Sample stimuli

sample 0 sample 1 sample 2 sample 3 sample 4 sample 5 sample 6 sample 7 sample 8 sample 9

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021uniformnoise-top1")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.821
2
.818
3
.816
4
.805
5
.799
6
.796
7
.776
8
.772
9
.772
10
.762
11
.757
12
.750
13
.743
14
.730
15
.724
16
.720
17
.708
18
.704
19
.701
20
.701
21
.701
22
.700
23
.696
24
.696
25
.693
26
.689
27
.686
28
.680
29
.674
30
.671
31
.670
32
.669
33
.657
34
.656
35
.656
36
.654
37
.650
38
.649
39
.644
40
.641
41
.632
42
.632
43
.627
44
.627
45
.626
46
.621
47
.621
48
.618
49
.618
50
.618
51
.616
52
.616
53
.613
54
.604
55
.599
56
.595
57
.586
58
.579
59
.578
60
.575
61
.573
62
.571
63
.568
64
.561
65
.560
66
.560
67
.560
68
.560
69
.554
70
.554
71
.551
72
.549
73
.547
74
.546
75
.542
76
.542
77
.540
78
.540
79
.535
80
.530
81
.530
82
.524
83
.516
84
.515
85
.514
86
.511
87
.507
88
.507
89
.506
90
.506
91
.505
92
.505
93
.501
94
.499
95
.499
96
.497
97
.496
98
.496
99
.496
100
.487
101
.486
102
.486
103
.481
104
.480
105
.479
106
.479
107
.477
108
.476
109
.475
110
.475
111
.471
112
.469
113
.469
114
.468
115
.464
116
.463
117
.461
118
.455
119
.453
120
.449
121
.449
122
.445
123
.445
124
.445
125
.445
126
.443
127
.443
128
.440
129
.440
130
.435
131
.430
132
.427
133
.427
134
.420
135
.417
136
.415
137
.414
138
.410
139
.410
140
.407
141
.406
142
.405
143
.405
144
.404
145
.404
146
.396
147
.395
148
.394
149
.393
150
.384
151
.383
152
.381
153
.380
154
.380
155
.375
156
.374
157
.372
158
.371
159
.369
160
.366
161
.366
162
.359
163
.357
164
.355
165
.351
166
.350
167
.350
168
.345
169
.345
170
.344
171
.343
172
.341
173
.340
174
.340
175
.339
176
.339
177
.335
178
.330
179
.330
180
.330
181
.329
182
.329
183
.326
184
.324
185
.323
186
.319
187
.318
188
.318
189
.318
190
.316
191
.315
192
.314
193
.314
194
.311
195
.311
196
.310
197
.309
198
.307
199
.301
200
.300
201
.294
202
.292
203
.291
204
.291
205
.290
206
.287
207
.285
208
.284
209
.281
210
.273
211
.269
212
.269
213
.269
214
.269
215
.265
216
.259
217
.259
218
.258
219
.256
220
.255
221
.250
222
.247
223
.242
224
.231
225
.230
226
.229
227
.226
228
.221
229
.214
230
.212
231
.212
232
.211
233
.201
234
.196
235
.194
236
.181
237
.180
238
.177
239
.177
240
.177
241
.177
242
.177
243
.177
244
.177
245
.177
246
.177
247
.158
248
.117
249
.090
250
.089
251
.087
252
.080
253
.077
254
.076
255
.072
256
.069
257
.066
258
.064
259
.062
260
.062
261
.062
262
.062
263
.062
264
.062
265
.062
266
.062
267
.062
268
.062
269
.060
270
.060
271
.059
272
.058
273
.058
274
.058
275
.056
276
.051
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408

Benchmark bibtex

@article{geirhos2021partial,
              title={Partial success in closing the gap between human and machine vision},
              author={Geirhos, Robert and Narayanappa, Kantharaju and Mitzkus, Benjamin and Thieringer, Tizian and Bethge, Matthias and Wichmann, Felix A and Brendel, Wieland},
              journal={Advances in Neural Information Processing Systems},
              volume={34},
              year={2021},
              url={https://openreview.net/forum?id=QkljT4mrfs}
        }

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021uniformnoise

Metric: top1