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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024eighth-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet_50_v1_spiking_l4	1.0
2	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
3	compact_resnet50_robust_IT	1.0
4	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
5	resnet50_st_wzc_seed5_2_323	1.0
6	compact_vgg19_V4	1.0
7	densenet-121	1.0
8	yudixie_wbh_object_class_scaling_0415_run_3	1.0
9	alexnet_training_seed_05	.974
10	resnext101_32x32d_wsl	.974
11	yudixie_resnet50_translation_reg_0_240908	.974
12	compact_cornets_V4	.974
13	convnext_large:fb_in22k_ft_in1k	.951
14	mobilenet_v2_0_75_224	.882
15	vit_base_patch16_clip_224:openai_ft_in1k	.882
16	alexnet_training_seed_01	.882
17	yudixie_resnet18_category_class_0_240719	.882
18	omnivore_swinS	.882
19	alexnet_training_seed_01_fov16	.882
20	AdvProp_efficientnet-b4	.882
21	resnet_SIN_IN_FT_IN	.882
22	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.861
23	resnext101_32x8d_wsl	.799
24	vit_base_patch14_dinov2-lvd142m	.799
25	resnet50_ewconplus_wzc_seed2_2__323	.799
26	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.780
27	vit_base_patch14_reg4_dinov2-lvd142m	.780
28	mobilenet_v2_1_0_192	.723
29	cv_18_dagger_408_pretrained	.723
30	cvt_cvt-13-224-in1k_4_LucyV4	.723
31	deit_small_imagenet_10_seed-0	.723
32	convnext_xlarge:fb_in22k_ft_in1k	.706
33	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.655
34	mobilenet_v2_1_0_160	.655
35	focalnet_tiny_lrf_in1k	.655
36	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.655
37	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.655
38	BiT-S-R152x2	.655
39	cvt_cvt-21-224-in1k_4_LucyV4	.593
40	resnet152_ecoset_full	.593
41	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.579
42	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.537
43	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.537
44	ReAlnet05_ALL	.537
45	omnivore_swinB	.524
46	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.486
47	resnet_50_v1_spiking	.486
48	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.486
49	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.486
50	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.486
51	effnetb1_272x240	.486
52	yudixie_resnet18_distance_translation_rotation_0_240719	.486
53	nasnet_large	.486
54	cvt_cvt-21-384-in1k_4_LucyV4	.475
55	custom_model_cv_18_dagger_408	.440
56	compact_resnet50_V4	.440
57	compact_resnet50_IT	.440
58	compact_resnet50_robust_V4	.440
59	compact_cornets_IT	.440
60	resnet50_st_wzc_seed3_2_323	.440
61	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.399
62	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.399
63	convnext_small_imagenet_1_seed-0	.399
64	yudixie_resnet18_imagenet1kpret_0_240719	.399
65	AlexNet_SIN_fov4	.399
66	ReAlnet03_ALL	.399
67	alexnet_training_seed_01_fov12	.399
68	densenet-169	.399
69	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.399
70	vit_large_patch14_clip_224:laion2b_ft_in1k	.361
71	vit_large_patch14_clip_224:openai_ft_in1k	.361
72	yudixie_resnet50_distance_reg_0_240908	.361
73	AdvProp_efficientnet-b6	.361
74	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.361
75	resnext101_32x48d_wsl	.361
76	resnet18_ecoset_full	.361
77	AdvProp_efficientnet-b2	.361
78	BiT-S-R50x3	.361
79	AT_efficientnet-b2	.361
80	resnet50_st_wzc_seed7_2_323	.361
81	deepeisnn_ei_cifar10_vgg19	.361
82	resnet50_st_wzc_2	.327
83	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.327
84	deit_small_imagenet_full_seed-0	.327
