly |
| 309 | bee |
| 310 | ant, emmet, pismire |
| 311 | grasshopper, hopper |
| 312 | cricket |
| 313 | walking stick, walkingstick, stick insect |
| 314 | cockroach, roach |
| 315 | mantis, mantid |
| 316 | cicada, cicala |
| 317 | leafhopper |
| 318 | lacewing, lacewing fly |
| 319 | dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk |
| 320 | damselfly |
| 321 | admiral |
| 322 | ringlet, ringlet butterfly |
| 323 | monarch, monarch butterfly, milkweed butterfly, Danaus plexippus |
| 324 | cabbage butterfly |
| 325 | sulphur butterfly, sulfur butterfly |
| 326 | lycaenid, lycaenid butterfly |
| 327 | starfish, sea star |
| 328 | sea urchin |
| 329 | sea cucumber, holothurian |
| 330 | wood rabbit, cottontail, cottontail rabbit |
| 331 | hare |
| 332 | Angora, Angora rabbit |
| 333 | hamster |
| 334 | porcupine, hedgehog |
| 335 | fox squirrel, eastern fox squirrel, Sciurus niger |
| 336 | marmot |
| 337 | beaver |
| 338 | guinea pig, Cavia cobaya |
| 339 | sorrel |
| 340 | zebra |
| 341 | hog, pig, grunter, squealer, Sus scrofa |
| 342 | wild boar, boar, Sus scrofa |
| 343 | warthog |
| 344 | hippopotamus, hippo, river horse, Hippopotamus amphibius |
| 345 | ox |
| 346 | water buffalo, water ox, Asiatic buffalo, Bubalus bubalis |
| 347 | bison |
| 348 | ram, tup |
| 349 | bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis |
| 350 | ibex, Capra ibex |
| 351 | hartebeest |
| 352 | impala, Aepyceros melampus |
| 353 | gazelle |
| 354 | Arabian camel, dromedary, Camelus dromedarius |
| 355 | llama |
| 356 | weasel |
| 357 | mink |
| 358 | polecat, fitch, foulmart, foumart, Mustela putorius |
| 359 | black-footed ferret, ferret, Mustela nigripes |
| 360 | otter |
| 361 | skunk, polecat, wood pussy |
| 362 | badger |
| 363 | armadillo |
| 364 | three-toed sloth, ai, Bradypus tridactylus |
| 365 | orangutan, orang, orangutang, Pongo pygmaeus |
| 366 | gorilla, Gorilla gorilla |
| 367 | chimpanzee, chimp, Pan troglodytes |
| 368 | gibbon, Hylobates lar |
| 369 | siamang, Hylobates syndactylus, Symphalangus syndactylus |
| 370 | guenon, guenon monkey |
| 371 | patas, hussar monkey, Erythrocebus patas |
| 372 | baboon |
| 373 | macaque |
| 374 | langur |
| 375 | colobus, colobus monkey |
| 376 | proboscis monkey, Nasalis larvatus |
| 377 | marmoset |
| 378 | capuchin, ringtail, Cebus capucinus |
| 379 | howler monkey, howler |
| 380 | titi, titi monkey |
| 381 | spider monkey, Ateles geoffroyi |
| 382 | squirrel monkey, Saimiri sciureus |
| 383 | Madagascar cat, ring-tailed lemur, Lemur catta |
| 384 | indri, indris, Indri indri, Indri brevicaudatus |
| 385 | Indian elephant, Elephas maximus |
| 386 | African elephant, Loxodonta africana |
| 387 | lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens |
| 388 | giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca |
| 389 | barracouta, snoek |
| 390 | eel |
| 391 | coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch |
| 392 | rock beauty, Holocanthus tricolor |
| 393 | anemone fish |
| 394 | sturgeon |
| 395 | gar, garfish, garpike, billfish, Lepisosteus osseus |
| 396 | lionfish |
| 397 | puffer, pufferfish, blowfish, globefish |
| 398 | abacus |
| 399 | abaya |
| 400 | academic gown, academic robe, judge's robe |
| 401 | accordion, piano accordion, squeeze box |
| 402 | acoustic guitar |
| 403 | aircraft carrier, carrier, flattop, attack aircraft carrier |
| 404 | airliner |
| 405 | airship, dirigible |
