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