85	convnext_small_imagenet_10_seed-0	.327
86	deit_large_imagenet_full_seed-0	.327
87	resnet-18_test_m	.327
88	yudixie_resnet18_translation_reg_0_240719	.327
89	deit3_base_patch16_224_fb_in1k	.327
90	yudixie_wbh_object_class_scaling_0415_imagenet	.327
91	resnet50_ewconplus_wzc	.296
92	resnet34_ecoset_full	.296
93	convnext_large_imagenet_full_seed-0	.296
94	yudixie_resnet50_distance_rotation_0_240908	.296
95	efficientnet-b7	.296
96	convnext_base:clip_laiona_augreg_ft_in1k_384	.296
97	deepeisnn_ei_imagenet_resnet18	.296
98	alexnet_fov12	.268
99	vit_base_patch16_dinov3-lvd1689m	.268
100	deit_small_imagenet_1_seed-0	.268
101	mobilenet_v2_1_3_224	.268
102	resnet50-vicregl0p75	.268
103	resnet34_imagenet_full	.243
104	AlexNet_SIN	.243
105	convnext_tiny_sup	.243
106	BiT-S-R152x4	.243
107	resnet50-vicreg	.220
108	resnet_101_v2	.220
109	vonegrcnn_52e_full	.220
110	BiT-S-R101x1	.220
111	mobilenet_v2_0_5_224	.199
112	pnasnet_large_halfPrecision	.199
113	cvt_cvt-13-384-in1k_4_LucyV4	.199
114	Res2Net50_26w_4s	.199
115	mobilenet_v2_1_0_224	.199
116	ReAlnet04_ALL	.199
117	ReAlnet06_ALL	.199
118	BiT-S-R50x1	.199
119	ReAlnet10_ALL	.180
120	resnet-152_v2_pytorch	.180
121	convnext_base_imagenet_full_seed-0	.180
122	mobilenet_v2_0_75_192	.180
123	resnet50-SIN_IN_IN	.180
124	resnet50_primary_visual_cortex	.180
125	resnet50_ewconplus_wzc_seed6_2_323	.180
126	yudixie_resnet18_distance_translation_0_240719	.163
127	ReAlnet01_cornet_fov12	.163
128	AlexNet_SIN_fov12	.163
129	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.163
130	ReAlnet08_ALL	.163
131	resnet50_imagenet_full	.148
132	deit_base_imagenet_full_seed-0	.148
133	pnasnet_large_pytorch	.148
134	efficientnet_b2_imagenet_full	.148
135	pnasnet_large	.148
136	resnet_50_v1_spiking_l3	.148
137	ReAlnet01_ALL	.148
138	resnet50-moclr8deg	.148
139	BiT-S-R101x3	.148
140	resnet50_ewconplus_wzc_2_323	.148
141	resnet50_st_wzc_seed4_2_323	.148
142	yudixie_wbh_object_class_scaling_0415_run_0	.148
143	densenet-201	.134
144	alexnet_fov16	.134
145	efficientnet_b1_imagenet_full	.134
146	resnet50-SIN	.134
147	ReAlnet02_ALL	.134
148	grcnn	.134
149	voneresnet-50	.134
150	grcnn_109	.134
151	resnet_50_v2	.134
152	resnet50_st_wzc_seed6_2_323	.134
153	resnet50_ewconplus_wzc_seed5_2__323	.134
154	convnext_base_fb_in1k_gram_aligned_dinov3	.134
155	yudixie_resnet50_imagenet1kpret_0_240908	.121
156	convnext_small_imagenet_full_seed-0	.121
157	ViT_L_32_imagenet1k	.121
158	resnet152_imagenet_full	.121
159	yudixie_resnet18_translation_rotation_0_240719	.121
160	yudixie_resnet50_rotation_reg_0_240908	.121
161	yudixie_resnet18_object_class_0_240719	.121
162	compact_vgg19_IT	.121
163	artResNet18_1	.121
164	resnet50_ewconplus_wzc_seed4_2_323	.121
165	inception_v3	.110
166	convnext_tiny_imagenet_full_seed-0	.110
167	alexnet	.110
168	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.110
169	VOneCORnet-S	.110
170	resnet50_imagenet_10_seed-0	.110
171	xception	.110
172	AlexNet_SIN_fov16	.110
173	antialiased-r50	.110
174	AdvProp_efficientnet-b8	.110
175	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.110
176	convnext_tiny:in12k_ft_in1k	.099
177	alexnet_training_seed_08	.099
178	deit_small_imagenet_100_seed-0	.099
179	yolos_tiny	.099
180	convnext_small_imagenet_100_seed-0	.099
181	yudixie_resnet18_distance_rotation_0_240719	.099
182	nasnet_mobile	.099
183	vgg_19	.099
184	yudixie_resnet50_distance_translation_rotation_0_240908	.099
185	alexnet_training_seed_09	.099
186	deit3_base_patch16_224_fb_in22k_ft_in1k	.099
187	vgg_16	.090