| 406 | altar |
| 407 | ambulance |
| 408 | amphibian, amphibious vehicle |
| 409 | analog clock |
| 410 | apiary, bee house |
| 411 | apron |
| 412 | ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin |
| 413 | assault rifle, assault gun |
| 414 | backpack, back pack, knapsack, packsack, rucksack, haversack |
| 415 | bakery, bakeshop, bakehouse |
| 416 | balance beam, beam |
| 417 | balloon |
| 418 | ballpoint, ballpoint pen, ballpen, Biro |
| 419 | Band Aid |
| 420 | banjo |
| 421 | bannister, banister, balustrade, balusters, handrail |
| 422 | barbell |
| 423 | barber chair |
| 424 | barbershop |
| 425 | barn |
| 426 | barometer |
| 427 | barrel, cask |
| 428 | barrow, garden cart, lawn cart, wheelbarrow |
| 429 | baseball |
| 430 | basketball |
| 431 | bassinet |
| 432 | bassoon |
| 433 | bathing cap, swimming cap |
| 434 | bath towel |
| 435 | bathtub, bathing tub, bath, tub |
| 436 | beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon |
| 437 | beacon, lighthouse, beacon light, pharos |
| 438 | beaker |
| 439 | bearskin, busby, shako |
| 440 | beer bottle |
| 441 | beer glass |
| 442 | bell cote, bell cot |
| 443 | bib |
| 444 | bicycle-built-for-two, tandem bicycle, tandem |
| 445 | bikini, two-piece |
| 446 | binder, ring-binder |
| 447 | binoculars, field glasses, opera glasses |
| 448 | birdhouse |
| 449 | boathouse |
| 450 | bobsled, bobsleigh, bob |
| 451 | bolo tie, bolo, bola tie, bola |
| 452 | bonnet, poke bonnet |
| 453 | bookcase |
| 454 | bookshop, bookstore, bookstall |
| 455 | bottlecap |
| 456 | bow |
| 457 | bow tie, bow-tie, bowtie |
| 458 | brass, memorial tablet, plaque |
| 459 | brassiere, bra, bandeau |
| 460 | breakwater, groin, groyne, mole, bulwark, seawall, jetty |
| 461 | breastplate, aegis, egis |
| 462 | broom |
| 463 | bucket, pail |
| 464 | buckle |
| 465 | bulletproof vest |
| 466 | bullet train, bullet |
| 467 | butcher shop, meat market |
| 468 | cab, hack, taxi, taxicab |
| 469 | caldron, cauldron |
| 470 | candle, taper, wax light |
| 471 | cannon |
| 472 | canoe |
| 473 | can opener, tin opener |
| 474 | cardigan |
| 475 | car mirror |
| 476 | carousel, carrousel, merry-go-round, roundabout, whirligig |
| 477 | carpenter's kit, tool kit |
| 478 | carton |
| 479 | car wheel |
| 480 | cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM |
| 481 | cassette |
| 482 | cassette player |
| 483 | castle |
| 484 | catamaran |
| 485 | CD player |
| 486 | cello, violoncello |
| 487 | cellular telephone, cellular phone, cellphone, cell, mobile phone |
| 488 | chain |
| 489 | chainlink fence |
| 490 | chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour |
| 491 | chain saw, chainsaw |
| 492 | chest |
| 493 | chiffonier, commode |
| 494 | chime, bell, gong |
| 495 | china cabinet, china closet |
| 496 | Christmas stocking |
| 497 | church, church building |
| 498 | cinema, movie theater, movie theatre, movie house, picture palace |
| 499 | cleaver, meat cleaver, chopper |
| 500 | cliff dwelling |
| 501 | cloak |
| 502 | clog, geta, patten, sabot |
| 503 | cocktail shaker |
| 504 | coffee mug |
| 505 | coffeepot |
| 506 | coil, spiral, volute, whorl, helix |
| 507 | combination lock |
| 508 | computer keyboard, keypad |
| 509 | confectionery, confectionary, candy store |
| 510 | container ship, containership, container vessel |
| 511 | convertible |
| 512 | corkscrew, bottle screw |
| 513 | cornet, horn, trumpet, trump |
| 514 | cowboy boot |
