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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	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.1
2	vit_base_patch16_dinov3:lvd1689m	.969
3	resnet50_ewconplus_wzc	.956
4	alexnet_training_seed_08	.932
5	convnext_small_imagenet_10_seed-0	.927
6	alexnet_training_seed_10	.885
7	convnext_tiny_imagenet_full_seed-0	.874
8	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.871
9	deit_small_imagenet_full_seed-0	.851
10	alexnet_training_seed_06	.834
11	vit_relpos_base_patch16_clsgap_224:sw_in1k	.833
12	alexnet_training_seed_09	.827
13	resnet50_imagenet_100_seed-0	.778
14	resnet50-SIN	.765
15	AlexNet_SIN	.759
16	convnext_small_imagenet_full_seed-0	.744
17	alexnet_training_seed_05	.733
18	BiT-S-R101x1	.705
19	mobilenet_v2_0_5_192	.700
20	vit_large_patch14_clip_224:openai_ft_in1k	.697
21	alexnet_training_seed_02	.689
22	VOneCORnet-S	.677
23	convnext_femto_ols:d1_in1k	.674
24	deit_large_imagenet_full_seed-0	.668
25	alexnet_training_seed_01_fov12	.660
26	voneresnet-50-robust	.656
27	grcnn	.655
28	alexnet_training_seed_03	.651
29	alexnet_training_seed_07	.642
30	antialiased-r50	.640
31	alexnet_training_seed_04	.639
32	convnext_base_imagenet_full_seed-0	.632
33	resnet50_robust_l2_eps1	.632
34	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.630
35	focalnet_tiny_lrf_in1k	.620
36	ReAlnet01_cornet	.614
37	BiT-S-R50x1	.613
38	deit_base_imagenet_full_seed-0	.612
39	omnivore_swinS	.607
40	vit_base_patch14_reg4_dinov2:lvd142m	.603
41	vit_base_patch14_dinov2:lvd142m	.590
42	antialiased-rnext101_32x8d	.587
43	ReAlnet03_cornet	.586
44	resnet101_ecoset_full	.577
45	alexnet_training_seed_01_fov16	.575
46	mobilenet_v2_0_75_160	.568
47	ReAlnet10_cornet	.567
48	AlexNet_SIN_fov4	.565
49	ReAlnet07_cornet	.565
50	ReAlnet09_cornet	.559
51	ReAlnet02_cornet	.557
52	convnext_base:clip_laiona_augreg_ft_in1k_384	.554
53	ReAlnet06_cornet	.540
54	alexnet_training_seed_01	.538
55	mobilenet_v2_0_75_224	.533
56	deit_small_imagenet_10_seed-0	.529
57	convnext_small_imagenet_1_seed-0	.527
58	voneresnet-50	.527
59	ReAlnet04_ALL	.524
60	resnet50_ecoset_full	.521
61	ReAlnet08_cornet	.513
62	resnext101_32x32d_wsl	.511
63	resnet50_robust_l2_eps3	.509
64	resnext101_32x8d_wsl	.506
65	yudixie_resnet18_random_0_240719	.505
66	resnet101_imagenet_full	.504
67	ReAlnet06_ALL	.502
68	ReAlnet08_ALL	.499
69	ReAlnet05_ALL	.499
70	ReAlnet03_ALL	.491
71	ReAlnet07_ALL	.491
72	resnet_152_v1	.483
73	resnext101_32x48d_wsl	.483
74	ReAlnet04_cornet	.481
75	nasnet_large	.481
76	ReAlnet09_ALL	.473
77	ReAlnet05_cornet	.464
78	resnet_101_v1	.463
79	BiT-S-R50x3	.462
80	grcnn_109	.462
81	efficientnet_b2_imagenet_full	.461
82	voneresnet-50-non_stochastic	.459
83	resnet50-vitoimagevidnet8	.456
84	resnet50-VITO-8deg-cc	.456
85	shufflenet_v2_x1_0	.455
86	resnet50-SIN_IN_IN	.454
87	ReAlnet02_ALL	.454
88	ReAlnet01_ALL	.452
89	alexnet	.449
90	alexnet_workflow_trigger	.449
91	alexnet_ks_torevert	.449
92	ReAlnet10_ALL	.438
93	resnet18_ecoset_full	.437
