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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	gabor_filter_entropy_4x4_v2	.947
2	gabor_filter_entropy_4x4	.941
3	gabor_filter_entropy_4x4_v2_forcedCosine	.906
4	AlexNet_SIN	.636
5	alexnet_training_seed_01	.630
6	alexnet_training_seed_10	.626
7	mehrer2020_alexnet_training_seed_07	.603
8	alexnet_training_seed_07	.578
9	alexnet_training_seed_03	.571
10	alexnet_training_seed_06	.570
11	mehrer2020_alexnet_training_seed_06	.547
12	mehrer2020_alexnet_training_seed_10	.533
13	mehrer2020_alexnet_training_seed_08	.498
14	mehrer2020_alexnet_training_seed_01	.498
15	alexnet_training_seed_04	.492
16	yudixie_wbh_object_class_scaling_0415_run_3	.490
17	AlexNet_SIN_fov16	.485
18	mehrer2020_alexnet_training_seed_04	.480
19	AlexNet_SIN_fov12	.458
20	alexnet_training_seed_05	.455
21	convnext_small_imagenet_10_seed-0	.438
22	mehrer2020_alexnet_training_seed_02	.431
23	mehrer2020_alexnet_training_seed_09	.421
24	alexnet_training_seed_01_fov12	.415
25	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.407
26	mehrer2020_alexnet_training_seed_05	.403
27	mehrer2020_alexnet_training_seed_03	.403
28	convnext_tiny_imagenet_full_seed-0	.383
29	alexnet_training_seed_01_fov16	.372
30	alexnet_training_seed_09	.369
31	yudixie_wbh_object_class_scaling_0415_run_1	.361
32	yudixie_wbh_object_class_scaling_0415_run_0	.361
33	alexnet	.335
34	alexnet_ks_torevert	.335
35	grcnn	.327
36	alexnet_training_seed_08	.313
37	mehrer2020_alexnet_training_seed_01_fov16	.312
38	alexnet_training_seed_02	.311
39	deepeisnn_ei_cifar10_resnet18	.303
40	alexnet_fov16	.285
41	pr1_stl10_disentangled_alpha04	.281
42	deit_small_imagenet_full_seed-0	.278
43	alexnet_fov12	.273
44	omnivore_swinS	.269
45	vit_relpos_base_patch16_clsgap_224:sw_in1k	.268
46	convnext_base_fb_in1k_gram_aligned_dinov3	.263
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.262
48	yudixie_resnet18_random_0_240719	.255
49	vit_base_patch16_clip_224:openai_ft_in1k	.254
50	deepeisnn_ei_cifar10_vgg19	.252
51	densenet-121	.247
52	convnext_small_imagenet_full_seed-0	.231
53	convnext_large:fb_in22k_ft_in1k	.227
54	mehrer2020_alexnet_training_seed_01_fov12	.226
55	gabor_filter_mean_abs_4x4_v2	.226
56	deit_large_imagenet_full_seed-0	.220
57	alexnet_training_seed_01_fov4	.220
58	deit_base_imagenet_full_seed-0	.216
59	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.212
60	resnext101_32x8d_wsl	.206
61	nasnet_mobile	.206
62	convnext_small_imagenet_1_seed-0	.203
63	deit_small_imagenet_10_seed-0	.201
64	grcnn_109	.200
65	resnet101_ecoset_full	.199
66	convnext_base_fb_in22k_ft_in1k	.197
67	convnext_xlarge:fb_in22k_ft_in1k	.194
68	resnet50-vicreg	.189
69	resnet50-vicregl0p75	.181
70	AT_efficientnet-b2	.178
71	AdvProp_efficientnet-b2	.178
72	mobilenet_v2_1_0_128	.175
73	BiT-S-R50x1	.172
74	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.170
75	s3d	.167
76	resnet50_imagenet_100_seed-0	.167
