Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("tong.Coggan2024_fMRI.V2-rdm")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	alexnet_training_seed_01	.630
2	alexnet_training_seed_10	.626
3	alexnet_training_seed_07	.578
4	alexnet_training_seed_03	.571
5	alexnet_training_seed_06	.570
6	alexnet_training_seed_04	.492
7	alexnet_training_seed_05	.455
8	convnext_small_imagenet_10_seed-0	.438
9	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.407
10	convnext_tiny_imagenet_full_seed-0	.383
11	alexnet_training_seed_09	.369
12	alexnet_training_seed_08	.313
13	alexnet_training_seed_02	.311
14	deit_small_imagenet_full_seed-0	.278
15	omnivore_swinS	.269
16	vit_relpos_base_patch16_clsgap_224:sw_in1k	.268
17	vit_large_patch14_clip_336:laion2b_ft_in1k	.262
18	yudixie_resnet18_random_0_240719	.255
19	vit_base_patch16_clip_224:openai_ft_in1k	.254
20	densenet-121	.247
21	convnext_small_imagenet_full_seed-0	.231
22	convnext_large:fb_in22k_ft_in1k	.227
23	deit_large_imagenet_full_seed-0	.220
24	deit_base_imagenet_full_seed-0	.216
25	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.212
26	resnext101_32x8d_wsl	.206
27	nasnet_mobile	.206
28	convnext_small_imagenet_1_seed-0	.203
29	deit_small_imagenet_10_seed-0	.201
30	resnet101_ecoset_full	.199
31	convnext_xlarge:fb_in22k_ft_in1k	.194
32	resnet50-vicreg	.189
33	resnet50-vicregl0p75	.181
34	AdvProp_efficientnet-b2	.178
35	AT_efficientnet-b2	.178
36	mobilenet_v2_1_0_128	.175
37	BiT-S-R50x1	.172
38	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.170
39	resnet50_imagenet_100_seed-0	.167
40	resnet50_ecoset_full	.164
41	resnet50-barlow	.163
42	yolos_tiny	.163
43	resnet50_primary_visual_cortex	.161
44	resnet50-SIN_IN_IN	.159
45	vit_large_patch14_clip_224:laion2b_ft_in1k	.149
46	convnext_large_imagenet_full_seed-0	.147
47	artResNet18_1	.143
48	deit_small_imagenet_1_seed-0	.142
49	resnet50_robust_l2_eps3	.141
50	convnext_tiny:in12k_ft_in1k	.138
51	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.137
52	resnet_101_v1	.135
53	resnet50-SIN	.133
54	resnet-18_test_m	.130
55	shufflenet_v2_x1_0	.121
56	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.121
57	resnet50-VITO-8deg-cc	.121
58	resnet50-vitoimagevidnet8	.121
59	resnet50_robust_l2_eps1	.121
60	efficientnet_b0	.119
61	resnet_50_v2	.118
62	imagenet_l2_3_0	.117
63	omnivore_swinB	.116
64	resnet18_imagenet_full	.112
65	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.111
66	convnext_base:clip_laiona_augreg_ft_in1k_384	.107
67	voneresnet-50-non_stochastic	.107
68	resnet18_ecoset_full	.106
69	convnext_base_imagenet_full_seed-0	.105
70	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.101
71	resnet152_ecoset_full	.100
72	Res2Net50_26w_4s	.100
73	hmax	.097
74	resnet50-moclr8deg	.097
75	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.096
76	resnet50-vicregl0p9	.094
77	cvt_cvt-21-224-in1k_4_LucyV4	.092
78	antialiased-r50	.089
79	resnet101_imagenet_full	.087
80	resnet152_imagenet_full	.086
81	resnet34_ecoset_full	.085
82	voneresnet-50-robust	.084
83	mobilenet_v2_1_0_160	.080
84	voneresnet-50	.078
85	resnet50_imagenet_full	.074
86	deit_small_imagenet_100_seed-0	.074
87	resnet-152_v2_pytorch	.073
88	yudixie_resnet50_rotation_reg_0_240908	.073
89	BiT-S-R101x1	.072
90	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.069
91	inception_v1	.067
92	convnext_tiny_sup	.063
93	resnet_50_v1_spiking_l4	.061
94	resnet_50_v1_spiking_l4a	.061
95	resnet_50_v1	.061
96	resnet50-sup	.061
97	resnet_50_v1_spiking	.061
98	custom_model_cv_18_dagger_408	.061
99	mobilenet_v2_1_4_224	.059
100	densenet-201	.058
101	cvt_cvt-21-384-in1k_4_LucyV4	.057
102	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.057
