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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("tong.Coggan2024_fMRI.IT-rdm")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	gabor_filter_entropy_4x4_v2_forcedCosine	1.0
2	gabor_filter_entropy_4x4_v2	1.0
3	gabor_filter_entropy_4x4	1.0
4	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
5	vit_base_patch16_dinov3-lvd1689m	.969
6	resnet50_ewconplus_wzc	.956
7	alexnet_training_seed_08	.932
8	convnext_small_imagenet_10_seed-0	.927
9	alexnet_training_seed_10	.885
10	convnext_tiny_imagenet_full_seed-0	.874
11	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.871
12	deit_small_imagenet_full_seed-0	.851
13	alexnet_training_seed_06	.834
14	vit_relpos_base_patch16_clsgap_224:sw_in1k	.833
15	alexnet_training_seed_09	.827
16	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.786
17	resnet50_imagenet_100_seed-0	.778
18	mehrer2020_alexnet_training_seed_04	.769
19	resnet50-SIN	.765
20	AlexNet_SIN	.759
21	convnext_small_imagenet_full_seed-0	.744
22	mehrer2020_alexnet_training_seed_07	.738
23	alexnet_training_seed_05	.733
24	gabor_filter_mean_abs_4x4_v2	.707
25	BiT-S-R101x1	.705
26	mobilenet_v2_0_5_192	.700
27	vit_large_patch14_clip_224:openai_ft_in1k	.697
28	alexnet_training_seed_02	.689
29	VOneCORnet-S	.677
30	convnext_femto_ols:d1_in1k	.674
31	deit_large_imagenet_full_seed-0	.668
32	alexnet_training_seed_01_fov12	.660
33	resnet50_ewconplus_wzc_seed2_2__323	.656
34	voneresnet-50-robust	.656
35	grcnn	.655
36	convnext_base_fb_in1k_gram_aligned_dinov3	.655
37	pr1_stl10_disentangled_alpha04	.652
38	alexnet_training_seed_03	.651
39	mehrer2020_alexnet_training_seed_08	.647
40	alexnet_training_seed_07	.642
41	resnet50_ewconplus_wzc_seed6_2_323	.642
42	antialiased-r50	.640
43	alexnet_training_seed_04	.639
44	convnext_base_imagenet_full_seed-0	.632
45	resnet50_robust_l2_eps1	.632
46	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.630
47	resnet50_hvs_wzc	.629
48	mehrer2020_alexnet_training_seed_01	.627
49	focalnet_tiny_lrf_in1k	.620
50	ReAlnet01_cornet	.614
51	BiT-S-R50x1	.613
52	deit_base_imagenet_full_seed-0	.612
53	resnet50_ewconplus_wzc_seed5_2__323	.608
54	omnivore_swinS	.607
55	vit_base_patch14_reg4_dinov2-lvd142m	.603
56	dinov2_vitl14_lc	.602
57	vit_base_patch14_dinov2-lvd142m	.590
58	antialiased-rnext101_32x8d	.587
59	ReAlnet03_cornet	.586
60	resnet101_ecoset_full	.577
61	alexnet_training_seed_01_fov16	.575
62	mehrer2020_alexnet_training_seed_05	.572
63	mobilenet_v2_0_75_160	.568
64	ReAlnet10_cornet	.567
65	AlexNet_SIN_fov4	.565
66	ReAlnet07_cornet	.565
67	ReAlnet09_cornet	.559
68	ReAlnet02_cornet	.557
69	convnext_base:clip_laiona_augreg_ft_in1k_384	.554
70	convnext_large_in22k_supervised	.550
71	resnext101_32x16d_wsl	.549
72	mehrer2020_alexnet_training_seed_10	.548
73	ReAlnet06_cornet	.540
74	alexnet_training_seed_01	.538
75	mobilenet_v2_0_75_224	.533
76	deit_small_imagenet_10_seed-0	.529
77	convnext_small_imagenet_1_seed-0	.527
78	voneresnet-50	.527
79	ReAlnet04_ALL	.524
80	resnet50_ecoset_full	.521
