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