| 515 | cowboy hat, ten-gallon hat |
| 516 | cradle |
| 517 | crane_1 |
| 518 | crash helmet |
| 519 | crate |
| 520 | crib, cot |
| 521 | Crock Pot |
| 522 | croquet ball |
| 523 | crutch |
| 524 | cuirass |
| 525 | dam, dike, dyke |
| 526 | desk |
| 527 | desktop computer |
| 528 | dial telephone, dial phone |
| 529 | diaper, nappy, napkin |
| 530 | digital clock |
| 531 | digital watch |
| 532 | dining table, board |
| 533 | dishrag, dishcloth |
| 534 | dishwasher, dish washer, dishwashing machine |
| 535 | disk brake, disc brake |
| 536 | dock, dockage, docking facility |
| 537 | dogsled, dog sled, dog sleigh |
| 538 | dome |
| 539 | doormat, welcome mat |
| 540 | drilling platform, offshore rig |
| 541 | drum, membranophone, tympan |
| 542 | drumstick |
| 543 | dumbbell |
| 544 | Dutch oven |
| 545 | electric fan, blower |
| 546 | electric guitar |
| 547 | electric locomotive |
| 548 | entertainment center |
| 549 | envelope |
| 550 | espresso maker |
| 551 | face powder |
| 552 | feather boa, boa |
| 553 | file, file cabinet, filing cabinet |
| 554 | fireboat |
| 555 | fire engine, fire truck |
| 556 | fire screen, fireguard |
| 557 | flagpole, flagstaff |
| 558 | flute, transverse flute |
| 559 | folding chair |
| 560 | football helmet |
| 561 | forklift |
| 562 | fountain |
| 563 | fountain pen |
| 564 | four-poster |
| 565 | freight car |
| 566 | French horn, horn |
| 567 | frying pan, frypan, skillet |
| 568 | fur coat |
| 569 | garbage truck, dustcart |
| 570 | gasmask, respirator, gas helmet |
| 571 | gas pump, gasoline pump, petrol pump, island dispenser |
| 572 | goblet |
| 573 | go-kart |
| 574 | golf ball |
| 575 | golfcart, golf cart |
| 576 | gondola |
| 577 | gong, tam-tam |
| 578 | gown |
| 579 | grand piano, grand |
| 580 | greenhouse, nursery, glasshouse |
| 581 | grille, radiator grille |
| 582 | grocery store, grocery, food market, market |
| 583 | guillotine |
| 584 | hair slide |
| 585 | hair spray |
| 586 | half track |
| 587 | hammer |
| 588 | hamper |
| 589 | hand blower, blow dryer, blow drier, hair dryer, hair drier |
| 590 | hand-held computer, hand-held microcomputer |
| 591 | handkerchief, hankie, hanky, hankey |
| 592 | hard disc, hard disk, fixed disk |
| 593 | harmonica, mouth organ, harp, mouth harp |
| 594 | harp |
| 595 | harvester, reaper |
| 596 | hatchet |
| 597 | holster |
| 598 | home theater, home theatre |
| 599 | honeycomb |
| 600 | hook, claw |
| 601 | hoopskirt, crinoline |
| 602 | horizontal bar, high bar |
| 603 | horse cart, horse-cart |
| 604 | hourglass |
| 605 | iPod |
| 606 | iron, smoothing iron |
| 607 | jack-o'-lantern |
| 608 | jean, blue jean, denim |
| 609 | jeep, landrover |
| 610 | jersey, T-shirt, tee shirt |
| 611 | jigsaw puzzle |
| 612 | jinrikisha, ricksha, rickshaw |
| 613 | joystick |
| 614 | kimono |
| 615 | knee pad |
| 616 | knot |
| 617 | lab coat, laboratory coat |
| 618 | ladle |
| 619 | lampshade, lamp shade |
| 620 | laptop, laptop computer |
| 621 | lawn mower, mower |
| 622 | lens cap, lens cover |
| 623 | letter opener, paper knife, paperknife |
| 624 | library |
| 625 | lifeboat |
| 626 | lighter, light, igniter, ignitor |
| 627 | limousine, limo |
| 628 | liner, ocean liner |
| 629 | lipstick, lip rouge |
| 630 | Loafer |
| 631 | lotion |
| 632 | loudspeaker, speaker, speaker unit, loudspeaker system, speaker system |
| 633 | loupe, jeweler's loupe |
| 634 | lumbermill, sawmill |