103	focalnet_tiny_lrf_in1k	.056
104	blt_vs	.056
105	resnet34_imagenet_full	.055
106	resnext101_32x32d_wsl	.053
107	mobilenet_v2_1_0_224	.052
108	VOneCORnet-S	.051
109	vit_large_patch14_clip_224:openai_ft_in1k	.048
110	convnext_femto_ols:d1_in1k	.047
111	efficientnet_b2_imagenet_full	.044
112	mobilenet_v2_0_75_160	.043
113	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.043
114	resnext101_32x48d_wsl	.041
115	ReAlnet04	.040
116	ReAlnet10	.040
117	resnet50-SIN_IN	.038
118	ReAlnet08	.038
119	ReAlnet05	.037
120	BiT-S-R50x3	.037
121	ReAlnet01	.037
122	convnext_small_imagenet_100_seed-0	.037
123	effnetb1_272x240	.036
124	ReAlnet03	.036
125	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.036
126	BiT-S-R101x3	.036
127	cvt_cvt-13-224-in1k_4_LucyV4	.035
128	ReAlnet02	.034
129	inception_v3	.033
130	ReAlnet07	.032
131	resnet-50-robust	.031
132	ReAlnet10_cornet	.030
133	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.030
134	cv_18_dagger_408_pretrained	.029
135	densenet-169	.028
136	ReAlnet06	.027
137	ReAlnet09	.026
138	cvt_cvt-13-384-in1k_4_LucyV4	.026
139	ReAlnet05_cornet	.025
140	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.025
141	ReAlnet08_cornet	.025
142	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.024
143	ReAlnet07_cornet	.024
144	ReAlnet03_cornet	.023
145	yudixie_resnet50_random_0_240908	.023
146	BiT-S-R152x2	.023
147	ReAlnet04_cornet	.022
148	resnet50_imagenet_10_seed-0	.021
149	ReAlnet06_cornet	.021
150	ReAlnet01_cornet	.020
151	ReAlnet02_cornet	.018
152	briaai_rmbg_1_4	.016
153	ReAlnet09_cornet	.016
154	resnet50_tutorial	.014
155	resnet_50_v1_spiking_l3	.014
156	yudixie_resnet50_imagenet1kpret_0_240908	.014
157	efficientnet-b7	.014
158	AdvProp_efficientnet-b6	.013
159	mobilenet_v2_1-4_224_pytorch	.011
160	efficientnet_b0_imagenet_full	.010
161	AdvProp_efficientnet-b8	.010
162	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.010
163	AdvProp_efficientnet-b4	.009
164	yudixie_resnet18_imagenet1kpret_0_240719	.008
165	mobilenet_v2_1_3_224	.005
166	efficientnet_b1_imagenet_full	.004
167	yudixie_resnet18_distance_reg_0_240719	.003
168	yudixie_resnet50_distance_reg_0_240908	.003
169	yudixie_resnet18_rotation_reg_0_240719	.003
170	yudixie_resnet50_distance_translation_rotation_0_240908	.003
171	yudixie_resnet18_distance_rotation_0_240719	.002
172	ViT_L_32_imagenet1k	.002
173	mobilenet_v2_1_0_192	.001
174	yudixie_resnet50_translation_rotation_0_240908	.001
175	yudixie_resnet50_distance_rotation_0_240908	.001
176	resnet50_imagenet_1_seed-0	.001
177	vgg_16	.001
178	AdvProp_efficientnet-b7	.000
179	yudixie_resnet18_translation_reg_0_240719	.000
180	mobilenet_v2_0_75_224	.000
181	yudixie_resnet18_category_class_0_240719	.000
182	yudixie_resnet50_object_class_0_240908	.000
183	mobilenet_v2_0_5_224	.000
184	vgg_19	.000
185	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.001
186	yudixie_resnet18_object_class_0_240719	.001
187	yudixie_resnet50_category_class_0_240908	.001
188	yudixie_resnet50_translation_reg_0_240908	.001
189	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.002
190	yudixie_resnet18_distance_translation_rotation_0_240719	.002
191	yudixie_resnet18_translation_rotation_0_240719	.003
192	yudixie_resnet50_distance_translation_0_240908	.003
193	yudixie_resnet18_distance_translation_0_240719	.005
194	vonegrcnn_62e_nobn
195	resnet_SIN_IN_FT_IN
196	resnet_152_v2
197	mobilenet_v2_0_75_192
198	vonegrcnn_47e
199	BiT-S-R152x4
200	mobilenet_v2_0_5_192
201	xception
202	pnasnet_large
203	grcnn
204	grcnn_109
205	inception_v4
206	resnet_152_v1
207	nasnet_large
208	resnet_101_v2
209	pnasnet_large_pytorch
210	vonegrcnn_52e_full

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.V2

Metric: rdm