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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	gabor_filter_entropy_4x4_v2	.927
2	gabor_filter_entropy_4x4_v2_forcedCosine	.883
3	gabor_filter_entropy_4x4	.857
4	mehrer2020_alexnet_training_seed_07	.477
5	mehrer2020_alexnet_training_seed_04	.406
6	mehrer2020_alexnet_training_seed_01	.380
7	mehrer2020_alexnet_training_seed_06	.375
8	mehrer2020_alexnet_training_seed_08	.374
9	AlexNet_SIN	.332
10	mehrer2020_alexnet_training_seed_09	.332
11	mehrer2020_alexnet_training_seed_02	.329
12	AlexNet_SIN_fov12	.318
13	mehrer2020_alexnet_training_seed_03	.311
14	alexnet	.301
15	alexnet_ks_torevert	.300
16	mehrer2020_alexnet_training_seed_05	.280
17	convnext_xlarge:fb_in22k_ft_in1k	.277
18	vit_base_patch14_dinov2-lvd142m	.248
19	alexnet_training_seed_01_fov16	.228
20	grcnn_109	.215
21	convnext_small_imagenet_1_seed-0	.215
22	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.206
23	alexnet_training_seed_01_fov4	.206
24	vit_large_patch14_clip_336:laion2b_ft_in1k	.199
25	mehrer2020_alexnet_training_seed_01_fov16	.199
26	vit_large_patch14_clip_224:openai_ft_in1k	.197
27	vit_large_patch14_clip_224:laion2b_ft_in1k	.171
28	deit_small_imagenet_10_seed-0	.171
29	yudixie_resnet18_random_0_240719	.169
30	efficientnet_b2_imagenet_full	.164
31	cvt_cvt-21-384-in1k_4_LucyV4	.161
32	alexnet_training_seed_01	.157
33	mobilenet_v2_0_5_224	.155
34	resnet-50-robust	.153
35	pr1_stl10_disentangled_alpha04	.148
36	omnivore_swinS	.145
37	deit_small_imagenet_1_seed-0	.144
38	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.143
39	deit_small_imagenet_full_seed-0	.135
40	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.134
41	BiT-S-R50x1	.134
42	convnext_large:fb_in22k_ft_in1k	.132
43	convnext_small_imagenet_10_seed-0	.131
44	mehrer2020_alexnet_training_seed_10	.129
45	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.126
46	vit_base_patch16_clip_224:openai_ft_in1k	.126
47	alexnet_training_seed_09	.124
48	convnext_large_imagenet_full_seed-0	.123
49	dinov2_vitg14_lc	.120
50	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.120
51	resnet50-moclr8deg	.115
52	resnet50_primary_visual_cortex	.109
53	mehrer2020_alexnet_training_seed_01_fov12	.107
54	mobilenet_v2_1_0_160	.107
55	pnasnet_large	.106
56	AlexNet_SIN_fov16	.106
57	vit_huge_clip336_laion	.106
58	alexnet_training_seed_01_fov12	.105
59	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
60	yolos_tiny	.093
61	shufflenet_v2_x1_0	.090
62	compact_vgg19_V4	.090
63	resnet-152_v2_pytorch	.090
64	alexnet_training_seed_10	.090
65	alexnet_fov16	.089
66	alexnet_training_seed_07	.089
67	densenet-121	.087
68	seresnext50_32x4d	.085
69	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.084
70	vit_relpos_base_patch16_clsgap_224:sw_in1k	.081
71	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.081
72	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.080
73	ReAlnet01_cornet_fov12	.080
74	resnet_101_v2	.080
75	mobilenet_v2_1_0_224	.079
76	alexnet_training_seed_06	.079
77	resnext101_32x48d_wsl	.079
78	resnet50-vitoimagevidnet8	.075
79	resnet50-VITO-8deg-cc	.075
80	inception_v1	.075
81	cvt_cvt-21-224-in1k_4_LucyV4	.074
82	alexnet_training_seed_04	.071
83	ReAlnet08	.070
84	alexnet_training_seed_05	.069
85	deit_large_imagenet_full_seed-0	.069
86	ReAlnet07	.069
87	ReAlnet05	.068
88	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.067
89	ReAlnet06	.065
90	ReAlnet10	.065
91	resnet50_st_wzc_2	.064
92	regnety_032	.064
93	ReAlnet01	.064
94	ViT_L_32_imagenet1k	.064
95	resnet50-vicregl0p9	.062
96	resnext101_32x32d_wsl	.062
97	resnet34_ecoset_full	.062
98	yudixie_wbh_object_class_scaling_0415_run_3	.061
99	resnet_152_v1	.060
100	ReAlnet02	.060
101	gabor_filter_mean_abs_4x4_v2	.058
102	resnet50-vicreg	.058
103	compact_vgg19_IT	.057
104	resnet_101_v1	.057
