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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	resnet50_ewconplus_wzc	.956
3	alexnet_training_seed_08	.932
4	convnext_small_imagenet_10_seed-0	.927
5	alexnet_training_seed_10	.885
6	convnext_tiny_imagenet_full_seed-0	.874
7	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.871
8	deit_small_imagenet_full_seed-0	.851
9	alexnet_training_seed_06	.834
10	vit_relpos_base_patch16_clsgap_224:sw_in1k	.833
11	alexnet_training_seed_09	.827
12	resnet50_imagenet_100_seed-0	.778
13	resnet50-SIN	.765
14	AlexNet_SIN	.759
15	convnext_small_imagenet_full_seed-0	.744
16	alexnet_training_seed_05	.733
17	BiT-S-R101x1	.705
18	mobilenet_v2_0_5_192	.700
19	vit_large_patch14_clip_224:openai_ft_in1k	.697
20	alexnet_training_seed_02	.689
21	VOneCORnet-S	.677
22	convnext_femto_ols:d1_in1k	.674
23	deit_large_imagenet_full_seed-0	.668
24	alexnet_training_seed_01_fov12	.660
25	voneresnet-50-robust	.656
26	grcnn	.655
27	alexnet_training_seed_03	.651
28	alexnet_training_seed_07	.642
29	antialiased-r50	.640
30	alexnet_training_seed_04	.639
31	convnext_base_imagenet_full_seed-0	.632
32	resnet50_robust_l2_eps1	.632
33	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.630
34	focalnet_tiny_lrf_in1k	.620
35	ReAlnet01_cornet	.614
36	BiT-S-R50x1	.613
37	deit_base_imagenet_full_seed-0	.612
38	omnivore_swinS	.607
39	antialiased-rnext101_32x8d	.587
40	ReAlnet03_cornet	.586
41	resnet101_ecoset_full	.577
42	alexnet_training_seed_01_fov16	.575
43	mobilenet_v2_0_75_160	.568
44	ReAlnet10_cornet	.567
45	AlexNet_SIN_fov4	.565
46	ReAlnet07_cornet	.565
47	ReAlnet09_cornet	.559
48	ReAlnet02_cornet	.557
49	convnext_base:clip_laiona_augreg_ft_in1k_384	.554
50	ReAlnet06_cornet	.540
51	alexnet_training_seed_01	.538
52	mobilenet_v2_0_75_224	.533
53	deit_small_imagenet_10_seed-0	.529
54	convnext_small_imagenet_1_seed-0	.527
55	voneresnet-50	.527
56	ReAlnet04_ALL	.524
57	resnet50_ecoset_full	.521
58	ReAlnet08_cornet	.513
59	resnext101_32x32d_wsl	.511
60	resnet50_robust_l2_eps3	.509
61	resnext101_32x8d_wsl	.506
62	yudixie_resnet18_random_0_240719	.505
63	resnet101_imagenet_full	.504
64	ReAlnet06_ALL	.502
65	ReAlnet08_ALL	.499
66	ReAlnet05_ALL	.499
67	ReAlnet03_ALL	.491
68	ReAlnet07_ALL	.491
69	resnet_152_v1	.483
70	resnext101_32x48d_wsl	.483
71	ReAlnet04_cornet	.481
72	nasnet_large	.481
73	ReAlnet09_ALL	.473
74	ReAlnet05_cornet	.464
75	resnet_101_v1	.463
76	BiT-S-R50x3	.462
77	grcnn_109	.462
78	efficientnet_b2_imagenet_full	.461
79	voneresnet-50-non_stochastic	.459
80	resnet50-vitoimagevidnet8	.456
81	resnet50-VITO-8deg-cc	.456
82	shufflenet_v2_x1_0	.455
83	resnet50-SIN_IN_IN	.454
84	ReAlnet02_ALL	.454
85	ReAlnet01_ALL	.452
86	alexnet	.449
87	alexnet_ks_torevert	.449
88	ReAlnet10_ALL	.438
89	resnet18_ecoset_full	.437
90	resnet50-SIN_IN	.431
91	resnet152_ecoset_full	.429
92	resnet_SIN_IN_FT_IN	.428
93	AlexNet_SIN_fov12	.424
94	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.424
