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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("tong.Coggan2024_fMRI.V4-rdm")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	AlexNet_SIN	.332
2	AlexNet_SIN_fov12	.318
3	alexnet	.301
4	alexnet_ks_torevert	.300
5	convnext_xlarge:fb_in22k_ft_in1k	.277
6	alexnet_training_seed_01_fov16	.228
7	grcnn_109	.215
8	convnext_small_imagenet_1_seed-0	.215
9	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.206
10	alexnet_training_seed_01_fov4	.206
11	vit_large_patch14_clip_336:laion2b_ft_in1k	.199
12	vit_large_patch14_clip_224:openai_ft_in1k	.197
13	vit_large_patch14_clip_224:laion2b_ft_in1k	.171
14	deit_small_imagenet_10_seed-0	.171
15	yudixie_resnet18_random_0_240719	.169
16	efficientnet_b2_imagenet_full	.164
17	cvt_cvt-21-384-in1k_4_LucyV4	.161
18	alexnet_training_seed_01	.157
19	mobilenet_v2_0_5_224	.155
20	resnet-50-robust	.153
21	omnivore_swinS	.145
22	deit_small_imagenet_1_seed-0	.144
23	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.143
24	deit_small_imagenet_full_seed-0	.135
25	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.134
26	BiT-S-R50x1	.134
27	convnext_large:fb_in22k_ft_in1k	.132
28	convnext_small_imagenet_10_seed-0	.131
29	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.126
30	vit_base_patch16_clip_224:openai_ft_in1k	.126
31	alexnet_training_seed_09	.124
32	convnext_large_imagenet_full_seed-0	.123
33	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.120
34	resnet50-moclr8deg	.115
35	resnet50_primary_visual_cortex	.109
36	mobilenet_v2_1_0_160	.107
37	pnasnet_large	.106
38	AlexNet_SIN_fov16	.106
39	alexnet_training_seed_01_fov12	.105
40	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
41	yolos_tiny	.093
42	shufflenet_v2_x1_0	.090
43	compact_vgg19_V4	.090
44	resnet-152_v2_pytorch	.090
45	alexnet_training_seed_10	.090
46	alexnet_fov16	.089
47	alexnet_training_seed_07	.089
48	densenet-121	.087
49	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.084
50	vit_relpos_base_patch16_clsgap_224:sw_in1k	.081
51	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.081
52	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.080
53	ReAlnet01_cornet_fov12	.080
54	resnet_101_v2	.080
55	mobilenet_v2_1_0_224	.079
56	alexnet_training_seed_06	.079
57	resnext101_32x48d_wsl	.079
58	resnet50-VITO-8deg-cc	.075
59	resnet50-vitoimagevidnet8	.075
60	inception_v1	.075
61	cvt_cvt-21-224-in1k_4_LucyV4	.074
62	alexnet_training_seed_04	.071
63	ReAlnet08	.070
64	alexnet_training_seed_05	.069
65	deit_large_imagenet_full_seed-0	.069
66	ReAlnet07	.069
67	ReAlnet05	.068
68	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.067
69	ReAlnet06	.065
70	ReAlnet10	.065
71	ReAlnet01	.064
72	ViT_L_32_imagenet1k	.064
73	resnet50-vicregl0p9	.062
74	resnext101_32x32d_wsl	.062
75	resnet34_ecoset_full	.062
76	resnet_152_v1	.060
77	ReAlnet02	.060
78	resnet50-vicreg	.058
79	compact_vgg19_IT	.057
80	resnet_101_v1	.057
81	ReAlnet09	.056
82	convnext_tiny_imagenet_full_seed-0	.056
83	hmax	.053
84	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.053
85	ReAlnet03	.053
86	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.052
87	ReAlnet04	.050
88	efficientnet_b0_imagenet_full	.050
89	BiT-S-R101x1	.049
90	resnet_152_v2	.048
91	AlexNet_SIN_fov4	.047
92	grcnn	.047
93	effnetb1_272x240	.047
94	voneresnet-50	.046
95	alexnet_training_seed_08	.044
96	densenet-201	.044
97	resnet50-barlow	.043
98	AdvProp_efficientnet-b8	.042
99	resnet50_ewconplus_wzc	.041
100	custom_model_cv_18_dagger_408	.040
101	BiT-S-R152x4	.040
102	resnext101_32x8d_wsl	.040
103	inception_v4	.039
104	resnet50-SIN	.039
105	omnivore_swinB	.038
106	nasnet_mobile	.038
107	VOneCORnet-S	.037
108	mobilenet_v2_0_75_160	.036
109	resnet101_imagenet_full	.036
110	inception_v3	.035
111	resnet101_ecoset_full	.033
112	densenet-169	.033
113	AdvProp_efficientnet-b2	.031
114	AT_efficientnet-b2	.031
115	deit_small_imagenet_100_seed-0	.029
116	regnet_y_400mf	.029
117	resnet18_imagenet_full	.029
118	resnet50_robust_l2_eps1	.028
119	cv_18_dagger_408_pretrained	.028
120	focalnet_tiny_lrf_in1k	.028
121	resnet152_imagenet_full	.027
122	nasnet_large	.027
123	convnext_small_imagenet_full_seed-0	.026
124	convnext_base_imagenet_full_seed-0	.026
125	mobilenet_v2_1_4_224	.025
126	mobilenet_v2_1-4_224_pytorch	.025
127	alexnet_fov4	.024
128	resnet152_ecoset_full	.024
129	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.024