| 635 | magnetic compass |
| 636 | mailbag, postbag |
| 637 | mailbox, letter box |
| 638 | maillot |
| 639 | maillot, tank suit |
| 640 | manhole cover |
| 641 | maraca |
| 642 | marimba, xylophone |
| 643 | mask |
| 644 | matchstick |
| 645 | maypole |
| 646 | maze, labyrinth |
| 647 | measuring cup |
| 648 | medicine chest, medicine cabinet |
| 649 | megalith, megalithic structure |
| 650 | microphone, mike |
| 651 | microwave, microwave oven |
| 652 | military uniform |
| 653 | milk can |
| 654 | minibus |
| 655 | miniskirt, mini |
| 656 | minivan |
| 657 | missile |
| 658 | mitten |
| 659 | mixing bowl |
| 660 | mobile home, manufactured home |
| 661 | Model T |
| 662 | modem |
| 663 | monastery |
| 664 | monitor |
| 665 | moped |
| 666 | mortar |
| 667 | mortarboard |
| 668 | mosque |
| 669 | mosquito net |
| 670 | motor scooter, scooter |
| 671 | mountain bike, all-terrain bike, off-roader |
| 672 | mountain tent |
| 673 | mouse, computer mouse |
| 674 | mousetrap |
| 675 | moving van |
| 676 | muzzle |
| 677 | nail |
| 678 | neck brace |
| 679 | necklace |
| 680 | nipple |
| 681 | notebook, notebook computer |
| 682 | obelisk |
| 683 | oboe, hautboy, hautbois |
| 684 | ocarina, sweet potato |
| 685 | odometer, hodometer, mileometer, milometer |
| 686 | oil filter |
| 687 | organ, pipe organ |
| 688 | oscilloscope, scope, cathode-ray oscilloscope, CRO |
| 689 | overskirt |
| 690 | oxcart |
| 691 | oxygen mask |
| 692 | packet |
| 693 | paddle, boat paddle |
| 694 | paddlewheel, paddle wheel |
| 695 | padlock |
| 696 | paintbrush |
| 697 | pajama, pyjama, pj's, jammies |
| 698 | palace |
| 699 | panpipe, pandean pipe, syrinx |
| 700 | paper towel |
| 701 | parachute, chute |
| 702 | parallel bars, bars |
| 703 | park bench |
| 704 | parking meter |
| 705 | passenger car, coach, carriage |
| 706 | patio, terrace |
| 707 | pay-phone, pay-station |
| 708 | pedestal, plinth, footstall |
| 709 | pencil box, pencil case |
| 710 | pencil sharpener |
| 711 | perfume, essence |
| 712 | Petri dish |
| 713 | photocopier |
| 714 | pick, plectrum, plectron |
| 715 | pickelhaube |
| 716 | picket fence, paling |
| 717 | pickup, pickup truck |
| 718 | pier |
| 719 | piggy bank, penny bank |
| 720 | pill bottle |
| 721 | pillow |
| 722 | ping-pong ball |
| 723 | pinwheel |
| 724 | pirate, pirate ship |
| 725 | pitcher, ewer |
| 726 | plane, carpenter's plane, woodworking plane |
| 727 | planetarium |
| 728 | plastic bag |
| 729 | plate rack |
| 730 | plow, plough |
| 731 | plunger, plumber's helper |
| 732 | Polaroid camera, Polaroid Land camera |
| 733 | pole |
| 734 | police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria |
| 735 | poncho |
| 736 | pool table, billiard table, snooker table |
| 737 | pop bottle, soda bottle |
| 738 | pot, flowerpot |
| 739 | potter's wheel |
| 740 | power drill |
| 741 | prayer rug, prayer mat |
| 742 | printer |
| 743 | prison, prison house |
| 744 | projectile, missile |
| 745 | projector |
| 746 | puck, hockey puck |
| 747 | punching bag, punch bag, punching ball, punchball |
| 748 | purse |
| 749 | quill, quill pen |
| 750 | quilt, comforter, comfort, puff |
| 751 | racer, race car, racing car |
| 752 | racket, racquet |
| 753 | radiator |
| 754 | radio, wireless |
| 755 | radio telescope, radio reflector |
| 756 | rain barrel |
| 757 | recreational vehicle, RV, R.V. |
| 758 | reel |
| 759 | reflex camera |
| 760 | refrigerator, icebox |
