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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_SIN	.636
2	alexnet_training_seed_01	.630
3	alexnet_training_seed_10	.626
4	alexnet_training_seed_07	.578
5	alexnet_training_seed_03	.571
6	alexnet_training_seed_06	.570
7	alexnet_training_seed_04	.492
8	AlexNet_SIN_fov16	.485
9	AlexNet_SIN_fov12	.458
10	alexnet_training_seed_05	.455
11	convnext_small_imagenet_10_seed-0	.438
12	alexnet_training_seed_01_fov12	.415
13	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.407
14	convnext_tiny_imagenet_full_seed-0	.383
15	alexnet_training_seed_01_fov16	.372
16	alexnet_training_seed_09	.369
17	alexnet	.335
18	alexnet_ks_torevert	.335
19	grcnn	.327
20	alexnet_training_seed_08	.313
21	alexnet_training_seed_02	.311
22	alexnet_fov16	.285
23	deit_small_imagenet_full_seed-0	.278
24	alexnet_fov12	.273
25	omnivore_swinS	.269
26	vit_relpos_base_patch16_clsgap_224:sw_in1k	.268
27	vit_large_patch14_clip_336:laion2b_ft_in1k	.262
28	yudixie_resnet18_random_0_240719	.255
29	vit_base_patch16_clip_224:openai_ft_in1k	.254
30	densenet-121	.247
31	convnext_small_imagenet_full_seed-0	.231
32	convnext_large:fb_in22k_ft_in1k	.227
33	deit_large_imagenet_full_seed-0	.220
34	alexnet_training_seed_01_fov4	.220
35	deit_base_imagenet_full_seed-0	.216
36	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.212
37	resnext101_32x8d_wsl	.206
38	nasnet_mobile	.206
39	convnext_small_imagenet_1_seed-0	.203
40	deit_small_imagenet_10_seed-0	.201
41	grcnn_109	.200
42	resnet101_ecoset_full	.199
43	convnext_xlarge:fb_in22k_ft_in1k	.194
44	resnet50-vicreg	.189
45	resnet50-vicregl0p75	.181
46	AdvProp_efficientnet-b2	.178
47	AT_efficientnet-b2	.178
48	mobilenet_v2_1_0_128	.175
49	BiT-S-R50x1	.172
50	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.170
51	s3d	.167
52	resnet50_imagenet_100_seed-0	.167
53	resnet50_ecoset_full	.164
54	resnet50-barlow	.163
55	yolos_tiny	.163
56	resnet50_primary_visual_cortex	.161
57	resnet50-SIN_IN_IN	.159
58	resnet_SIN_IN_FT_IN	.159
59	antialias-resnet152	.155
60	vit_large_patch14_clip_224:laion2b_ft_in1k	.149
61	resnet_152_v1	.148
62	convnext_large_imagenet_full_seed-0	.147
63	artResNet18_1	.143
64	deit_small_imagenet_1_seed-0	.142
65	resnet50_robust_l2_eps3	.141
66	convnext_tiny:in12k_ft_in1k	.138
67	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.137
68	resnet_101_v1	.135
69	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.133
70	resnext101_32x16d_wsl	.133
71	resnet50-SIN	.133
72	resnet_101_v2	.131
73	resnet-18_test_m	.130
74	shufflenet_v2_x1_0	.121
75	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.121
76	resnet50-VITO-8deg-cc	.121
77	resnet50-vitoimagevidnet8	.121
78	resnet50_robust_l2_eps1	.121
79	efficientnet_b0	.119
80	antialiased-rnext101_32x8d	.118
81	resnet_50_v2	.118
82	imagenet_l2_3_0	.117
83	omnivore_swinB	.116
84	compact_resnet50_IT	.114
85	resnet18_imagenet_full	.112
86	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.111