81	mehrer2020_alexnet_training_seed_06	.518
82	ReAlnet08_cornet	.513
83	resnext101_32x32d_wsl	.511
84	mehrer2020_alexnet_training_seed_09	.510
85	resnet50_robust_l2_eps3	.509
86	resnext101_32x8d_wsl	.506
87	yudixie_resnet18_random_0_240719	.505
88	resnet101_imagenet_full	.504
89	ReAlnet06_ALL	.502
90	ReAlnet08_ALL	.499
91	deepeisnn_ei_cifar10_vgg19	.499
92	ReAlnet05_ALL	.499
93	ReAlnet03_ALL	.491
94	ReAlnet07_ALL	.491
95	resnet50_st_wzc_seed6_2_323	.489
96	resnet_152_v1	.483
97	resnext101_32x48d_wsl	.483
98	mehrer2020_alexnet_training_seed_03	.482
99	ReAlnet04_cornet	.481
100	nasnet_large	.481
101	ReAlnet09_ALL	.473
102	ReAlnet05_cornet	.464
103	resnet_101_v1	.463
104	BiT-S-R50x3	.462
105	grcnn_109	.462
106	efficientnet_b2_imagenet_full	.461
107	voneresnet-50-non_stochastic	.459
108	resnet50-vitoimagevidnet8	.456
109	resnet50-VITO-8deg-cc	.456
110	shufflenet_v2_x1_0	.455
111	resnet50-SIN_IN_IN	.454
112	ReAlnet02_ALL	.454
113	ReAlnet01_ALL	.452
114	alexnet	.449
115	alexnet_ks_torevert	.449
116	deepeisnn_ei_cifar10_resnet18	.445
117	mehrer2020_alexnet_training_seed_02	.442
118	ReAlnet10_ALL	.438
119	resnet18_ecoset_full	.437
120	resnet50_st_wzc_seed7_2_323	.434
121	resnet50-SIN_IN	.431
122	resnet152_ecoset_full	.429
123	resnet_SIN_IN_FT_IN	.428
124	resnet50_vicreg_linhead	.427
125	AlexNet_SIN_fov12	.424
126	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.424
127	convnext_base_fb_in22k_ft_in1k	.423
128	artResNet18_1	.413
129	mobilenet_v2_0_75_192	.410
130	seresnext50_32x4d	.409
131	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.409
132	mehrer2020_alexnet_training_seed_01_fov4	.407
133	vit_large_patch14_clip_224:laion2b_ft_in1k	.399
134	inception_v1	.393
135	pnasnet_large	.392
136	resnet50_byol_linhead	.387
137	alexnet_training_seed_01_fov4	.385
138	deit_small_imagenet_1_seed-0	.384
139	resnet50_imagenet_full	.380
140	cvt_cvt-21-224-in1k_4_LucyV4	.380
141	AlexNet_SIN_fov16	.377
142	resnet50_st_wzc_2	.376
143	ReAlnet03	.375
144	ReAlnet01	.369
145	resnet_50_v1_spiking	.366
146	resnet_50_v1	.366
147	resnet50-sup	.366
148	ReAlnet01_cornet_fov12	.366
149	blt_vs	.365
150	resnet50_primary_visual_cortex	.365
151	dinov2_vitl14_lc_res336	.360
152	resnet34_imagenet_full	.359
153	mobilenet_v2_0_5_224	.358
154	resnet50_st_wzc_seed3_2_323	.357
155	convnext_base_fb_in1k	.356
156	resnet50-vicregl0p9	.355
157	convnext_large_imagenet_full_seed-0	.354
158	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.349
159	ReAlnet09	.345
160	mehrer2020_alexnet_training_seed_01_fov12	.342
161	resnet50_barlowtwins_linhead	.341
162	ReAlnet10	.336
163	resnet50_simclr_linhead_01norm	.334
164	ReAlnet06	.331
165	imagenet_l2_3_0	.330
166	ReAlnet02	.329
167	effnetb1_272x240	.328
168	mobilenet_v2_1_0_160	.327
169	alexnet_fov16	.326
170	xception	.324
171	ReAlnet05	.323
172	resnet-18_test_m	.322
173	resnet50_simsiam_linhead	.321
174	ijepa_vith14_linhead	.318
175	ReAlnet07	.318
176	nasnet_mobile	.310
177	ReAlnet08	.309
178	ReAlnet04	.308
179	BiT-S-R101x3	.300
