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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	alexnet_workflow_trigger	.300
6	convnext_xlarge:fb_in22k_ft_in1k	.277
7	vit_base_patch14_dinov2:lvd142m	.248
8	alexnet_training_seed_01_fov16	.228
9	grcnn_109	.215
10	convnext_small_imagenet_1_seed-0	.215
11	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.206
12	alexnet_training_seed_01_fov4	.206
13	vit_large_patch14_clip_336:laion2b_ft_in1k	.199
14	vit_large_patch14_clip_224:openai_ft_in1k	.197
15	vit_large_patch14_clip_224:laion2b_ft_in1k	.171
16	deit_small_imagenet_10_seed-0	.171
17	yudixie_resnet18_random_0_240719	.169
18	efficientnet_b2_imagenet_full	.164
19	cvt_cvt-21-384-in1k_4_LucyV4	.161
20	alexnet_training_seed_01	.157
21	mobilenet_v2_0_5_224	.155
22	resnet-50-robust	.153
23	omnivore_swinS	.145
24	deit_small_imagenet_1_seed-0	.144
25	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.143
26	deit_small_imagenet_full_seed-0	.135
27	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.134
28	BiT-S-R50x1	.134
29	convnext_large:fb_in22k_ft_in1k	.132
30	convnext_small_imagenet_10_seed-0	.131
31	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.126
32	vit_base_patch16_clip_224:openai_ft_in1k	.126
33	alexnet_training_seed_09	.124
34	convnext_large_imagenet_full_seed-0	.123
35	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.120
36	resnet50-moclr8deg	.115
37	resnet50_primary_visual_cortex	.109
38	mobilenet_v2_1_0_160	.107
39	pnasnet_large	.106
40	AlexNet_SIN_fov16	.106
41	alexnet_training_seed_01_fov12	.105
42	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
43	yolos_tiny	.093
44	shufflenet_v2_x1_0	.090
45	compact_vgg19_V4	.090
46	resnet-152_v2_pytorch	.090
47	alexnet_training_seed_10	.090
48	alexnet_fov16	.089
49	alexnet_training_seed_07	.089
50	densenet-121	.087
51	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.084
52	vit_relpos_base_patch16_clsgap_224:sw_in1k	.081
53	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.081
54	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.080
55	ReAlnet01_cornet_fov12	.080
56	resnet_101_v2	.080
57	mobilenet_v2_1_0_224	.079
58	alexnet_training_seed_06	.079
59	resnext101_32x48d_wsl	.079
60	resnet50-vitoimagevidnet8	.075
61	resnet50-VITO-8deg-cc	.075
62	inception_v1	.075
63	cvt_cvt-21-224-in1k_4_LucyV4	.074
64	alexnet_training_seed_04	.071
65	ReAlnet08	.070
66	alexnet_training_seed_05	.069
67	deit_large_imagenet_full_seed-0	.069
68	ReAlnet07	.069
69	ReAlnet05	.068
70	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.067
71	ReAlnet06	.065
72	ReAlnet10	.065
73	ReAlnet01	.064
74	ViT_L_32_imagenet1k	.064
75	resnet50-vicregl0p9	.062
76	resnext101_32x32d_wsl	.062
77	resnet34_ecoset_full	.062
78	resnet_152_v1	.060
79	ReAlnet02	.060
80	resnet50-vicreg	.058
81	compact_vgg19_IT	.057
82	resnet_101_v1	.057
83	ReAlnet09	.056
84	convnext_tiny_imagenet_full_seed-0	.056
85	hmax	.053
86	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.053
87	ReAlnet03	.053
