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