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("Marques2020_FreemanZiemba2013-texture_sparseness")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.930
2
.919
3
.917
4
.912
5
.908
6
.908
7
.907
8
.900
9
.897
10
.894
11
.886
12
.885
13
.884
14
.878
15
.877
16
.879
17
.876
18
.875
19
.870
20
.868
21
.866
22
.863
23
.856
24
.857
25
.853
26
.849
27
.851
28
.847
29
.845
30
.845
31
.844
32
.843
33
.843
34
.842
35
.843
36
.841
37
.841
38
.841
39
.838
40
.839
41
.837
42
.839
43
.838
44
.835
45
.834
46
.833
47
.832
48
.830
49
.829
50
.829
51
.827
52
.825
53
.825
54
.824
55
.823
56
.822
57
.823
58
.820
59
.817
60
.814
61
.814
62
.814
63
.813
64
.813
65
.812
66
.811
67
.811
68
.808
69
.806
70
.805
71
.806
72
.804
73
.804
74
.802
75
.801
76
.801
77
.800
78
.799
79
.798
80
.798
81
.799
82
.796
83
.795
84
.794
85
.794
86
.793
87
.794
88
.793
89
.791
90
.792
91
.791
92
.790
93
.789
94
.789
95
.787
96
.787
97
.786
98
.784
99
.783
100
.781
101
.780
102
.780
103
.781
104
.779
105
.778
106
.780
107
.778
108
.779
109
.777
110
.777
111
.776
112
.778
113
.776
114
.776
115
.775
116
.776
117
.773
118
.772
119
.771
120
.769
121
.769
122
.768
123
.767
124
.767
125
.767
126
.766
127
.766
128
.766
129
.764
130
.762
131
.764
132
.762
133
.763
134
.762
135
.762
136
.762
137
.761
138
.761
139
.759
140
.758
141
.756
142
.755
143
.752
144
.752
145
.751
146
.751
147
.750
148
.749
149
.747
150
.746
151
.746
152
.741
153
.742
154
.741
155
.741
156
.738
157
.738
158
.737
159
.737
160
.735
161
.737
162
.736
163
.734
164
.731
165
.731
166
.728
167
.726
168
.726
169
.725
170
.727
171
.718
172
.717
173
.715
174
.715
175
.714
176
.711
177
.710
178
.711
179
.709
180
.707
181
.706
182
.703
183
.702
184
.702
185
.700
186
.700
187
.701
188
.700
189
.699
190
.696
191
.696
192
.695
193
.695
194
.692
195
.692
196
.691
197
.690
198
.687
199
.687
200
.687
201
.686
202
.684
203
.684
204
.684
205
.681
206
.681
207
.680
208
.680
209
.679
210
.679
211
.677
212
.677
213
.673
214
.671
215
.669
216
.667
217
.668
218
.668
219
.666
220
.663
221
.664
222
.663
223
.663
224
.659
225
.658
226
.658
227
.658
228
.658
229
.655
230
.655
231
.651
232
.651
233
.647
234
.646
235
.645
236
.645
237
.644
238
.644
239
.643
240
.643
241
.643
242
.642
243
.642
244
.642
245
.641
246
.640
247
.639
248
.634
249
.634
250
.632
251
.631
252
.631
253
.630
254
.630
255
.625
256
.624
257
.622
258
.622
259
.620
260
.616
261
.616
262
.615
263
.613
264
.611
265
.607
266
.606
267
.603
268
.603
269
.601
270
.599
271
.600
272
.600
273
.598
274
.597
275
.596
276
.597
277
.594
278
.594
279
.593
280
.594
281
.593
282
.592
283
.591
284
.589
285
.588
286
.586
287
.586
288
.584
289
.582
290
.583
291
.582
292
.582
293
.579
294
.572
295
.572
296
.570
297
.569
298
.565
299
.560
300
.555
301
.554
302
.554
303
.550
304
.548
305
.548
306
.546
307
.545
308
.543
309
.543
310
.542
311
.543
312
.542
313
.543
314
.542
315
.542
316
.541
317
.534
318
.533
319
.529
320
.523
321
.515
322
.513
323
.511
324
.509
325
.509
326
.508
327
.500
328
.498
329
.497
330
.490
331
.486
332
.467
333
.455
334
.451
335
.451
336
.451
337
.433
338
.430
339
.422
340
.412
341
.404
342
.386
343
.358
344
.347
345
.338
346
.330
347
.329
348
.325
349
.325
350
.254
351
.241
352
.164
353
.157
354
.094
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378

Benchmark bibtex

@article{Freeman2013,
            author = {Freeman, Jeremy and Ziemba, Corey M. and Heeger, David J. and Simoncelli, E. P. and Movshon, J. A.},
            doi = {10.1038/nn.3402},
            issn = {10976256},
            journal = {Nature Neuroscience},
            number = {7},
            pages = {974--981},
            pmid = {23685719},
            publisher = {Nature Publishing Group},
            title = {{A functional and perceptual signature of the second visual area in primates}},
            url = {http://dx.doi.org/10.1038/nn.3402},
            volume = {16},
            year = {2013}
            }
            

Ceiling

0.93.

Note that scores are relative to this ceiling.

Data: Marques2020_FreemanZiemba2013

Metric: texture_sparseness