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	alexnet_training_seed_08	.932
3	convnext_small_imagenet_10_seed-0	.927
4	alexnet_training_seed_10	.885
5	convnext_tiny_imagenet_full_seed-0	.874
6	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.871
7	deit_small_imagenet_full_seed-0	.851
8	alexnet_training_seed_06	.834
9	vit_relpos_base_patch16_clsgap_224:sw_in1k	.833
10	alexnet_training_seed_09	.827
11	resnet50_imagenet_100_seed-0	.778
12	resnet50-SIN	.765
13	convnext_small_imagenet_full_seed-0	.744
14	alexnet_training_seed_05	.733
15	BiT-S-R101x1	.705
16	mobilenet_v2_0_5_192	.700
17	vit_large_patch14_clip_224:openai_ft_in1k	.697
18	alexnet_training_seed_02	.689
19	VOneCORnet-S	.677
20	convnext_femto_ols:d1_in1k	.674
21	deit_large_imagenet_full_seed-0	.668
22	voneresnet-50-robust	.656
23	alexnet_training_seed_03	.651
24	alexnet_training_seed_07	.642
25	antialiased-r50	.640
26	alexnet_training_seed_04	.639
27	convnext_base_imagenet_full_seed-0	.632
28	resnet50_robust_l2_eps1	.632
29	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.630
30	focalnet_tiny_lrf_in1k	.620
31	ReAlnet01_cornet	.614
32	BiT-S-R50x1	.613
33	deit_base_imagenet_full_seed-0	.612
34	omnivore_swinS	.607
35	ReAlnet03_cornet	.586
36	resnet101_ecoset_full	.577
37	mobilenet_v2_0_75_160	.568
38	ReAlnet10_cornet	.567
39	ReAlnet07_cornet	.565
40	ReAlnet09_cornet	.559
41	ReAlnet02_cornet	.557
42	convnext_base:clip_laiona_augreg_ft_in1k_384	.554
43	ReAlnet06_cornet	.540
44	alexnet_training_seed_01	.538
45	mobilenet_v2_0_75_224	.533
46	deit_small_imagenet_10_seed-0	.529
47	convnext_small_imagenet_1_seed-0	.527
48	voneresnet-50	.527
49	resnet50_ecoset_full	.521
50	ReAlnet08_cornet	.513
51	resnext101_32x32d_wsl	.511
52	resnet50_robust_l2_eps3	.509
53	resnext101_32x8d_wsl	.506
54	yudixie_resnet18_random_0_240719	.505
55	resnet101_imagenet_full	.504
56	resnext101_32x48d_wsl	.483
57	ReAlnet04_cornet	.481
58	ReAlnet05_cornet	.464
59	resnet_101_v1	.463
60	BiT-S-R50x3	.462
61	efficientnet_b2_imagenet_full	.461
62	voneresnet-50-non_stochastic	.459
63	resnet50-VITO-8deg-cc	.456
64	resnet50-vitoimagevidnet8	.456
65	shufflenet_v2_x1_0	.455
66	resnet50-SIN_IN_IN	.454
67	resnet18_ecoset_full	.437
68	resnet50-SIN_IN	.431
69	resnet152_ecoset_full	.429
70	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.424
71	artResNet18_1	.413
72	mobilenet_v2_0_75_192	.410
73	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.409
74	vit_large_patch14_clip_224:laion2b_ft_in1k	.399
75	inception_v1	.393
76	deit_small_imagenet_1_seed-0	.384
77	resnet50_imagenet_full	.380
78	cvt_cvt-21-224-in1k_4_LucyV4	.380
79	ReAlnet03	.375
80	ReAlnet01	.369
81	ReAlnet_incorrect	.369
82	resnet50-sup	.366
83	resnet_50_v1	.366
84	blt_vs	.365
85	resnet34_imagenet_full	.359
86	mobilenet_v2_0_5_224	.358
87	resnet50-vicregl0p9	.355
88	convnext_large_imagenet_full_seed-0	.354
89	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.349
90	ReAlnet09	.345
91	ReAlnet10	.336
92	ReAlnet06	.331
93	imagenet_l2_3_0	.330
94	ReAlnet02	.329
95	effnetb1_272x240	.328
96	mobilenet_v2_1_0_160	.327
97	ReAlnet05	.323
98	resnet-18_test_m	.322
99	ReAlnet07	.318
100	nasnet_mobile	.310
101	ReAlnet08	.309
102	ReAlnet04	.308
103	BiT-S-R101x3	.300
104	resnet50-moclr8deg	.285
105	resnet18_imagenet_full	.271
106	yudixie_resnet18_imagenet1kpret_0_240719	.256
107	hmax	.254
108	resnet50-vicregl0p75	.252
109	resnet50-barlow	.245
110	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.245
111	resnet50-vicreg	.244
112	convnext_xlarge:fb_in22k_ft_in1k	.243
113	efficientnet_b0	.242
114	omnivore_swinB	.240
