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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	yudixie_wbh_object_class_scaling_0415_run_3	.490
9	AlexNet_SIN_fov16	.485
10	AlexNet_SIN_fov12	.458
11	alexnet_training_seed_05	.455
12	convnext_small_imagenet_10_seed-0	.438
13	alexnet_training_seed_01_fov12	.415
14	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.407
15	convnext_tiny_imagenet_full_seed-0	.383
16	alexnet_training_seed_01_fov16	.372
17	alexnet_training_seed_09	.369
18	yudixie_wbh_object_class_scaling_0415_run_1	.361
19	yudixie_wbh_object_class_scaling_0415_run_0	.361
20	alexnet	.335
21	alexnet_ks_torevert	.335
22	grcnn	.327
23	alexnet_training_seed_08	.313
24	alexnet_training_seed_02	.311
25	deepeisnn_ei_cifar10_resnet18	.303
26	alexnet_fov16	.285
27	pr1_stl10_disentangled_alpha04	.281
28	deit_small_imagenet_full_seed-0	.278
29	alexnet_fov12	.273
30	omnivore_swinS	.269
31	vit_relpos_base_patch16_clsgap_224:sw_in1k	.268
32	convnext_base_fb_in1k_gram_aligned_dinov3	.263
33	vit_large_patch14_clip_336:laion2b_ft_in1k	.262
34	yudixie_resnet18_random_0_240719	.255
35	vit_base_patch16_clip_224:openai_ft_in1k	.254
36	deepeisnn_ei_cifar10_vgg19	.252
37	densenet-121	.247
38	convnext_small_imagenet_full_seed-0	.231
39	convnext_large:fb_in22k_ft_in1k	.227
40	deit_large_imagenet_full_seed-0	.220
41	alexnet_training_seed_01_fov4	.220
42	deit_base_imagenet_full_seed-0	.216
43	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.212
44	resnext101_32x8d_wsl	.206
45	nasnet_mobile	.206
46	convnext_small_imagenet_1_seed-0	.203
47	deit_small_imagenet_10_seed-0	.201
48	grcnn_109	.200
49	resnet101_ecoset_full	.199
50	convnext_base_fb_in22k_ft_in1k	.197
51	convnext_xlarge:fb_in22k_ft_in1k	.194
52	resnet50-vicreg	.189
53	aughost_fair_resnet18	.183
54	resnet50-vicregl0p75	.181
55	AT_efficientnet-b2	.178
56	AdvProp_efficientnet-b2	.178
57	mobilenet_v2_1_0_128	.175
58	BiT-S-R50x1	.172
59	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.170
60	s3d	.167
61	resnet50_imagenet_100_seed-0	.167
62	resnet50_ecoset_full	.164
63	resnet50-barlow	.163
64	yolos_tiny	.163
65	resnet50_primary_visual_cortex	.161
66	resnet50-SIN_IN_IN	.159
67	resnet_SIN_IN_FT_IN	.159
68	antialias-resnet152	.155
69	vit_large_patch14_clip_224:laion2b_ft_in1k	.149
70	resnet_152_v1	.148
71	convnext_large_imagenet_full_seed-0	.147
72	dinov2_vitg14_lc	.145
73	artResNet18_1	.143
74	deit_small_imagenet_1_seed-0	.142
75	resnet50_robust_l2_eps3	.141
76	convnext_tiny:in12k_ft_in1k	.138
77	resnet50_st_wzc_seed3_2_323	.138
78	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.137
79	resnet_101_v1	.135
80	vit_huge_clip336_laion	.134
81	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.133
82	resnext101_32x16d_wsl	.133
83	resnet50-SIN	.133
84	resnet_101_v2	.131
85	resnet-18_test_m	.130
86	shufflenet_v2_x1_0	.121
87	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.121
88	resnet50-vitoimagevidnet8	.121
89	resnet50-VITO-8deg-cc	.121
90	resnet50_robust_l2_eps1	.121
91	resnet50_hvs_wzc	.120
92	efficientnet_b0	.119
93	antialiased-rnext101_32x8d	.118
94	resnet_50_v2	.118
95	imagenet_l2_3_0	.117
96	omnivore_swinB	.116
97	compact_resnet50_IT	.114
98	resnet18_imagenet_full	.112
99	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.111
100	mc3_18	.111
101	convnext_base:clip_laiona_augreg_ft_in1k_384	.107
102	r3d_18	.107
103	voneresnet-50-non_stochastic	.107
104	resnet50_st_wzc_seed7_2_323	.107
105	resnet18_ecoset_full	.106
106	convnext_base_imagenet_full_seed-0	.105