88	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.052
89	ReAlnet04	.050
90	efficientnet_b0_imagenet_full	.050
91	BiT-S-R101x1	.049
92	resnet_152_v2	.048
93	AlexNet_SIN_fov4	.047
94	grcnn	.047
95	effnetb1_272x240	.047
96	voneresnet-50	.046
97	alexnet_training_seed_08	.044
98	densenet-201	.044
99	resnet50-barlow	.043
100	AdvProp_efficientnet-b8	.042
101	resnet50_ewconplus_wzc	.041
102	custom_model_cv_18_dagger_408	.040
103	BiT-S-R152x4	.040
104	resnext101_32x8d_wsl	.040
105	inception_v4	.039
106	resnet50-SIN	.039
107	omnivore_swinB	.038
108	nasnet_mobile	.038
109	VOneCORnet-S	.037
110	mobilenet_v2_0_75_160	.036
111	resnet101_imagenet_full	.036
112	inception_v3	.035
113	resnet101_ecoset_full	.033
114	densenet-169	.033
115	AT_efficientnet-b2	.031
116	AdvProp_efficientnet-b2	.031
117	deit_small_imagenet_100_seed-0	.029
118	regnet_y_400mf	.029
119	resnet18_imagenet_full	.029
120	resnet50_robust_l2_eps1	.028
121	cv_18_dagger_408_pretrained	.028
122	focalnet_tiny_lrf_in1k	.028
123	resnet152_imagenet_full	.027
124	nasnet_large	.027
125	convnext_small_imagenet_full_seed-0	.026
126	convnext_base_imagenet_full_seed-0	.026
127	mobilenet_v2_1_4_224	.025
128	mobilenet_v2_1-4_224_pytorch	.025
129	alexnet_fov4	.024
130	resnet152_ecoset_full	.024
131	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.024
132	BiT-S-R50x3	.024
133	alexnet_fov12	.024
134	BiT-S-R101x3	.023
135	resnet18_imagenet21kP	.023
136	efficientnet-b7	.023
137	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.022
138	ReAlnet07_ALL	.022
139	ReAlnet02_ALL	.022
140	resnet50_imagenet_full	.022
141	convnext_base:clip_laiona_augreg_ft_in1k_384	.021
142	ReAlnet08_ALL	.021
143	imagenet_l2_3_0	.021
144	resnet18_ecoset_full	.020
145	ReAlnet03_ALL	.019
146	ReAlnet05_ALL	.019
147	ReAlnet10_ALL	.019
148	ReAlnet04_ALL	.019
149	ReAlnet09_ALL	.018
150	ReAlnet06_ALL	.018
151	resnet50_robust_l2_eps3	.018
152	ReAlnet10_cornet	.018
153	resnet50-vicregl0p75	.017
154	ReAlnet08_cornet	.017
155	ReAlnet01_ALL	.017
156	ReAlnet02_cornet	.016
157	resnet50_ecoset_full	.016
158	BiT-S-R152x2	.016
159	AdvProp_efficientnet-b6	.015
160	voneresnet-50-robust	.015
161	alexnet_training_seed_03	.015
162	cvt_cvt-13-224-in1k_4_LucyV4	.015
163	ReAlnet01_cornet	.015
164	ReAlnet07_cornet	.014
165	yudixie_resnet50_random_0_240908	.014
166	ReAlnet03_cornet	.014
167	ReAlnet05_cornet	.014
168	mobilenet_v2_1_3_224	.014
169	ReAlnet04_cornet	.013
170	Res2Net50_26w_4s	.013
171	vonegrcnn_47e	.012
172	alexnet_training_seed_02	.012
173	vonegrcnn_52e_full	.012
174	vonegrcnn_62e_nobn	.011
175	efficientnet_b0	.011
176	resnet34_imagenet_full	.011
177	cvt_cvt-13-384-in1k_4_LucyV4	.010
178	ReAlnet09_cornet	.010
179	ReAlnet06_cornet	.010
180	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.010
181	mobilenet_v2_1_0_192	.010
182	mobilenet_v2_1_0_128	.009
183	convnext_small_imagenet_100_seed-0	.009
184	yudixie_resnet18_distance_translation_0_240719	.009
185	resnet-18_test_m	.009
186	mobilenet_v2_0_5_192	.008
