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("Geirhos2021phasescrambling-top1")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.945
2
.944
3
.934
4
.933
5
.928
6
.911
7
.895
8
.895
9
.894
10
.892
11
.883
12
.881
13
.880
14
.880
15
.875
16
.873
17
.873
18
.872
19
.864
20
.856
21
.852
22
.850
23
.844
24
.836
25
.836
26
.833
27
.830
28
.825
29
.822
30
.822
31
.819
32
.819
33
.817
34
.817
35
.814
36
.809
37
.805
38
.803
39
.800
40
.791
41
.789
42
.786
43
.784
44
.781
45
.778
46
.770
47
.769
48
.767
49
.764
50
.761
51
.761
52
.758
53
.755
54
.753
55
.752
56
.750
57
.738
58
.727
59
.723
60
.719
61
.717
62
.713
63
.692
64
.691
65
.691
66
.689
67
.689
68
.689
69
.684
70
.680
71
.678
72
.678
73
.678
74
.675
75
.672
76
.670
77
.666
78
.666
79
.664
80
.661
81
.661
82
.661
83
.661
84
.659
85
.659
86
.658
87
.656
88
.656
89
.656
90
.655
91
.655
92
.653
93
.653
94
.653
95
.653
96
.652
97
.652
98
.650
99
.650
100
.648
101
.648
102
.648
103
.647
104
.645
105
.645
106
.644
107
.644
108
.644
109
.641
110
.641
111
.639
112
.639
113
.639
114
.637
115
.636
116
.636
117
.636
118
.633
119
.633
120
.633
121
.633
122
.633
123
.633
124
.631
125
.630
126
.630
127
.628
128
.627
129
.627
130
.627
131
.625
132
.625
133
.623
134
.623
135
.622
136
.622
137
.620
138
.620
139
.620
140
.620
141
.620
142
.620
143
.620
144
.616
145
.616
146
.614
147
.614
148
.613
149
.613
150
.609
151
.608
152
.606
153
.606
154
.606
155
.606
156
.605
157
.603
158
.602
159
.598
160
.597
161
.597
162
.597
163
.597
164
.597
165
.597
166
.595
167
.595
168
.595
169
.595
170
.595
171
.594
172
.594
173
.594
174
.594
175
.594
176
.594
177
.594
178
.592
179
.592
180
.591
181
.589
182
.589
183
.589
184
.589
185
.589
186
.589
187
.588
188
.588
189
.586
190
.584
191
.584
192
.584
193
.583
194
.583
195
.583
196
.580
197
.580
198
.580
199
.578
200
.577
201
.577
202
.577
203
.577
204
.575
205
.573
206
.573
207
.573
208
.573
209
.573
210
.572
211
.572
212
.570
213
.569
214
.567
215
.567
216
.567
217
.566
218
.564
219
.564
220
.562
221
.562
222
.559
223
.558
224
.558
225
.556
226
.553
227
.553
228
.550
229
.550
230
.548
231
.545
232
.545
233
.544
234
.541
235
.539
236
.536
237
.533
238
.530
239
.530
240
.525
241
.523
242
.523
243
.522
244
.522
245
.520
246
.520
247
.520
248
.520
249
.520
250
.519
251
.517
252
.517
253
.516
254
.511
255
.511
256
.511
257
.511
258
.506
259
.505
260
.503
261
.503
262
.498
263
.498
264
.495
265
.494
266
.492
267
.491
268
.489
269
.484
270
.483
271
.481
272
.470
273
.470
274
.463
275
.463
276
.461
277
.461
278
.458
279
.458
280
.445
281
.445
282
.436
283
.430
284
.427
285
.420
286
.417
287
.412
288
.406
289
.398
290
.378
291
.372
292
.323
293
.286
294
.109
295
.105
296
.098
297
.097
298
.086
299
.083
300
.080
301
.073
302
.069
303
.067
304
.064
305
.062
306
.062
307
.062
308
.062
309
.062
310
.062
311
.062
312
.062
313
.062
314
.062
315
.062
316
.062
317
.062
318
.061
319
.059
320
.059
321
.041
322
.037
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
470
471
472
473
474
475
476
477
478
479
480
481
482
483

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: Geirhos2021phasescrambling

Metric: top1