107	vonegrcnn_62e_nobn	.105
108	regnet_y_400mf	.104
109	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.101
110	resnet152_ecoset_full	.100
111	Res2Net50_26w_4s	.100
112	hmax	.097
113	BiT-S-R152x4	.097
114	inception_v4	.097
115	resnet50-moclr8deg	.097
116	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.096
117	resnet50-vicregl0p9	.094
118	dinov2_vitl14_lc	.094
119	resnet50_ewconplus_wzc_seed6_2_323	.094
120	cvt_cvt-21-224-in1k_4_LucyV4	.092
121	antialiased-r50	.089
122	AlexNet_SIN_fov4	.089
123	resnet50_ewconplus_wzc	.088
124	resnet101_imagenet_full	.087
125	resnet152_imagenet_full	.086
126	resnet34_ecoset_full	.085
127	voneresnet-50-robust	.084
128	SeLaVi-VGG-Sound	.081
129	compact_resnet50_robust_IT	.080
130	vit_base_patch14_dinov2-lvd142m	.080
131	mobilenet_v2_1_0_160	.080
132	resnet50_st_wzc_2	.079
133	voneresnet-50	.078
134	vit_large_clip336_openai	.077
135	pnasnet_large	.076
136	resnet50_imagenet_full	.074
137	deit_small_imagenet_100_seed-0	.074
138	resnet-152_v2_pytorch	.073
139	yudixie_resnet50_rotation_reg_0_240908	.073
140	BiT-S-R101x1	.072
141	resnet50_ewconplus_wzc_seed5_2__323	.072
142	SeLaVi-AVE	.071
143	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.069
144	inception_v1	.067
145	resnet50_ewconplus_wzc_seed2_2__323	.064
146	resnet50_st_wzc_seed6_2_323	.063
147	convnext_tiny_sup	.063
148	dinov2_vitl14_lc_res336	.062
149	resnet_50_v1_spiking_l4a	.061
150	resnet_50_v1_spiking_l4	.061
151	resnet_50_v1_spiking	.061
152	resnet_50_v1	.061
153	resnet50-sup	.061
154	custom_model_cv_18_dagger_408	.061
155	mobilenet_v2_1_4_224	.059
156	densenet-201	.058
157	cvt_cvt-21-384-in1k_4_LucyV4	.057
158	yudixie_wbh_object_class_scaling_0415_run_2	.057
159	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.057
160	focalnet_tiny_lrf_in1k	.056
161	blt_vs	.056
162	resnet34_imagenet_full	.055
163	resnet_152_v2	.054
164	resnext101_32x32d_wsl	.053
165	mobilenet_v2_1_0_224	.052
166	VOneCORnet-S	.051
167	r2plus1d_18	.050
168	vit_large_patch14_clip_224:openai_ft_in1k	.048
169	convnext_femto_ols:d1_in1k	.047
170	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.047
171	deit3_base_patch16_224_fb_in22k_ft_in1k	.047
172	compact_resnet50_V4	.045
173	alexnet_fov4	.044
174	efficientnet_b2_imagenet_full	.044
175	mobilenet_v2_0_75_160	.043
176	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.043
177	resnext101_32x48d_wsl	.041
178	ReAlnet04	.040
179	eva02_large_in22k	.040
180	ReAlnet07_ALL	.040
181	deepeisnn_ei_imagenet_resnet18	.040
182	ReAlnet10	.040
183	resnet50-SIN_IN	.038
184	ReAlnet08	.038
185	ReAlnet05	.037
186	BiT-S-R50x3	.037
187	ReAlnet01	.037
188	convnext_small_imagenet_100_seed-0	.037
189	ReAlnet01_cornet_fov4	.037
190	effnetb1_272x240	.036
191	ReAlnet03	.036
192	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.036
193	BiT-S-R101x3	.036
194	cvt_cvt-13-224-in1k_4_LucyV4	.035
195	ReAlnet08_ALL	.035
196	ReAlnet02	.034
197	deit3_base_patch16_224_fb_in1k	.033
198	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.033
199	inception_v3	.033
200	ReAlnet04_ALL	.033
201	ReAlnet07	.032
202	vit_base_patch14_reg4_dinov2-lvd142m	.032
203	ReAlnet02_ALL	.032
204	ReAlnet09_ALL	.031
205	ReAlnet05_ALL	.031
206	resnet-50-robust	.031
207	ReAlnet10_cornet	.030
208	ReAlnet06_ALL	.030
209	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.030
210	ReAlnet10_ALL	.030
211	ReAlnet01_ALL	.029
212	cv_18_dagger_408_pretrained	.029
213	ReAlnet03_ALL	.028
214	densenet-169	.028
215	ReAlnet06	.027
216	predictive_coding_pc	.026