87	mc3_18	.111
88	convnext_base:clip_laiona_augreg_ft_in1k_384	.107
89	r3d_18	.107
90	voneresnet-50-non_stochastic	.107
91	resnet18_ecoset_full	.106
92	convnext_base_imagenet_full_seed-0	.105
93	vonegrcnn_62e_nobn	.105
94	regnet_y_400mf	.104
95	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.101
96	resnet152_ecoset_full	.100
97	Res2Net50_26w_4s	.100
98	hmax	.097
99	BiT-S-R152x4	.097
100	inception_v4	.097
101	resnet50-moclr8deg	.097
102	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.096
103	resnet50-vicregl0p9	.094
104	cvt_cvt-21-224-in1k_4_LucyV4	.092
105	antialiased-r50	.089
106	AlexNet_SIN_fov4	.089
107	resnet50_ewconplus_wzc	.088
108	resnet101_imagenet_full	.087
109	resnet152_imagenet_full	.086
110	resnet34_ecoset_full	.085
111	voneresnet-50-robust	.084
112	SeLaVi-VGG-Sound	.081
113	compact_resnet50_robust_IT	.080
114	mobilenet_v2_1_0_160	.080
115	voneresnet-50	.078
116	pnasnet_large	.076
117	resnet50_imagenet_full	.074
118	deit_small_imagenet_100_seed-0	.074
119	resnet-152_v2_pytorch	.073
120	yudixie_resnet50_rotation_reg_0_240908	.073
121	BiT-S-R101x1	.072
122	SeLaVi-AVE	.071
123	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.069
124	inception_v1	.067
125	convnext_tiny_sup	.063
126	resnet_50_v1_spiking	.061
127	resnet_50_v1_spiking_l4	.061
128	resnet_50_v1_spiking_l4a	.061
129	resnet_50_v1	.061
130	resnet50-sup	.061
131	custom_model_cv_18_dagger_408	.061
132	mobilenet_v2_1_4_224	.059
133	densenet-201	.058
134	cvt_cvt-21-384-in1k_4_LucyV4	.057
135	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.057
136	focalnet_tiny_lrf_in1k	.056
137	blt_vs	.056
138	resnet34_imagenet_full	.055
139	resnet_152_v2	.054
140	resnext101_32x32d_wsl	.053
141	mobilenet_v2_1_0_224	.052
142	VOneCORnet-S	.051
143	r2plus1d_18	.050
144	vit_large_patch14_clip_224:openai_ft_in1k	.048
145	convnext_femto_ols:d1_in1k	.047
146	compact_resnet50_V4	.045
147	alexnet_fov4	.044
148	efficientnet_b2_imagenet_full	.044
149	mobilenet_v2_0_75_160	.043
150	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.043
151	resnext101_32x48d_wsl	.041
152	ReAlnet04	.040
153	ReAlnet07_ALL	.040
154	ReAlnet10	.040
155	resnet50-SIN_IN	.038
156	ReAlnet08	.038
157	ReAlnet05	.037
158	BiT-S-R50x3	.037
159	ReAlnet01	.037
160	convnext_small_imagenet_100_seed-0	.037
161	ReAlnet01_cornet_fov4	.037
162	effnetb1_272x240	.036
163	ReAlnet03	.036
164	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.036
165	BiT-S-R101x3	.036
166	cvt_cvt-13-224-in1k_4_LucyV4	.035
167	ReAlnet08_ALL	.035
168	ReAlnet02	.034
169	inception_v3	.033
170	ReAlnet04_ALL	.033
171	ReAlnet07	.032
172	ReAlnet02_ALL	.032
173	ReAlnet09_ALL	.031
174	ReAlnet05_ALL	.031
175	resnet-50-robust	.031
176	ReAlnet10_cornet	.030
177	ReAlnet06_ALL	.030
178	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.030
179	ReAlnet10_ALL	.030
180	ReAlnet01_ALL	.029
181	cv_18_dagger_408_pretrained	.029
182	ReAlnet03_ALL	.028
183	densenet-169	.028
184	ReAlnet06	.027
185	ReAlnet09	.026