187	yudixie_resnet50_imagenet1kpret_0_240312	.008
188	resnet_50_v1_spiking_l3	.008
189	resnet_50_v1_spiking_l4a	.008
190	resnet_50_v1_spiking_l4	.008
191	resnet_50_v1_spiking	.008
192	yudixie_resnet50_imagenet1kpret_0_240908	.008
193	resnet_50_v1	.008
194	resnet50-sup	.008
195	resnet50_tutorial	.008
196	antialiased-rnext101_32x8d	.008
197	AdvProp_efficientnet-b4	.007
198	briaai_rmbg_1_4	.007
199	voneresnet-50-non_stochastic	.006
200	convnext_tiny_sup	.006
201	compact_resnet50_robust_IT	.005
202	resnet_50_v2	.005
203	resnet50-SIN_IN_IN	.005
204	resnet_SIN_IN_FT_IN	.005
205	deit_base_imagenet_full_seed-0	.005
206	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.005
207	ReAlnet01_cornet_fov4	.005
208	xception	.005
209	tv_efficientnet-b1	.004
210	yudixie_resnet18_imagenet1kpret_0_240719	.004
211	AdvProp_efficientnet-b7	.004
212	antialias-resnet152	.004
213	resnet50-SIN_IN	.004
214	yudixie_resnet18_translation_rotation_0_240719	.003
215	compact_resnet50_IT	.003
216	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.003
217	resnet50_imagenet_100_seed-0	.002
218	artResNet18_1	.002
219	antialiased-r50	.002
220	yudixie_resnet18_translation_reg_0_240719	.001
221	resnet50_imagenet_10_seed-0	.001
222	resnet50_imagenet_1_seed-0	.001
223	yudixie_resnet18_rotation_reg_0_240719	.000
224	convnext_femto_ols:d1_in1k	.000
225	blt_vs	.000
226	yudixie_resnet18_distance_rotation_0_240719	.000
227	yudixie_resnet18_distance_reg_0_240719	.000
228	efficientnet_b1_imagenet_full	.000
229	yudixie_resnet18_distance_translation_rotation_0_240719	.000
230	vgg_16	.000
231	vit_base_patch16_dinov3:lvd1689m	.001
232	mobilenet_v2_0_75_224	.001
233	convnext_tiny:in12k_ft_in1k	.002
234	yudixie_resnet50_rotation_reg_0_240908	.003
235	vgg_19	.003
236	yudixie_resnet50_object_class_0_240908	.003
237	yudixie_resnet50_translation_rotation_0_240908	.003
238	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.003
239	yudixie_resnet18_object_class_0_240719	.004
240	yudixie_resnet50_category_class_0_240908	.004
241	yudixie_resnet50_translation_reg_0_240908	.004
242	yudixie_resnet50_distance_translation_rotation_0_240908	.005
243	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.006
244	yudixie_resnet50_distance_translation_0_240908	.007
245	yudixie_resnet18_category_class_0_240719	.007
246	compact_cornets_IT	.007
247	yudixie_resnet50_distance_rotation_0_240908	.007
248	yudixie_resnet50_distance_reg_0_240908	.008
249	vit_base_patch14_reg4_dinov2:lvd142m
250	ReAlnet01_cornet_fov16	nan
251	compact_cornets_V4	nan
252	compact_resnet50_robust_V4	nan
253	compact_resnet50_V4
254	mvit_v2_s
255	r2plus1d_18
256	SeLaVi-Kinetics-Sound
257	SeLaVi-VGG-Sound
258	SeLaVi-Kinetics400
259	resnet50_eMMCR_Vanilla
260	mvit_v1_b
261	s3d
262	mc3_18
263	fixres_resnext101_32x48d_wsl
264	resnext101_32x16d_wsl
265	r3d_18
266	SeLaVi-AVE
267	mobilenet_v2_0_75_192
268	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

0.33.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_fMRI.V4

Metric: rdm