217	ReAlnet09	.026
218	cvt_cvt-13-384-in1k_4_LucyV4	.026
219	convnext_large_in22k_supervised	.025
220	ReAlnet05_cornet	.025
221	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.025
222	ReAlnet08_cornet	.025
223	resnet18_imagenet21kP	.024
224	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.024
225	ReAlnet07_cornet	.024
226	ReAlnet03_cornet	.023
227	yudixie_resnet50_random_0_240908	.023
228	BiT-S-R152x2	.023
229	nasnet_large	.022
230	ReAlnet04_cornet	.022
231	resnet50_imagenet_10_seed-0	.021
232	ReAlnet06_cornet	.021
233	compact_vgg19_V4	.020
234	compact_cornets_IT	.020
235	ReAlnet01_cornet	.020
236	ReAlnet02_cornet	.018
237	compact_vgg19_IT	.018
238	briaai_rmbg_1_4	.016
239	dinov2_vitg14_reg_lc	.016
240	convnext_xxlarge_clip	.016
241	ReAlnet09_cornet	.016
242	dinov2_vitl14_reg_lc_featread	.015
243	dinov2_vitl14_reg_lc	.015
244	yudixie_resnet50_imagenet1kpret_0_240312	.014
245	resnet_50_v1_spiking_l3	.014
246	yudixie_resnet50_imagenet1kpret_0_240908	.014
247	resnet50_tutorial	.014
248	efficientnet-b7	.014
249	AdvProp_efficientnet-b6	.013
250	xception	.012
251	mobilenet_v2_1-4_224_pytorch	.011
252	convnext_large_clip_laion2b_finelayers	.011
253	efficientnet_b0_imagenet_full	.010
254	AdvProp_efficientnet-b8	.010
255	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.010
256	AdvProp_efficientnet-b4	.009
257	yudixie_wbh_object_class_scaling_0415_imagenet	.008
258	yudixie_resnet18_imagenet1kpret_0_240719	.008
259	vit_base_patch16_dinov3-lvd1689m	.006
260	mobilenet_v2_1_3_224	.005
261	SeLaVi-Kinetics400	.005
262	vonegrcnn_47e	.005
263	vonegrcnn_52e_full	.004
264	tv_efficientnet-b1	.004
265	efficientnet_b1_imagenet_full	.004
266	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.003
267	yudixie_resnet18_distance_reg_0_240719	.003
268	yudixie_resnet50_distance_reg_0_240908	.003
269	yudixie_resnet18_rotation_reg_0_240719	.003
270	yudixie_resnet50_distance_translation_rotation_0_240908	.003
271	yudixie_resnet18_distance_rotation_0_240719	.002
272	ViT_L_32_imagenet1k	.002
273	convnext_base_fb_in1k	.002
274	mobilenet_v2_1_0_192	.001
275	yudixie_resnet50_translation_rotation_0_240908	.001
276	yudixie_resnet50_distance_rotation_0_240908	.001
277	resnet50_imagenet_1_seed-0	.001
278	vgg_16	.001
279	AdvProp_efficientnet-b7	.000
280	yudixie_resnet18_translation_reg_0_240719	.000
281	mobilenet_v2_0_75_224	.000
282	resnet18_fair	.000
283	yudixie_resnet18_category_class_0_240719	.000
284	yudixie_resnet50_object_class_0_240908	.000
285	mobilenet_v2_0_5_224	.000
286	vgg_19	.000
287	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.001
288	yudixie_resnet18_object_class_0_240719	.001
289	yudixie_resnet50_category_class_0_240908	.001
290	yudixie_resnet50_translation_reg_0_240908	.001
291	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.002
292	yudixie_resnet18_distance_translation_rotation_0_240719	.002
293	yudixie_resnet18_translation_rotation_0_240719	.003
294	yudixie_resnet50_distance_translation_0_240908	.003
295	yudixie_resnet18_distance_translation_0_240719	.005
296	pnasnet_large_halfPrecision
297	ReAlnet01_cornet_fov16	1.0
298	ReAlnet01_cornet_fov12	1.0
299	compact_cornets_V4	1.0
300	compact_resnet50_robust_V4	1.0
301	mvit_v2_s
302	SeLaVi-Kinetics-Sound
303	resnet50_eMMCR_Vanilla
304	mvit_v1_b
305	fixres_resnext101_32x48d_wsl
306	mobilenet_v2_0_75_192
307	mobilenet_v2_0_5_192
308	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

0.45.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_fMRI.V2

Metric: rdm