180	convnext_xxlarge_clip	.294
181	deepeisnn_ei_imagenet_resnet18	.289
182	ReAlnet01_cornet_fov16	.288
183	regnety_032	.287
184	resnet50-moclr8deg	.285
185	dinov2_vitg14_lc	.283
186	alexnet_fov4	.282
187	resnet18_imagenet_full	.271
188	eicircuit_resnet18_bn_20260919	.265
189	dinov2_vitg14_reg_lc	.262
190	resnet18_imagenet21kP	.261
191	yudixie_wbh_object_class_scaling_0415_imagenet	.256
192	yudixie_resnet18_imagenet1kpret_0_240719	.256
193	hmax	.254
194	resnet50-vicregl0p75	.252
195	mehrer2020_alexnet_training_seed_01_fov16	.251
196	vit_huge_clip336_laion	.250
197	resnet50-barlow	.245
198	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.245
199	resnet50-vicreg	.244
200	convnext_xlarge:fb_in22k_ft_in1k	.243
201	efficientnet_b0	.242
202	vonegrcnn_52e_full	.241
203	omnivore_swinB	.240
204	resnet18_fair	.238
205	resnet50_imagenet_10_seed-0	.233
206	dinov2_vitl14_reg_lc_featread	.233
207	dinov2_vitl14_reg_lc	.233
208	resnet_101_v2	.230
209	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.230
210	vit_base_patch16_clip_224:openai_ft_in1k	.229
211	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.228
212	yudixie_wbh_object_class_scaling_0415_run_3	.221
213	regnet_y_400mf	.218
214	resnet152_imagenet_full	.215
215	yudixie_resnet50_imagenet1kpret_0_240312	.213
216	resnet_50_v1_spiking_l4	.213
217	yudixie_resnet50_imagenet1kpret_0_240908	.213
218	resnet_50_v1_spiking_l4a	.213
219	resnet50_tutorial	.213
220	Res2Net50_26w_4s	.211
221	alexnet_fov12	.210
222	vonegrcnn_47e	.207
223	resnet34_ecoset_full	.203
224	inception_v3	.201
225	deit3_base_patch16_224_fb_in1k	.196
226	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.196
227	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.188
228	tv_efficientnet-b1	.186
229	cvt_cvt-21-384-in1k_4_LucyV4	.184
230	resnet-152_v2_pytorch	.180
231	predictive_coding_pc	.178
232	vonegrcnn_62e_nobn	.177
233	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.173
234	convnext_tiny_sup	.173
235	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.166
236	eva02_large_in22k	.166
237	resnet_152_v2	.164
238	compact_vgg19_IT	.160
239	yolos_tiny	.159
240	convnext_large:fb_in22k_ft_in1k	.158
241	deit_small_imagenet_100_seed-0	.158
242	resnet_50_v2	.158
243	antialias-resnet152	.149
244	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.149
245	vit_large_clip336_openai	.145
246	AdvProp_efficientnet-b4	.144
247	briaai_rmbg_1_4	.142
248	custom_model_cv_18_dagger_408	.139
249	compact_vgg19_V4	.136
250	efficientnet-b7	.131
251	convnext_small_imagenet_100_seed-0	.120
252	vit_large_patch14_clip_336:laion2b_ft_in1k	.119
253	BiT-S-R152x4	.115
254	mobilenet_v2_1_0_224	.114
255	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.107
256	densenet-201	.104
257	mobilenet_v2_1-4_224_pytorch	.103
258	mobilenet_v2_1_4_224	.103
259	inception_v4	.102
260	AdvProp_efficientnet-b6	.101
261	cv_18_dagger_408_pretrained	.099
262	efficientnet_b0_imagenet_full	.099
263	convnext_tiny:in12k_ft_in1k	.097
264	AdvProp_efficientnet-b8	.093
265	mobilenet_v2_1_0_128	.092