77	resnet50_ecoset_full	.164
78	resnet50-barlow	.163
79	yolos_tiny	.163
80	resnet50_primary_visual_cortex	.161
81	resnet50-SIN_IN_IN	.159
82	resnet_SIN_IN_FT_IN	.159
83	antialias-resnet152	.155
84	vit_large_patch14_clip_224:laion2b_ft_in1k	.149
85	resnet_152_v1	.148
86	convnext_large_imagenet_full_seed-0	.147
87	dinov2_vitg14_lc	.145
88	artResNet18_1	.143
89	deit_small_imagenet_1_seed-0	.142
90	resnet50_robust_l2_eps3	.141
91	convnext_tiny:in12k_ft_in1k	.138
92	resnet50_st_wzc_seed3_2_323	.138
93	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.137
94	resnet_101_v1	.135
95	vit_huge_clip336_laion	.134
96	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.133
97	resnext101_32x16d_wsl	.133
98	resnet50-SIN	.133
99	resnet_101_v2	.131
100	resnet-18_test_m	.130
101	shufflenet_v2_x1_0	.121
102	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.121
103	resnet50-vitoimagevidnet8	.121
104	resnet50-VITO-8deg-cc	.121
105	resnet50_robust_l2_eps1	.121
106	resnet50_hvs_wzc	.120
107	efficientnet_b0	.119
108	antialiased-rnext101_32x8d	.118
109	resnet_50_v2	.118
110	imagenet_l2_3_0	.117
111	omnivore_swinB	.116
112	compact_resnet50_IT	.114
113	resnet18_imagenet_full	.112
114	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.111
115	mc3_18	.111
116	convnext_base:clip_laiona_augreg_ft_in1k_384	.107
117	r3d_18	.107
118	voneresnet-50-non_stochastic	.107
119	resnet50_st_wzc_seed7_2_323	.107
120	resnet18_ecoset_full	.106
121	convnext_base_imagenet_full_seed-0	.105
122	vonegrcnn_62e_nobn	.105
123	regnet_y_400mf	.104
124	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.101
125	resnet152_ecoset_full	.100
126	eicircuit_resnet18_bn_20260919	.100
127	Res2Net50_26w_4s	.100
128	hmax	.097
129	BiT-S-R152x4	.097
130	inception_v4	.097
131	resnet50-moclr8deg	.097
132	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.096
133	resnet50-vicregl0p9	.094
134	dinov2_vitl14_lc	.094
135	resnet50_ewconplus_wzc_seed6_2_323	.094
136	ijepa_vith14_linhead	.092
137	cvt_cvt-21-224-in1k_4_LucyV4	.092
138	antialiased-r50	.089
139	AlexNet_SIN_fov4	.089
140	resnet50_ewconplus_wzc	.088
141	resnet101_imagenet_full	.087
142	seresnext50_32x4d	.087
143	resnet152_imagenet_full	.086
144	resnet34_ecoset_full	.085
145	voneresnet-50-robust	.084
146	SeLaVi-VGG-Sound	.081
147	compact_resnet50_robust_IT	.080
148	vit_base_patch14_dinov2-lvd142m	.080
149	mobilenet_v2_1_0_160	.080
150	resnet50_st_wzc_2	.079
151	voneresnet-50	.078
152	vit_large_clip336_openai	.077
153	pnasnet_large	.076
154	resnet50_imagenet_full	.074
155	deit_small_imagenet_100_seed-0	.074
156	resnet-152_v2_pytorch	.073
157	yudixie_resnet50_rotation_reg_0_240908	.073
158	BiT-S-R101x1	.072
159	resnet50_ewconplus_wzc_seed5_2__323	.072
160	regnety_032	.072
161	SeLaVi-AVE	.071
162	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.069
163	inception_v1	.067
164	resnet50_ewconplus_wzc_seed2_2__323	.064
165	resnet50_st_wzc_seed6_2_323	.063