105	ReAlnet09	.056
106	vit_large_clip336_openai	.056
107	convnext_tiny_imagenet_full_seed-0	.056
108	resnext101_32x16d_wsl	.054
109	hmax	.053
110	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.053
111	ReAlnet03	.053
112	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.052
113	ReAlnet04	.050
114	efficientnet_b0_imagenet_full	.050
115	BiT-S-R101x1	.049
116	resnet_152_v2	.048
117	AlexNet_SIN_fov4	.047
118	grcnn	.047
119	effnetb1_272x240	.047
120	voneresnet-50	.046
121	alexnet_training_seed_08	.044
122	densenet-201	.044
123	resnet50-barlow	.043
124	mehrer2020_alexnet_training_seed_01_fov4	.043
125	resnet50_st_wzc_seed7_2_323	.043
126	AdvProp_efficientnet-b8	.042
127	resnet50_ewconplus_wzc	.041
128	custom_model_cv_18_dagger_408	.040
129	BiT-S-R152x4	.040
130	resnext101_32x8d_wsl	.040
131	inception_v4	.039
132	resnet50-SIN	.039
133	deepeisnn_ei_imagenet_resnet18	.039
134	dinov2_vitl14_lc_res336	.038
135	omnivore_swinB	.038
136	nasnet_mobile	.038
137	resnet50_st_wzc_seed3_2_323	.037
138	VOneCORnet-S	.037
139	mobilenet_v2_0_75_160	.036
140	resnet101_imagenet_full	.036
141	dinov2_vitl14_lc	.036
142	inception_v3	.035
143	resnet101_ecoset_full	.033
144	densenet-169	.033
145	predictive_coding_pc	.032
146	yudixie_wbh_object_class_scaling_0415_run_2	.031
147	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.031
148	deit3_base_patch16_224_fb_in22k_ft_in1k	.031
149	AT_efficientnet-b2	.031
150	AdvProp_efficientnet-b2	.031
151	deit_small_imagenet_100_seed-0	.029
152	regnet_y_400mf	.029
153	resnet18_imagenet_full	.029
154	resnet50_robust_l2_eps1	.028
155	cv_18_dagger_408_pretrained	.028
156	focalnet_tiny_lrf_in1k	.028
157	dinov2_vitl14_reg_lc_featread	.027
158	dinov2_vitl14_reg_lc	.027
159	resnet152_imagenet_full	.027
160	nasnet_large	.027
161	convnext_small_imagenet_full_seed-0	.026
162	convnext_base_imagenet_full_seed-0	.026
163	mobilenet_v2_1_4_224	.025
164	mobilenet_v2_1-4_224_pytorch	.025
165	eva02_large_in22k	.025
166	alexnet_fov4	.024
167	resnet152_ecoset_full	.024
168	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.024
169	BiT-S-R50x3	.024
170	alexnet_fov12	.024
171	BiT-S-R101x3	.023
172	resnet18_imagenet21kP	.023
173	dinov2_vitg14_reg_lc	.023
174	efficientnet-b7	.023
175	resnet50_ewconplus_wzc_seed2_2__323	.022
176	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.022
177	ReAlnet07_ALL	.022
178	ReAlnet02_ALL	.022
179	resnet50_imagenet_full	.022
180	convnext_base:clip_laiona_augreg_ft_in1k_384	.021
181	ReAlnet08_ALL	.021
182	imagenet_l2_3_0	.021
183	resnet18_ecoset_full	.020
184	ReAlnet03_ALL	.019
185	ReAlnet05_ALL	.019
186	ReAlnet10_ALL	.019
187	ReAlnet04_ALL	.019
188	convnext_large_in22k_supervised	.018
189	ReAlnet09_ALL	.018
190	ReAlnet06_ALL	.018
191	resnet50_robust_l2_eps3	.018
192	ReAlnet10_cornet	.018
193	resnet50-vicregl0p75	.017
194	ReAlnet08_cornet	.017
195	ReAlnet01_ALL	.017
196	deit3_base_patch16_224_fb_in1k	.016
197	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.016
198	ReAlnet02_cornet	.016
199	resnet50_ecoset_full	.016
200	BiT-S-R152x2	.016
201	AdvProp_efficientnet-b6	.015
202	voneresnet-50-robust	.015
203	alexnet_training_seed_03	.015
204	resnet50_ewconplus_wzc_seed5_2__323	.015
205	cvt_cvt-13-224-in1k_4_LucyV4	.015
206	ReAlnet01_cornet	.015
207	convnext_xxlarge_clip	.015
208	ReAlnet07_cornet	.014
209	yudixie_resnet50_random_0_240908	.014
210	yudixie_wbh_object_class_scaling_0415_run_1	.014
211	ReAlnet03_cornet	.014
212	ReAlnet05_cornet	.014
213	resnet50_st_wzc_seed6_2_323	.014
214	mobilenet_v2_1_3_224	.014
215	vit_base_patch14_reg4_dinov2-lvd142m	.013
216	ReAlnet04_cornet	.013
217	Res2Net50_26w_4s	.013
218	eicircuit_resnet18_bn_20260919	.012
219	vonegrcnn_47e	.012
220	alexnet_training_seed_02	.012
221	vonegrcnn_52e_full	.012
222	resnet50_ewconplus_wzc_seed6_2_323	.012