186	cvt_cvt-13-384-in1k_4_LucyV4	.026
187	ReAlnet05_cornet	.025
188	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.025
189	ReAlnet08_cornet	.025
190	resnet18_imagenet21kP	.024
191	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.024
192	ReAlnet07_cornet	.024
193	ReAlnet03_cornet	.023
194	yudixie_resnet50_random_0_240908	.023
195	BiT-S-R152x2	.023
196	nasnet_large	.022
197	ReAlnet04_cornet	.022
198	resnet50_imagenet_10_seed-0	.021
199	ReAlnet06_cornet	.021
200	compact_vgg19_V4	.020
201	compact_cornets_IT	.020
202	ReAlnet01_cornet	.020
203	ReAlnet02_cornet	.018
204	compact_vgg19_IT	.018
205	briaai_rmbg_1_4	.016
206	ReAlnet09_cornet	.016
207	yudixie_resnet50_imagenet1kpret_0_240908	.014
208	resnet50_tutorial	.014
209	resnet_50_v1_spiking_l3	.014
210	yudixie_resnet50_imagenet1kpret_0_240312	.014
211	efficientnet-b7	.014
212	AdvProp_efficientnet-b6	.013
213	xception	.012
214	mobilenet_v2_1-4_224_pytorch	.011
215	efficientnet_b0_imagenet_full	.010
216	AdvProp_efficientnet-b8	.010
217	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.010
218	AdvProp_efficientnet-b4	.009
219	yudixie_resnet18_imagenet1kpret_0_240719	.008
220	mobilenet_v2_1_3_224	.005
221	SeLaVi-Kinetics400	.005
222	vonegrcnn_47e	.005
223	vonegrcnn_52e_full	.004
224	tv_efficientnet-b1	.004
225	efficientnet_b1_imagenet_full	.004
226	yudixie_resnet18_distance_reg_0_240719	.003
227	yudixie_resnet50_distance_reg_0_240908	.003
228	yudixie_resnet18_rotation_reg_0_240719	.003
229	yudixie_resnet50_distance_translation_rotation_0_240908	.003
230	yudixie_resnet18_distance_rotation_0_240719	.002
231	ViT_L_32_imagenet1k	.002
232	mobilenet_v2_1_0_192	.001
233	yudixie_resnet50_translation_rotation_0_240908	.001
234	yudixie_resnet50_distance_rotation_0_240908	.001
235	resnet50_imagenet_1_seed-0	.001
236	vgg_16	.001
237	AdvProp_efficientnet-b7	.000
238	yudixie_resnet18_translation_reg_0_240719	.000
239	mobilenet_v2_0_75_224	.000
240	yudixie_resnet18_category_class_0_240719	.000
241	yudixie_resnet50_object_class_0_240908	.000
242	mobilenet_v2_0_5_224	.000
243	vgg_19	.000
244	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.001
245	yudixie_resnet18_object_class_0_240719	.001
246	yudixie_resnet50_category_class_0_240908	.001
247	yudixie_resnet50_translation_reg_0_240908	.001
248	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.002
249	yudixie_resnet18_distance_translation_rotation_0_240719	.002
250	yudixie_resnet18_translation_rotation_0_240719	.003
251	yudixie_resnet50_distance_translation_0_240908	.003
252	yudixie_resnet18_distance_translation_0_240719	.005
253	pnasnet_large_pytorch
254	mobilenet_v2_0_5_192
255	mobilenet_v2_0_75_192
256	ReAlnet01_cornet_fov12	nan
257	fixres_resnext101_32x48d_wsl
258	compact_resnet50_robust_V4	nan
259	ReAlnet01_cornet_fov16	nan
260	mvit_v1_b
261	resnet50_eMMCR_Vanilla
262	compact_cornets_V4	nan
263	SeLaVi-Kinetics-Sound
264	mvit_v2_s

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