95	artResNet18_1	.413
96	mobilenet_v2_0_75_192	.410
97	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.409
98	vit_large_patch14_clip_224:laion2b_ft_in1k	.399
99	inception_v1	.393
100	pnasnet_large	.392
101	alexnet_training_seed_01_fov4	.385
102	deit_small_imagenet_1_seed-0	.384
103	resnet50_imagenet_full	.380
104	cvt_cvt-21-224-in1k_4_LucyV4	.380
105	AlexNet_SIN_fov16	.377
106	ReAlnet03	.375
107	ReAlnet01	.369
108	resnet_50_v1_spiking	.366
109	resnet_50_v1	.366
110	resnet50-sup	.366
111	ReAlnet01_cornet_fov12	.366
112	blt_vs	.365
113	resnet50_primary_visual_cortex	.365
114	resnet34_imagenet_full	.359
115	mobilenet_v2_0_5_224	.358
116	resnet50-vicregl0p9	.355
117	convnext_large_imagenet_full_seed-0	.354
118	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.349
119	ReAlnet09	.345
120	ReAlnet10	.336
121	ReAlnet06	.331
122	imagenet_l2_3_0	.330
123	ReAlnet02	.329
124	effnetb1_272x240	.328
125	mobilenet_v2_1_0_160	.327
126	alexnet_fov16	.326
127	xception	.324
128	ReAlnet05	.323
129	resnet-18_test_m	.322
130	ReAlnet07	.318
131	nasnet_mobile	.310
132	ReAlnet08	.309
133	ReAlnet04	.308
134	BiT-S-R101x3	.300
135	ReAlnet01_cornet_fov16	.288
136	resnet50-moclr8deg	.285
137	alexnet_fov4	.282
138	resnet18_imagenet_full	.271
139	resnet18_imagenet21kP	.261
140	yudixie_resnet18_imagenet1kpret_0_240719	.256
141	hmax	.254
142	resnet50-vicregl0p75	.252
143	resnet50-barlow	.245
144	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.245
145	resnet50-vicreg	.244
146	convnext_xlarge:fb_in22k_ft_in1k	.243
147	efficientnet_b0	.242
148	vonegrcnn_52e_full	.241
149	omnivore_swinB	.240
150	resnet50_imagenet_10_seed-0	.233
151	resnet_101_v2	.230
152	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.230
153	vit_base_patch16_clip_224:openai_ft_in1k	.229
154	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.228
155	regnet_y_400mf	.218
156	resnet152_imagenet_full	.215
157	resnet_50_v1_spiking_l4	.213
158	yudixie_resnet50_imagenet1kpret_0_240908	.213
159	resnet50_tutorial	.213
160	resnet_50_v1_spiking_l4a	.213
161	yudixie_resnet50_imagenet1kpret_0_240312	.213
162	Res2Net50_26w_4s	.211
163	alexnet_fov12	.210
164	vonegrcnn_47e	.207
165	resnet34_ecoset_full	.203
166	inception_v3	.201
167	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.188
168	tv_efficientnet-b1	.186
169	cvt_cvt-21-384-in1k_4_LucyV4	.184
170	resnet-152_v2_pytorch	.180
171	vonegrcnn_62e_nobn	.177
172	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.173
173	convnext_tiny_sup	.173
174	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.166
175	resnet_152_v2	.164
176	compact_vgg19_IT	.160
177	yolos_tiny	.159
178	convnext_large:fb_in22k_ft_in1k	.158
179	deit_small_imagenet_100_seed-0	.158
180	resnet_50_v2	.158
181	antialias-resnet152	.149
182	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.149
183	AdvProp_efficientnet-b4	.144
184	briaai_rmbg_1_4	.142
185	custom_model_cv_18_dagger_408	.139