223	vonegrcnn_62e_nobn	.011
224	efficientnet_b0	.011
225	resnet34_imagenet_full	.011
226	cvt_cvt-13-384-in1k_4_LucyV4	.010
227	ReAlnet09_cornet	.010
228	resnet50_hvs_wzc	.010
229	ReAlnet06_cornet	.010
230	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.010
231	mobilenet_v2_1_0_192	.010
232	deepeisnn_ei_cifar10_vgg19	.010
233	mobilenet_v2_1_0_128	.009
234	convnext_small_imagenet_100_seed-0	.009
235	yudixie_resnet18_distance_translation_0_240719	.009
236	resnet-18_test_m	.009
237	mobilenet_v2_0_5_192	.008
238	yudixie_wbh_object_class_scaling_0415_run_0	.008
239	yudixie_resnet50_imagenet1kpret_0_240312	.008
240	resnet_50_v1_spiking_l3	.008
241	resnet_50_v1_spiking_l4a	.008
242	resnet_50_v1_spiking_l4	.008
243	resnet_50_v1_spiking	.008
244	yudixie_resnet50_imagenet1kpret_0_240908	.008
245	resnet_50_v1	.008
246	resnet50-sup	.008
247	resnet50_tutorial	.008
248	convnext_large_clip_laion2b_finelayers	.008
249	antialiased-rnext101_32x8d	.008
250	AdvProp_efficientnet-b4	.007
251	briaai_rmbg_1_4	.007
252	voneresnet-50-non_stochastic	.006
253	convnext_tiny_sup	.006
254	compact_resnet50_robust_IT	.005
255	resnet_50_v2	.005
256	resnet50-SIN_IN_IN	.005
257	resnet_SIN_IN_FT_IN	.005
258	deit_base_imagenet_full_seed-0	.005
259	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.005
260	ReAlnet01_cornet_fov4	.005
261	xception	.005
262	tv_efficientnet-b1	.004
263	yudixie_wbh_object_class_scaling_0415_imagenet	.004
264	yudixie_resnet18_imagenet1kpret_0_240719	.004
265	AdvProp_efficientnet-b7	.004
266	antialias-resnet152	.004
267	resnet50-SIN_IN	.004
268	yudixie_resnet18_translation_rotation_0_240719	.003
269	compact_resnet50_IT	.003
270	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.003
271	convnext_base_fb_in1k_gram_aligned_dinov3	.002
272	convnext_base_fb_in1k	.002
273	deepeisnn_ei_cifar10_resnet18	.002
274	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.002
275	convnext_base_fb_in22k_ft_in1k	.002
276	resnet50_imagenet_100_seed-0	.002
277	artResNet18_1	.002
278	antialiased-r50	.002
279	yudixie_resnet18_translation_reg_0_240719	.001
280	resnet50_imagenet_10_seed-0	.001
281	resnet50_imagenet_1_seed-0	.001
282	yudixie_resnet18_rotation_reg_0_240719	.000
283	convnext_femto_ols:d1_in1k	.000
284	blt_vs	.000
285	yudixie_resnet18_distance_rotation_0_240719	.000
286	yudixie_resnet18_distance_reg_0_240719	.000
287	efficientnet_b1_imagenet_full	.000
288	yudixie_resnet18_distance_translation_rotation_0_240719	.000
289	vgg_16	.000
290	vit_base_patch16_dinov3-lvd1689m	.001
291	mobilenet_v2_0_75_224	.001
292	convnext_tiny:in12k_ft_in1k	.002
293	yudixie_resnet50_rotation_reg_0_240908	.003
294	vgg_19	.003
295	yudixie_resnet50_object_class_0_240908	.003
296	yudixie_resnet50_translation_rotation_0_240908	.003
297	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.003
298	resnet18_fair	.003
299	yudixie_resnet18_object_class_0_240719	.004
300	yudixie_resnet50_category_class_0_240908	.004
301	yudixie_resnet50_translation_reg_0_240908	.004
302	yudixie_resnet50_distance_translation_rotation_0_240908	.005
303	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.006
304	yudixie_resnet50_distance_translation_0_240908	.007
305	yudixie_resnet18_category_class_0_240719	.007
306	compact_cornets_IT	.007
307	yudixie_resnet50_distance_rotation_0_240908	.007
308	yudixie_resnet50_distance_reg_0_240908	.008
309	pnasnet_large_halfPrecision
310	ReAlnet01_cornet_fov16	1.0
311	compact_cornets_V4	1.0
312	compact_resnet50_robust_V4	1.0
313	compact_resnet50_V4
314	mvit_v2_s
315	r2plus1d_18
316	SeLaVi-Kinetics-Sound
317	SeLaVi-VGG-Sound
318	SeLaVi-Kinetics400
319	resnet50_eMMCR_Vanilla
320	mvit_v1_b
321	s3d
322	mc3_18
323	fixres_resnext101_32x48d_wsl
324	r3d_18
325	SeLaVi-AVE
326	mobilenet_v2_0_75_192
327	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