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

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.863
2
.854
3
4
5
6
.851
7
8
9
10
.842
11
12
13
.829
14
15
16
.827
17
18
.822
19
20
21
.804
22
.802
23
24
25
26
27
28
29
.790
30
31
.780
32
33
.778
34
35
36
37
38
39
.774
40
41
42
.772
43
.768
44
.767
45
46
47
48
.764
49
50
51
52
.759
53
54
55
56
.756
57
.752
58
.752
59
60
.750
61
62
63
64
65
.746
66
67
.745
68
69
.744
70
71
72
.740
73
74
75
76
.739
77
78
79
80
.733
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
.718
102
103
.715
104
105
.711
106
.709
107
108
.707
109
110
111
112
113
.702
114
115
.700
116
117
.698
118
.698
119
.698
120
121
122
123
124
.688
125
.687
126
127
.684
128
129
130
.680
131
132
.672
133
134
135
136
.664
137
138
139
.654
140
141
.653
142
.653
143
.652
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
.639
171
.633
172
.632
173
174
175
176
.621
177
.617
178
179
180
181
.610
182
.603
183
.603
184
.602
185
186
.591
187
.588
188
189
.582
190
.577
191
.577
192
.575
193
.575
194
195
196
.563
197
.557
198
199
200
201
202
203
204
205
206
207
208
209
210
211
.512
212
.508
213
214
215
.498
216
.477
217
218
219
.470
220
221
222
.455
223
.455
224
225
226
.415
227
228
229
230
231
232
233
234
235
236
237
.260
238
239
240
241
242
243
244
245
246
247
248
249
250
251
.001
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
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

Benchmark bibtex

@INPROCEEDINGS{5206848,  
                                                author={J. {Deng} and W. {Dong} and R. {Socher} and L. {Li} and  {Kai Li} and  {Li Fei-Fei}},  
                                                booktitle={2009 IEEE Conference on Computer Vision and Pattern Recognition},   
                                                title={ImageNet: A large-scale hierarchical image database},   
                                                year={2009},  
                                                volume={},  
                                                number={},  
                                                pages={248-255},
                                            }

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: ImageNet

Metric: top1