266	resnet-50-robust	.084
267	AT_efficientnet-b2	.082
268	AdvProp_efficientnet-b2	.082
269	mobilenet_v2_1_0_192	.078
270	AdvProp_efficientnet-b7	.075
271	ReAlnet01_cornet_fov4	.074
272	yudixie_wbh_object_class_scaling_0415_run_1	.071
273	yudixie_wbh_object_class_scaling_0415_run_2	.067
274	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.066
275	mobilenet_v2_1_3_224	.063
276	yudixie_wbh_object_class_scaling_0415_run_0	.062
277	yudixie_resnet18_distance_reg_0_240719	.060
278	densenet-169	.057
279	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.057
280	convnext_large_clip_laion2b_finelayers	.055
281	efficientnet_b1_imagenet_full	.052
282	BiT-S-R152x2	.048
283	yudixie_resnet50_random_0_240908	.035
284	densenet-121	.035
285	yudixie_resnet18_distance_rotation_0_240719	.033
286	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.030
287	resnet_50_v1_spiking_l3	.025
288	yudixie_resnet18_translation_reg_0_240719	.023
289	vgg_16	.022
290	yudixie_resnet18_distance_translation_rotation_0_240719	.019
291	ViT_L_32_imagenet1k	.015
292	cvt_cvt-13-384-in1k_4_LucyV4	.011
293	yudixie_resnet18_translation_rotation_0_240719	.009
294	vgg_19	.008
295	compact_cornets_IT	.002
296	yudixie_resnet50_distance_rotation_0_240908	.002
297	yudixie_resnet18_distance_translation_0_240719	.001
298	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.000
299	yudixie_resnet18_rotation_reg_0_240719	.000
300	yudixie_resnet50_distance_translation_rotation_0_240908	.000
301	resnet50_imagenet_1_seed-0	.000
302	cvt_cvt-13-224-in1k_4_LucyV4	.000
303	yudixie_resnet50_translation_rotation_0_240908	.000
304	yudixie_resnet50_object_class_0_240908	.000
305	compact_resnet50_robust_IT	.000
306	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.001
307	deit3_base_patch16_224_fb_in22k_ft_in1k	.001
308	yudixie_resnet18_object_class_0_240719	.001
309	yudixie_resnet50_distance_translation_0_240908	.001
310	yudixie_resnet50_rotation_reg_0_240908	.001
311	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.001
312	yudixie_resnet50_category_class_0_240908	.002
313	yudixie_resnet50_translation_reg_0_240908	.002
314	compact_resnet50_IT	.003
315	yudixie_resnet18_category_class_0_240719	.005
316	yudixie_resnet50_distance_reg_0_240908	.016
317	pnasnet_large_halfPrecision
318	compact_cornets_V4	1.0
319	compact_resnet50_robust_V4	1.0
320	compact_resnet50_V4
321	s3d
322	mvit_v2_s
323	r2plus1d_18
324	SeLaVi-Kinetics-Sound
325	SeLaVi-VGG-Sound
326	SeLaVi-Kinetics400
327	resnet50_eMMCR_Vanilla
328	mvit_v1_b
329	mc3_18
330	fixres_resnext101_32x48d_wsl
331	r3d_18
332	SeLaVi-AVE
333	pnasnet_large_pytorch

Benchmark bibtex

@inproceedings{santurkar2019computer,
    title={Computer Vision with a Single (Robust) Classifier},
    author={Shibani Santurkar and Dimitris Tsipras and Brandon Tran and Andrew Ilyas and Logan Engstrom and Aleksander Madry},
    booktitle={ArXiv preprint arXiv:1906.09453},
    year={2019}
}

Ceiling

0.24.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_fMRI.IT

Metric: rdm