115	resnet50_imagenet_10_seed-0	.233
116	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.230
117	vit_base_patch16_clip_224:openai_ft_in1k	.229
118	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.228
119	resnet152_imagenet_full	.215
120	yudixie_resnet50_imagenet1kpret_0_240908	.213
121	resnet50_tutorial	.213
122	Res2Net50_26w_4s	.211
123	resnet34_ecoset_full	.203
124	inception_v3	.201
125	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.188
126	cvt_cvt-21-384-in1k_4_LucyV4	.184
127	resnet-152_v2_pytorch	.180
128	convnext_tiny_sup	.173
129	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.166
130	convnext_large:fb_in22k_ft_in1k	.158
131	deit_small_imagenet_100_seed-0	.158
132	resnet_50_v2	.158
133	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.149
134	AdvProp_efficientnet-b4	.144
135	custom_model_cv_18_dagger_408	.139
136	efficientnet-b7	.131
137	convnext_small_imagenet_100_seed-0	.120
138	vit_large_patch14_clip_336:laion2b_ft_in1k	.119
139	mobilenet_v2_1_0_224	.114
140	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.107
141	densenet-201	.104
142	mobilenet_v2_1-4_224_pytorch	.103
143	mobilenet_v2_1_4_224	.103
144	AdvProp_efficientnet-b6	.101
145	cv_18_dagger_408_pretrained	.099
146	efficientnet_b0_imagenet_full	.099
147	convnext_tiny:in12k_ft_in1k	.097
148	AdvProp_efficientnet-b8	.093
149	mobilenet_v2_1_0_128	.092
150	resnet-50-robust	.084
151	AT_efficientnet-b2	.082
152	AdvProp_efficientnet-b2	.082
153	mobilenet_v2_1_0_192	.078
154	AdvProp_efficientnet-b7	.075
155	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.066
156	mobilenet_v2_1_3_224	.063
157	yudixie_resnet18_distance_reg_0_240719	.060
158	densenet-169	.057
159	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.057
160	efficientnet_b1_imagenet_full	.052
161	BiT-S-R152x2	.048
162	yudixie_resnet50_random_0_240908	.035
163	densenet-121	.035
164	yudixie_resnet18_distance_rotation_0_240719	.033
165	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.030
166	yudixie_resnet18_translation_reg_0_240719	.023
167	vgg_16	.022
168	yudixie_resnet18_distance_translation_rotation_0_240719	.019
169	ViT_L_32_imagenet1k	.015
170	cvt_cvt-13-384-in1k_4_LucyV4	.011
171	yudixie_resnet18_translation_rotation_0_240719	.009
172	vgg_19	.008
173	yudixie_resnet50_distance_rotation_0_240908	.002
174	yudixie_resnet18_distance_translation_0_240719	.001
175	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.000
176	yudixie_resnet18_rotation_reg_0_240719	.000
177	yudixie_resnet50_distance_translation_rotation_0_240908	.000
178	resnet50_imagenet_1_seed-0	.000
179	cvt_cvt-13-224-in1k_4_LucyV4	.000
180	yudixie_resnet50_translation_rotation_0_240908	.000
181	yudixie_resnet50_object_class_0_240908	.000
182	yudixie_resnet18_object_class_0_240719	.001
183	yudixie_resnet50_distance_translation_0_240908	.001
184	yudixie_resnet50_rotation_reg_0_240908	.001
185	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.001
186	yudixie_resnet50_category_class_0_240908	.002
187	yudixie_resnet50_translation_reg_0_240908	.002
188	yudixie_resnet18_category_class_0_240719	.005
189	yudixie_resnet50_distance_reg_0_240908	.016
190	grcnn	X
191	pnasnet_large_pytorch	X
192	nasnet_large	X
193	xception	X
194	vonegrcnn_47e	X
195	resnet_152_v1	X
196	resnet_152_v2	X
197	vonegrcnn_62e_nobn	X
198	inception_v4	X
199	BiT-S-R152x4	X
200	resnet_SIN_IN_FT_IN	X
201	resnet_101_v2	X
202	grcnn_109	X
203	vonegrcnn_52e_full	X
204	pnasnet_large	X

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

Not available

Data: tong.Coggan2024_fMRI.IT

Metric: rdm