186	compact_vgg19_V4	.136
187	efficientnet-b7	.131
188	convnext_small_imagenet_100_seed-0	.120
189	vit_large_patch14_clip_336:laion2b_ft_in1k	.119
190	BiT-S-R152x4	.115
191	mobilenet_v2_1_0_224	.114
192	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.107
193	densenet-201	.104
194	mobilenet_v2_1-4_224_pytorch	.103
195	mobilenet_v2_1_4_224	.103
196	inception_v4	.102
197	AdvProp_efficientnet-b6	.101
198	cv_18_dagger_408_pretrained	.099
199	efficientnet_b0_imagenet_full	.099
200	convnext_tiny:in12k_ft_in1k	.097
201	AdvProp_efficientnet-b8	.093
202	mobilenet_v2_1_0_128	.092
203	resnet-50-robust	.084
204	AdvProp_efficientnet-b2	.082
205	AT_efficientnet-b2	.082
206	mobilenet_v2_1_0_192	.078
207	AdvProp_efficientnet-b7	.075
208	ReAlnet01_cornet_fov4	.074
209	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.066
210	mobilenet_v2_1_3_224	.063
211	yudixie_resnet18_distance_reg_0_240719	.060
212	densenet-169	.057
213	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.057
214	efficientnet_b1_imagenet_full	.052
215	BiT-S-R152x2	.048
216	yudixie_resnet50_random_0_240908	.035
217	densenet-121	.035
218	yudixie_resnet18_distance_rotation_0_240719	.033
219	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.030
220	resnet_50_v1_spiking_l3	.025
221	yudixie_resnet18_translation_reg_0_240719	.023
222	vgg_16	.022
223	yudixie_resnet18_distance_translation_rotation_0_240719	.019
224	ViT_L_32_imagenet1k	.015
225	cvt_cvt-13-384-in1k_4_LucyV4	.011
226	yudixie_resnet18_translation_rotation_0_240719	.009
227	vgg_19	.008
228	compact_cornets_IT	.002
229	yudixie_resnet50_distance_rotation_0_240908	.002
230	yudixie_resnet18_distance_translation_0_240719	.001
231	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.000
232	yudixie_resnet18_rotation_reg_0_240719	.000
233	yudixie_resnet50_distance_translation_rotation_0_240908	.000
234	resnet50_imagenet_1_seed-0	.000
235	cvt_cvt-13-224-in1k_4_LucyV4	.000
236	yudixie_resnet50_translation_rotation_0_240908	.000
237	yudixie_resnet50_object_class_0_240908	.000
238	compact_resnet50_robust_IT	.000
239	yudixie_resnet18_object_class_0_240719	.001
240	yudixie_resnet50_distance_translation_0_240908	.001
241	yudixie_resnet50_rotation_reg_0_240908	.001
242	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.001
243	yudixie_resnet50_category_class_0_240908	.002
244	yudixie_resnet50_translation_reg_0_240908	.002
245	compact_resnet50_IT	.003
246	yudixie_resnet18_category_class_0_240719	.005
247	yudixie_resnet50_distance_reg_0_240908	.016
248	s3d
249	pnasnet_large_pytorch
250	compact_resnet50_V4
251	SeLaVi-AVE
252	r3d_18
253	fixres_resnext101_32x48d_wsl
254	resnext101_32x16d_wsl
255	compact_resnet50_robust_V4	nan
256	mc3_18
257	compact_cornets_V4	nan
258	mvit_v1_b
259	resnet50_eMMCR_Vanilla
260	SeLaVi-Kinetics400
261	SeLaVi-VGG-Sound
262	SeLaVi-Kinetics-Sound
263	r2plus1d_18
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.IT

Metric: rdm