166	convnext_tiny_sup	.063
167	mehrer2020_alexnet_training_seed_01_fov4	.063
168	resnet50_simclr_linhead_01norm	.063
169	dinov2_vitl14_lc_res336	.062
170	resnet_50_v1_spiking_l4a	.061
171	resnet_50_v1_spiking_l4	.061
172	resnet_50_v1_spiking	.061
173	resnet_50_v1	.061
174	resnet50-sup	.061
175	custom_model_cv_18_dagger_408	.061
176	mobilenet_v2_1_4_224	.059
177	densenet-201	.058
178	cvt_cvt-21-384-in1k_4_LucyV4	.057
179	yudixie_wbh_object_class_scaling_0415_run_2	.057
180	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.057
181	focalnet_tiny_lrf_in1k	.056
182	blt_vs	.056
183	resnet34_imagenet_full	.055
184	resnet_152_v2	.054
185	resnext101_32x32d_wsl	.053
186	mobilenet_v2_1_0_224	.052
187	resnet50_barlowtwins_linhead	.051
188	VOneCORnet-S	.051
189	r2plus1d_18	.050
190	vit_large_patch14_clip_224:openai_ft_in1k	.048
191	convnext_femto_ols:d1_in1k	.047
192	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.047
193	deit3_base_patch16_224_fb_in22k_ft_in1k	.047
194	compact_resnet50_V4	.045
195	alexnet_fov4	.044
196	efficientnet_b2_imagenet_full	.044
197	mobilenet_v2_0_75_160	.043
198	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.043
199	resnext101_32x48d_wsl	.041
200	ReAlnet04	.040
201	eva02_large_in22k	.040
202	ReAlnet07_ALL	.040
203	deepeisnn_ei_imagenet_resnet18	.040
204	ReAlnet10	.040
205	resnet50_byol_linhead	.038
206	resnet50-SIN_IN	.038
207	ReAlnet08	.038
208	ReAlnet05	.037
209	BiT-S-R50x3	.037
210	ReAlnet01	.037
211	convnext_small_imagenet_100_seed-0	.037
212	ReAlnet01_cornet_fov4	.037
213	effnetb1_272x240	.036
214	ReAlnet03	.036
215	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.036
216	BiT-S-R101x3	.036
217	cvt_cvt-13-224-in1k_4_LucyV4	.035
218	ReAlnet08_ALL	.035
219	ReAlnet02	.034
220	deit3_base_patch16_224_fb_in1k	.033
221	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.033
222	inception_v3	.033
223	ReAlnet04_ALL	.033
224	ReAlnet07	.032
225	vit_base_patch14_reg4_dinov2-lvd142m	.032
226	ReAlnet02_ALL	.032
227	ReAlnet09_ALL	.031
228	ReAlnet05_ALL	.031
229	resnet-50-robust	.031
230	ReAlnet10_cornet	.030
231	ReAlnet06_ALL	.030
232	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.030
233	ReAlnet10_ALL	.030
234	ReAlnet01_ALL	.029
235	cv_18_dagger_408_pretrained	.029
236	ReAlnet03_ALL	.028
237	densenet-169	.028
238	ReAlnet06	.027
239	predictive_coding_pc	.026
240	ReAlnet09	.026
241	cvt_cvt-13-384-in1k_4_LucyV4	.026
242	convnext_large_in22k_supervised	.025
243	ReAlnet05_cornet	.025
244	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.025
245	ReAlnet08_cornet	.025
246	resnet18_imagenet21kP	.024
247	resnet50_vicreg_linhead	.024
248	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.024
249	ReAlnet07_cornet	.024
250	ReAlnet03_cornet	.023
251	yudixie_resnet50_random_0_240908	.023
252	BiT-S-R152x2	.023
253	nasnet_large	.022
254	ReAlnet04_cornet	.022
255	resnet50_imagenet_10_seed-0	.021
256	resnet50_simsiam_linhead	.021