130	BiT-S-R50x3	.024
131	alexnet_fov12	.024
132	BiT-S-R101x3	.023
133	resnet18_imagenet21kP	.023
134	efficientnet-b7	.023
135	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.022
136	ReAlnet07_ALL	.022
137	ReAlnet02_ALL	.022
138	resnet50_imagenet_full	.022
139	convnext_base:clip_laiona_augreg_ft_in1k_384	.021
140	ReAlnet08_ALL	.021
141	imagenet_l2_3_0	.021
142	resnet18_ecoset_full	.020
143	ReAlnet03_ALL	.019
144	ReAlnet05_ALL	.019
145	ReAlnet10_ALL	.019
146	ReAlnet04_ALL	.019
147	ReAlnet09_ALL	.018
148	ReAlnet06_ALL	.018
149	resnet50_robust_l2_eps3	.018
150	ReAlnet10_cornet	.018
151	resnet50-vicregl0p75	.017
152	ReAlnet08_cornet	.017
153	ReAlnet01_ALL	.017
154	ReAlnet02_cornet	.016
155	resnet50_ecoset_full	.016
156	BiT-S-R152x2	.016
157	AdvProp_efficientnet-b6	.015
158	voneresnet-50-robust	.015
159	alexnet_training_seed_03	.015
160	cvt_cvt-13-224-in1k_4_LucyV4	.015
161	ReAlnet01_cornet	.015
162	ReAlnet07_cornet	.014
163	yudixie_resnet50_random_0_240908	.014
164	ReAlnet03_cornet	.014
165	ReAlnet05_cornet	.014
166	mobilenet_v2_1_3_224	.014
167	ReAlnet04_cornet	.013
168	Res2Net50_26w_4s	.013
169	vonegrcnn_47e	.012
170	alexnet_training_seed_02	.012
171	vonegrcnn_52e_full	.012
172	vonegrcnn_62e_nobn	.011
173	efficientnet_b0	.011
174	resnet34_imagenet_full	.011
175	cvt_cvt-13-384-in1k_4_LucyV4	.010
176	ReAlnet09_cornet	.010
177	ReAlnet06_cornet	.010
178	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.010
179	mobilenet_v2_1_0_192	.010
180	mobilenet_v2_1_0_128	.009
181	convnext_small_imagenet_100_seed-0	.009
182	yudixie_resnet18_distance_translation_0_240719	.009
183	resnet-18_test_m	.009
184	mobilenet_v2_0_5_192	.008
185	resnet_50_v1_spiking	.008
186	resnet50_tutorial	.008
187	yudixie_resnet50_imagenet1kpret_0_240908	.008
188	resnet_50_v1_spiking_l4	.008
189	resnet_50_v1_spiking_l4a	.008
190	resnet_50_v1_spiking_l3	.008
191	resnet_50_v1	.008
192	resnet50-sup	.008
193	yudixie_resnet50_imagenet1kpret_0_240312	.008
194	antialiased-rnext101_32x8d	.008
195	AdvProp_efficientnet-b4	.007
196	briaai_rmbg_1_4	.007
197	voneresnet-50-non_stochastic	.006
198	convnext_tiny_sup	.006
199	compact_resnet50_robust_IT	.005
200	resnet_50_v2	.005
201	resnet50-SIN_IN_IN	.005
202	resnet_SIN_IN_FT_IN	.005
203	deit_base_imagenet_full_seed-0	.005
204	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.005
205	ReAlnet01_cornet_fov4	.005
206	xception	.005
207	tv_efficientnet-b1	.004
208	yudixie_resnet18_imagenet1kpret_0_240719	.004
209	AdvProp_efficientnet-b7	.004
210	antialias-resnet152	.004
211	resnet50-SIN_IN	.004
212	yudixie_resnet18_translation_rotation_0_240719	.003
213	compact_resnet50_IT	.003
214	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.003
215	resnet50_imagenet_100_seed-0	.002
216	artResNet18_1	.002
217	antialiased-r50	.002
218	yudixie_resnet18_translation_reg_0_240719	.001
219	resnet50_imagenet_10_seed-0	.001
220	resnet50_imagenet_1_seed-0	.001
221	yudixie_resnet18_rotation_reg_0_240719	.000
222	convnext_femto_ols:d1_in1k	.000
223	blt_vs	.000
224	yudixie_resnet18_distance_rotation_0_240719	.000
225	yudixie_resnet18_distance_reg_0_240719	.000
226	efficientnet_b1_imagenet_full	.000
227	yudixie_resnet18_distance_translation_rotation_0_240719	.000
228	vgg_16	.000
229	mobilenet_v2_0_75_224	.001
230	convnext_tiny:in12k_ft_in1k	.002
231	yudixie_resnet50_rotation_reg_0_240908	.003
232	vgg_19	.003
233	yudixie_resnet50_object_class_0_240908	.003
234	yudixie_resnet50_translation_rotation_0_240908	.003
235	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.003
236	yudixie_resnet18_object_class_0_240719	.004
237	yudixie_resnet50_category_class_0_240908	.004
238	yudixie_resnet50_translation_reg_0_240908	.004
239	yudixie_resnet50_distance_translation_rotation_0_240908	.005
240	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.006
241	yudixie_resnet50_distance_translation_0_240908	.007
242	yudixie_resnet18_category_class_0_240719	.007
243	compact_cornets_IT	.007
244	yudixie_resnet50_distance_rotation_0_240908	.007
245	yudixie_resnet50_distance_reg_0_240908	.008
246	pnasnet_large_pytorch
247	mobilenet_v2_0_75_192
248	compact_resnet50_V4
249	SeLaVi-AVE
250	ReAlnet01_cornet_fov16	nan
251	r3d_18
252	resnext101_32x16d_wsl
253	fixres_resnext101_32x48d_wsl
254	compact_resnet50_robust_V4	nan
255	mc3_18
256	s3d
257	mvit_v1_b
258	resnet50_eMMCR_Vanilla
259	compact_cornets_V4	nan
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.V4

Metric: rdm