| 761 | remote control, remote |
| 762 | restaurant, eating house, eating place, eatery |
| 763 | revolver, six-gun, six-shooter |
| 764 | rifle |
| 765 | rocking chair, rocker |
| 766 | rotisserie |
| 767 | rubber eraser, rubber, pencil eraser |
| 768 | rugby ball |
| 769 | rule, ruler |
| 770 | running shoe |
| 771 | safe |
| 772 | safety pin |
| 773 | saltshaker, salt shaker |
| 774 | sandal |
| 775 | sarong |
| 776 | sax, saxophone |
| 777 | scabbard |
| 778 | scale, weighing machine |
| 779 | school bus |
| 780 | schooner |
| 781 | scoreboard |
| 782 | screen, CRT screen |
| 783 | screw |
| 784 | screwdriver |
| 785 | seat belt, seatbelt |
| 786 | sewing machine |
| 787 | shield, buckler |
| 788 | shoe shop, shoe-shop, shoe store |
| 789 | shoji |
| 790 | shopping basket |
| 791 | shopping cart |
| 792 | shovel |
| 793 | shower cap |
| 794 | shower curtain |
| 795 | ski |
| 796 | ski mask |
| 797 | sleeping bag |
| 798 | slide rule, slipstick |
| 799 | sliding door |
| 800 | slot, one-armed bandit |
| 801 | snorkel |
| 802 | snowmobile |
| 803 | snowplow, snowplough |
| 804 | soap dispenser |
| 805 | soccer ball |
| 806 | sock |
| 807 | solar dish, solar collector, solar furnace |
| 808 | sombrero |
| 809 | soup bowl |
| 810 | space bar |
| 811 | space heater |
| 812 | space shuttle |
| 813 | spatula |
| 814 | speedboat |
| 815 | spider web, spider's web |
| 816 | spindle |
| 817 | sports car, sport car |
| 818 | spotlight, spot |
| 819 | stage |
| 820 | steam locomotive |
| 821 | steel arch bridge |
| 822 | steel drum |
| 823 | stethoscope |
| 824 | stole |
| 825 | stone wall |
| 826 | stopwatch, stop watch |
| 827 | stove |
| 828 | strainer |
| 829 | streetcar, tram, tramcar, trolley, trolley car |
| 830 | stretcher |
| 831 | studio couch, day bed |
| 832 | stupa, tope |
| 833 | submarine, pigboat, sub, U-boat |
| 834 | suit, suit of clothes |
| 835 | sundial |
| 836 | sunglass |
| 837 | sunglasses, dark glasses, shades |
| 838 | sunscreen, sunblock, sun blocker |
| 839 | suspension bridge |
| 840 | swab, swob, mop |
| 841 | sweatshirt |
| 842 | swimming trunks, bathing trunks |
| 843 | swing |
| 844 | switch, electric switch, electrical switch |
| 845 | syringe |
| 846 | table lamp |
| 847 | tank, army tank, armored combat vehicle, armoured combat vehicle |
| 848 | tape player |
| 849 | teapot |
| 850 | teddy, teddy bear |
| 851 | television, television system |
| 852 | tennis ball |
| 853 | thatch, thatched roof |
| 854 | theater curtain, theatre curtain |
| 855 | thimble |
| 856 | thresher, thrasher, threshing machine |
| 857 | throne |
| 858 | tile roof |
| 859 | toaster |
| 860 | tobacco shop, tobacconist shop, tobacconist |
| 861 | toilet seat |
| 862 | torch |
| 863 | totem pole |
| 864 | tow truck, tow car, wrecker |
| 865 | toyshop |
| 866 | tractor |
| 867 | trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi |
| 868 | tray |
| 869 | trench coat |
| 870 | tricycle, trike, velocipede |
| 871 | trimaran |
| 872 | tripod |
| 873 | triumphal arch |
| 874 | trolleybus, trolley coach, trackless trolley |
| 875 | trombone |
| 876 | tub, vat |
| 877 | turnstile |
| 878 | typewriter keyboard |
| 879 | umbrella |
| 880 | unicycle, monocycle |
| 881 | upright, upright piano |
| 882 | vacuum, vacuum cleaner |
| 883 | vase |
| 884 | vault |
| 885 | velvet |
| 886 | vending machine |
| 887 | vestment |
| 888 | viaduct |
| 889 | violin, fiddle |
| 890 | volleyball |
| 891 | waffle iron |