94	resnet50-SIN_IN	.431
95	resnet152_ecoset_full	.429
96	resnet_SIN_IN_FT_IN	.428
97	AlexNet_SIN_fov12	.424
98	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.424
99	artResNet18_1	.413
100	mobilenet_v2_0_75_192	.410
101	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.409
102	vit_large_patch14_clip_224:laion2b_ft_in1k	.399
103	inception_v1	.393
104	pnasnet_large	.392
105	alexnet_training_seed_01_fov4	.385
106	deit_small_imagenet_1_seed-0	.384
107	resnet50_imagenet_full	.380
108	cvt_cvt-21-224-in1k_4_LucyV4	.380
109	AlexNet_SIN_fov16	.377
110	ReAlnet03	.375
111	ReAlnet01	.369
112	resnet_50_v1_spiking	.366
113	resnet_50_v1	.366
114	resnet50-sup	.366
115	ReAlnet01_cornet_fov12	.366
116	blt_vs	.365
117	resnet50_primary_visual_cortex	.365
118	resnet34_imagenet_full	.359
119	mobilenet_v2_0_5_224	.358
120	resnet50-vicregl0p9	.355
121	convnext_large_imagenet_full_seed-0	.354
122	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.349
123	ReAlnet09	.345
124	ReAlnet10	.336
125	ReAlnet06	.331
126	imagenet_l2_3_0	.330
127	ReAlnet02	.329
128	effnetb1_272x240	.328
129	mobilenet_v2_1_0_160	.327
130	alexnet_fov16	.326
131	xception	.324
132	ReAlnet05	.323
133	resnet-18_test_m	.322
134	ReAlnet07	.318
135	nasnet_mobile	.310
136	ReAlnet08	.309
137	ReAlnet04	.308
138	BiT-S-R101x3	.300
139	ReAlnet01_cornet_fov16	.288
140	resnet50-moclr8deg	.285
141	alexnet_fov4	.282
142	resnet18_imagenet_full	.271
143	resnet18_imagenet21kP	.261
144	yudixie_resnet18_imagenet1kpret_0_240719	.256
145	hmax	.254
146	resnet50-vicregl0p75	.252
147	resnet50-barlow	.245
148	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.245
149	resnet50-vicreg	.244
150	convnext_xlarge:fb_in22k_ft_in1k	.243
151	efficientnet_b0	.242
152	vonegrcnn_52e_full	.241
153	omnivore_swinB	.240
154	resnet50_imagenet_10_seed-0	.233
155	resnet_101_v2	.230
156	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.230
157	vit_base_patch16_clip_224:openai_ft_in1k	.229
158	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.228
159	regnet_y_400mf	.218
160	resnet152_imagenet_full	.215
161	yudixie_resnet50_imagenet1kpret_0_240312	.213
162	resnet_50_v1_spiking_l4	.213
163	yudixie_resnet50_imagenet1kpret_0_240908	.213
164	resnet_50_v1_spiking_l4a	.213
165	resnet50_tutorial	.213
166	Res2Net50_26w_4s	.211
167	alexnet_fov12	.210
168	vonegrcnn_47e	.207
169	resnet34_ecoset_full	.203
170	inception_v3	.201
171	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.188
172	tv_efficientnet-b1	.186
173	cvt_cvt-21-384-in1k_4_LucyV4	.184
174	resnet-152_v2_pytorch	.180
175	vonegrcnn_62e_nobn	.177
176	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.173
177	convnext_tiny_sup	.173
178	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.166
179	resnet_152_v2	.164
180	compact_vgg19_IT	.160
181	yolos_tiny	.159
182	convnext_large:fb_in22k_ft_in1k	.158
183	deit_small_imagenet_100_seed-0	.158
184	resnet_50_v2	.158
185	antialias-resnet152	.149
186	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.149