188	alexnet_training_seed_02	.081
189	ReAlnet09	.081
190	mobilenet_v2_0_75_160	.081
191	mobilenet_v2_1-4_224_pytorch	.081
192	aughost_fair_resnet18	.081
193	shufflenet_v2_x1_0	.081
194	ReAlnet09_cornet	.081
195	efficientnet_b0	.081
196	mobilenet_v2_1_4_224	.081
197	yudixie_resnet50_object_class_0_240908	.081
198	resnet18_fair	.081
199	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.081
200	resnet50_st_wzc_noseed_2_323	.074
201	yudixie_resnet18_distance_reg_0_240719	.074
202	ReAlnet08	.067
203	alexnet_fov4	.067
204	inception_v4	.067
205	ReAlnet04_cornet	.067
206	ReAlnet08_cornet	.067
207	resnet_152_v2	.067
208	ReAlnet04	.067
209	resnet50_ewconplus_noseed_2_323	.067
210	resnet50_tutorial	.060
211	resnet18_imagenet_full	.060
212	resnet101_ecoset_full	.060
213	ReAlnet01_cornet_fov16	.060
214	resnet_152_v1	.060
215	resnet101_imagenet_full	.055
216	resnet50-barlow	.055
217	alexnet_training_seed_03	.055
218	yudixie_wbh_object_class_scaling_0415_run_2	.055
219	deepeisnn_ei_cifar10_resnet18	.055
220	yudixie_resnet50_category_class_0_240908	.050
221	yudixie_resnet18_random_0_240719	.050
222	vonegrcnn_62e_nobn	.050
223	ReAlnet09_ALL	.050
224	yudixie_resnet18_rotation_reg_0_240719	.045
225	alexnet_training_seed_01_fov4	.045
226	ReAlnet06	.041
227	briaai_rmbg_1_4	.041
228	mobilenet_v2_0_5_192	.041
229	ReAlnet06_cornet	.041
230	vonegrcnn_47e	.041
231	ReAlnet07_ALL	.041
232	ReAlnet10	.037
233	resnet_50_v1_spiking_l4a	.037
234	resnet50_imagenet_100_seed-0	.037
235	yudixie_resnet50_distance_translation_0_240908	.037
236	ReAlnet10_cornet	.037
237	AdvProp_efficientnet-b7	.037
238	convnext_femto_ols:d1_in1k	.037
239	alexnet_training_seed_06	.033
240	mobilenet_v2_1_0_128	.033
241	alexnet_training_seed_07	.033
242	predictive_coding_pc	.033
243	inception_v1	.030
244	ReAlnet03	.027
245	resnet50_ecoset_full	.027
246	ReAlnet03_cornet	.027
247	resnet_101_v1	.027
248	resnet50-vicregl0p9	.027
249	yudixie_wbh_object_class_scaling_0415_run_1	.027
250	resnet-50-robust	.025
251	resnet50-VITO-8deg-cc	.025
252	resnet_50_v1	.025
253	resnet50-vitoimagevidnet8	.025
254	resnet50-sup	.025
255	ReAlnet05	.022
256	ReAlnet01_cornet_fov4	.022
257	ReAlnet05_cornet	.022
258	voneresnet-50-robust	.022
259	blt_vs	.020
260	ReAlnet02_cornet	.020
261	ReAlnet02	.020
262	efficientnet_b0_imagenet_full	.018
263	pr1_stl10_disentangled_alpha04	.018
264	ReAlnet07	.017
265	resnet50-SIN_IN	.017
266	ReAlnet07_cornet	.017
267	yudixie_resnet50_translation_rotation_0_240908	.017
268	yudixie_resnet50_random_0_240908	.015
269	resnet50_robust_l2_eps1	.014
270	alexnet_training_seed_04	.011
271	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.011
272	alexnet_training_seed_10	.011
273	ReAlnet01_cornet	.010
274	voneresnet-50-non_stochastic	.010
275	ReAlnet01	.010
276	resnet50_robust_l2_eps3	.008
277	imagenet_l2_3_0	.008
278	resnet50_imagenet_1_seed-0	.006
279	hmax
280	convnext_base_fb_in1k
281	convnext_base_fb_in22k_ft_in1k

Benchmark bibtex

        @misc{ferguson_ngo_lee_dicarlo_schrimpf_2024,
         title={How Well is Visual Search Asymmetry predicted by a Binary-Choice, Rapid, Accuracy-based Visual-search, Oddball-detection (BRAVO) task?},
         url={osf.io/5ba3n},
         DOI={10.17605/OSF.IO/5BA3N},
         publisher={OSF},
         author={Ferguson, Michael E, Jr and Ngo, Jerry and Lee, Michael and DiCarlo, James and Schrimpf, Martin},
         year={2024},
         month={Jun}
}

Ceiling

0.85.

Note that scores are relative to this ceiling.

Data: Ferguson2024eighth

Metric: value_delta