| 892 | wall clock |
| 893 | wallet, billfold, notecase, pocketbook |
| 894 | wardrobe, closet, press |
| 895 | warplane, military plane |
| 896 | washbasin, handbasin, washbowl, lavabo, wash-hand basin |
| 897 | washer, automatic washer, washing machine |
| 898 | water bottle |
| 899 | water jug |
| 900 | water tower |
| 901 | whiskey jug |
| 902 | whistle |
| 903 | wig |
| 904 | window screen |
| 905 | window shade |
| 906 | Windsor tie |
| 907 | wine bottle |
| 908 | wing |
| 909 | wok |
| 910 | wooden spoon |
| 911 | wool, woolen, woollen |
| 912 | worm fence, snake fence, snake-rail fence, Virginia fence |
| 913 | wreck |
| 914 | yawl |
| 915 | yurt |
| 916 | web site, website, internet site, site |
| 917 | comic book |
| 918 | crossword puzzle, crossword |
| 919 | street sign |
| 920 | traffic light, traffic signal, stoplight |
| 921 | book jacket, dust cover, dust jacket, dust wrapper |
| 922 | menu |
| 923 | plate |
| 924 | guacamole |
| 925 | consomme |
| 926 | hot pot, hotpot |
| 927 | trifle |
| 928 | ice cream, icecream |
| 929 | ice lolly, lolly, lollipop, popsicle |
| 930 | French loaf |
| 931 | bagel, beigel |
| 932 | pretzel |
| 933 | cheeseburger |
| 934 | hotdog, hot dog, red hot |
| 935 | mashed potato |
| 936 | head cabbage |
| 937 | broccoli |
| 938 | cauliflower |
| 939 | zucchini, courgette |
| 940 | spaghetti squash |
| 941 | acorn squash |
| 942 | butternut squash |
| 943 | cucumber, cuke |
| 944 | artichoke, globe artichoke |
| 945 | bell pepper |
| 946 | cardoon |
| 947 | mushroom |
| 948 | Granny Smith |
| 949 | strawberry |
| 950 | orange |
| 951 | lemon |
| 952 | fig |
| 953 | pineapple, ananas |
| 954 | banana |
| 955 | jackfruit, jak, jack |
| 956 | custard apple |
| 957 | pomegranate |
| 958 | hay |
| 959 | carbonara |
| 960 | chocolate sauce, chocolate syrup |
| 961 | dough |
| 962 | meat loaf, meatloaf |
| 963 | pizza, pizza pie |
| 964 | potpie |
| 965 | burrito |
| 966 | red wine |
| 967 | espresso |
| 968 | cup |
| 969 | eggnog |
| 970 | alp |
| 971 | bubble |
| 972 | cliff, drop, drop-off |
| 973 | coral reef |
| 974 | geyser |
| 975 | lakeside, lakeshore |
| 976 | promontory, headland, head, foreland |
| 977 | sandbar, sand bar |
| 978 | seashore, coast, seacoast, sea-coast |
| 979 | valley, vale |
| 980 | volcano |
| 981 | ballplayer, baseball player |
| 982 | groom, bridegroom |
| 983 | scuba diver |
| 984 | rapeseed |
| 985 | daisy |
| 986 | yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum |
| 987 | corn |
| 988 | acorn |
| 989 | hip, rose hip, rosehip |
| 990 | buckeye, horse chestnut, conker |
| 991 | coral fungus |
| 992 | agaric |
| 993 | gyromitra |
| 994 | stinkhorn, carrion fungus |
| 995 | earthstar |
| 996 | hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa |
| 997 | bolete |
| 998 | ear, spike, capitulum |
| 999 | toilet tissue, toilet paper, bathroom tissue |
Data Splits
This dataset is a validation-only set.
Dataset Creation
Source Data
This dataset is sourced from ImageNet, ImageNet-ReaL, ImageNet-V2, ImageNet-A, ImageNet-C, ImageNet-R, ImageNet-Sketch, and ObjectNet.
Citation Information
@article{taesiri2023zoom,
title={ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification},
author={Taesiri, Mohammad Reza and Nguyen, Giang and Habchi, Sarra and Bezemer, Cor-Paul and Nguyen, Anh},
journal={arXiv preprint arXiv:2304.05538},
year={2023}
}
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