257	ReAlnet06_cornet	.021
258	compact_vgg19_V4	.020
259	compact_cornets_IT	.020
260	ReAlnet01_cornet	.020
261	ReAlnet02_cornet	.018
262	compact_vgg19_IT	.018
263	briaai_rmbg_1_4	.016
264	dinov2_vitg14_reg_lc	.016
265	convnext_xxlarge_clip	.016
266	ReAlnet09_cornet	.016
267	dinov2_vitl14_reg_lc_featread	.015
268	dinov2_vitl14_reg_lc	.015
269	yudixie_resnet50_imagenet1kpret_0_240312	.014
270	resnet_50_v1_spiking_l3	.014
271	yudixie_resnet50_imagenet1kpret_0_240908	.014
272	resnet50_tutorial	.014
273	efficientnet-b7	.014
274	AdvProp_efficientnet-b6	.013
275	xception	.012
276	mobilenet_v2_1-4_224_pytorch	.011
277	convnext_large_clip_laion2b_finelayers	.011
278	efficientnet_b0_imagenet_full	.010
279	AdvProp_efficientnet-b8	.010
280	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.010
281	AdvProp_efficientnet-b4	.009
282	yudixie_wbh_object_class_scaling_0415_imagenet	.008
283	yudixie_resnet18_imagenet1kpret_0_240719	.008
284	vit_base_patch16_dinov3-lvd1689m	.006
285	mobilenet_v2_1_3_224	.005
286	SeLaVi-Kinetics400	.005
287	vonegrcnn_47e	.005
288	vonegrcnn_52e_full	.004
289	tv_efficientnet-b1	.004
290	efficientnet_b1_imagenet_full	.004
291	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.003
292	yudixie_resnet18_distance_reg_0_240719	.003
293	yudixie_resnet50_distance_reg_0_240908	.003
294	yudixie_resnet18_rotation_reg_0_240719	.003
295	yudixie_resnet50_distance_translation_rotation_0_240908	.003
296	yudixie_resnet18_distance_rotation_0_240719	.002
297	ViT_L_32_imagenet1k	.002
298	convnext_base_fb_in1k	.002
299	mobilenet_v2_1_0_192	.001
300	yudixie_resnet50_translation_rotation_0_240908	.001
301	yudixie_resnet50_distance_rotation_0_240908	.001
302	resnet50_imagenet_1_seed-0	.001
303	vgg_16	.001
304	AdvProp_efficientnet-b7	.000
305	yudixie_resnet18_translation_reg_0_240719	.000
306	mobilenet_v2_0_75_224	.000
307	resnet18_fair	.000
308	yudixie_resnet18_category_class_0_240719	.000
309	yudixie_resnet50_object_class_0_240908	.000
310	mobilenet_v2_0_5_224	.000
311	vgg_19	.000
312	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.001
313	yudixie_resnet18_object_class_0_240719	.001
314	yudixie_resnet50_category_class_0_240908	.001
315	yudixie_resnet50_translation_reg_0_240908	.001
316	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.002
317	yudixie_resnet18_distance_translation_rotation_0_240719	.002
318	yudixie_resnet18_translation_rotation_0_240719	.003
319	yudixie_resnet50_distance_translation_0_240908	.003
320	yudixie_resnet18_distance_translation_0_240719	.005
321	pnasnet_large_halfPrecision
322	ReAlnet01_cornet_fov16	1.0
323	ReAlnet01_cornet_fov12	1.0
324	compact_cornets_V4	1.0
325	compact_resnet50_robust_V4	1.0
326	mvit_v2_s
327	SeLaVi-Kinetics-Sound
328	resnet50_eMMCR_Vanilla
329	mvit_v1_b
330	fixres_resnext101_32x48d_wsl
331	mobilenet_v2_0_75_192
332	mobilenet_v2_0_5_192
333	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