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("Geirhos2021lowpass-top1")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.818
2
.801
3
.787
4
.779
5
.771
6
.736
7
.708
8
.679
9
.666
10
.657
11
.645
12
.642
13
.641
14
.640
15
.639
16
.632
17
.629
18
.627
19
.626
20
.619
21
.619
22
.616
23
.616
24
.615
25
.615
26
.615
27
.613
28
.611
29
.609
30
.605
31
.603
32
.580
33
.579
34
.570
35
.568
36
.568
37
.561
38
.557
39
.556
40
.555
41
.551
42
.547
43
.544
44
.544
45
.541
46
.541
47
.540
48
.540
49
.539
50
.537
51
.536
52
.530
53
.527
54
.526
55
.526
56
.526
57
.522
58
.519
59
.516
60
.506
61
.505
62
.505
63
.505
64
.497
65
.495
66
.494
67
.494
68
.492
69
.489
70
.487
71
.487
72
.486
73
.485
74
.485
75
.484
76
.484
77
.484
78
.484
79
.484
80
.481
81
.481
82
.481
83
.479
84
.477
85
.477
86
.477
87
.476
88
.476
89
.476
90
.476
91
.474
92
.474
93
.474
94
.472
95
.471
96
.469
97
.469
98
.469
99
.468
100
.466
101
.466
102
.464
103
.463
104
.463
105
.461
106
.460
107
.460
108
.460
109
.459
110
.458
111
.456
112
.456
113
.454
114
.454
115
.454
116
.453
117
.453
118
.453
119
.453
120
.453
121
.453
122
.451
123
.450
124
.449
125
.449
126
.449
127
.448
128
.446
129
.446
130
.446
131
.446
132
.445
133
.444
134
.444
135
.443
136
.441
137
.440
138
.440
139
.439
140
.439
141
.439
142
.439
143
.438
144
.436
145
.434
146
.434
147
.432
148
.432
149
.431
150
.431
151
.431
152
.431
153
.427
154
.425
155
.425
156
.425
157
.424
158
.422
159
.422
160
.421
161
.420
162
.420
163
.419
164
.417
165
.415
166
.414
167
.414
168
.412
169
.411
170
.410
171
.410
172
.410
173
.407
174
.404
175
.404
176
.404
177
.399
178
.398
179
.398
180
.396
181
.395
182
.395
183
.395
184
.393
185
.391
186
.390
187
.389
188
.389
189
.388
190
.388
191
.388
192
.385
193
.385
194
.380
195
.379
196
.379
197
.379
198
.378
199
.376
200
.376
201
.374
202
.374
203
.372
204
.372
205
.369
206
.369
207
.366
208
.365
209
.364
210
.364
211
.361
212
.361
213
.361
214
.360
215
.360
216
.357
217
.357
218
.356
219
.356
220
.355
221
.354
222
.351
223
.349
224
.349
225
.349
226
.349
227
.346
228
.345
229
.345
230
.345
231
.345
232
.345
233
.344
234
.344
235
.343
236
.340
237
.339
238
.338
239
.338
240
.338
241
.335
242
.335
243
.328
244
.328
245
.326
246
.326
247
.326
248
.326
249
.326
250
.321
251
.320
252
.314
253
.312
254
.312
255
.311
256
.309
257
.307
258
.304
259
.302
260
.300
261
.299
262
.297
263
.296
264
.295
265
.294
266
.294
267
.294
268
.292
269
.291
270
.291
271
.291
272
.290
273
.286
274
.286
275
.282
276
.279
277
.259
278
.250
279
.101
280
.101
281
.099
282
.071
283
.070
284
.068
285
.065
286
.064
287
.064
288
.064
289
.062
290
.062
291
.062
292
.062
293
.062
294
.062
295
.062
296
.062
297
.062
298
.062
299
.062
300
.059
301
.058
302
.058
303
.056
304
.056
305
.055
306
.050
307
.049
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
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469

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: Geirhos2021lowpass

Metric: top1