187	AdvProp_efficientnet-b4	.144
188	briaai_rmbg_1_4	.142
189	custom_model_cv_18_dagger_408	.139
190	compact_vgg19_V4	.136
191	efficientnet-b7	.131
192	convnext_small_imagenet_100_seed-0	.120
193	vit_large_patch14_clip_336:laion2b_ft_in1k	.119
194	BiT-S-R152x4	.115
195	mobilenet_v2_1_0_224	.114
196	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.107
197	densenet-201	.104
198	mobilenet_v2_1-4_224_pytorch	.103
199	mobilenet_v2_1_4_224	.103
200	inception_v4	.102
201	AdvProp_efficientnet-b6	.101
202	cv_18_dagger_408_pretrained	.099
203	efficientnet_b0_imagenet_full	.099
204	convnext_tiny:in12k_ft_in1k	.097
205	AdvProp_efficientnet-b8	.093
206	mobilenet_v2_1_0_128	.092
207	resnet-50-robust	.084
208	AT_efficientnet-b2	.082
209	AdvProp_efficientnet-b2	.082
210	mobilenet_v2_1_0_192	.078
211	AdvProp_efficientnet-b7	.075
212	ReAlnet01_cornet_fov4	.074
213	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.066
214	mobilenet_v2_1_3_224	.063
215	yudixie_resnet18_distance_reg_0_240719	.060
216	densenet-169	.057
217	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.057
218	efficientnet_b1_imagenet_full	.052
219	BiT-S-R152x2	.048
220	yudixie_resnet50_random_0_240908	.035
221	densenet-121	.035
222	yudixie_resnet18_distance_rotation_0_240719	.033
223	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.030
224	resnet_50_v1_spiking_l3	.025
225	yudixie_resnet18_translation_reg_0_240719	.023
226	vgg_16	.022
227	yudixie_resnet18_distance_translation_rotation_0_240719	.019
228	ViT_L_32_imagenet1k	.015
229	cvt_cvt-13-384-in1k_4_LucyV4	.011
230	yudixie_resnet18_translation_rotation_0_240719	.009
231	vgg_19	.008
232	compact_cornets_IT	.002
233	yudixie_resnet50_distance_rotation_0_240908	.002
234	yudixie_resnet18_distance_translation_0_240719	.001
235	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.000
236	yudixie_resnet18_rotation_reg_0_240719	.000
237	yudixie_resnet50_distance_translation_rotation_0_240908	.000
238	resnet50_imagenet_1_seed-0	.000
239	cvt_cvt-13-224-in1k_4_LucyV4	.000
240	yudixie_resnet50_translation_rotation_0_240908	.000
241	yudixie_resnet50_object_class_0_240908	.000
242	compact_resnet50_robust_IT	.000
243	yudixie_resnet18_object_class_0_240719	.001
244	yudixie_resnet50_distance_translation_0_240908	.001
245	yudixie_resnet50_rotation_reg_0_240908	.001
246	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.001
247	yudixie_resnet50_category_class_0_240908	.002
248	yudixie_resnet50_translation_reg_0_240908	.002
249	compact_resnet50_IT	.003
250	yudixie_resnet18_category_class_0_240719	.005
251	yudixie_resnet50_distance_reg_0_240908	.016
252	compact_cornets_V4	nan
253	compact_resnet50_robust_V4	nan
254	compact_resnet50_V4
255	s3d
256	mvit_v2_s
257	r2plus1d_18
258	SeLaVi-Kinetics-Sound
259	SeLaVi-VGG-Sound
260	SeLaVi-Kinetics400
261	resnet50_eMMCR_Vanilla
262	mvit_v1_b
263	mc3_18
264	resnext101_32x16d_wsl
265	fixres_resnext101_32x48d_wsl
266	r3d_18
267	SeLaVi-AVE
268	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