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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	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
4	densenet-121	1.0
5	alexnet_training_seed_05	.974
6	resnext101_32x32d_wsl	.974
7	yudixie_resnet50_translation_reg_0_240908	.974
8	convnext_large:fb_in22k_ft_in1k	.951
9	mobilenet_v2_0_75_224	.882
10	vit_base_patch16_clip_224:openai_ft_in1k	.882
11	alexnet_training_seed_01	.882
12	yudixie_resnet18_category_class_0_240719	.882
13	omnivore_swinS	.882
14	AdvProp_efficientnet-b4	.882
15	resnet_SIN_IN_FT_IN	.882
16	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.861
17	resnext101_32x8d_wsl	.799
18	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.780
19	mobilenet_v2_1_0_192	.723
20	cvt_cvt-13-224-in1k_4_LucyV4	.723
21	deit_small_imagenet_10_seed-0	.723
22	convnext_xlarge:fb_in22k_ft_in1k	.706
23	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.655
24	mobilenet_v2_1_0_160	.655
25	focalnet_tiny_lrf_in1k	.655
26	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.655
27	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.655
28	BiT-S-R152x2	.655
29	cvt_cvt-21-224-in1k_4_LucyV4	.593
30	resnet152_ecoset_full	.593
31	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.579
32	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.537
33	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.537
34	ReAlnet05_ALL	.537
35	omnivore_swinB	.524
36	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.486
37	resnet_50_v1_spiking	.486
38	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.486
39	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.486
40	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.486
41	effnetb1_272x240	.486
42	yudixie_resnet18_distance_translation_rotation_0_240719	.486
43	nasnet_large	.486
44	cvt_cvt-21-384-in1k_4_LucyV4	.475
45	custom_model_cv_18_dagger_408	.440
46	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.399
47	convnext_small_imagenet_1_seed-0	.399
48	yudixie_resnet18_imagenet1kpret_0_240719	.399
49	ReAlnet03_ALL	.399
50	densenet-169	.399
51	vit_large_patch14_clip_224:laion2b_ft_in1k	.361
52	vit_large_patch14_clip_224:openai_ft_in1k	.361
53	yudixie_resnet50_distance_reg_0_240908	.361
54	AdvProp_efficientnet-b6	.361
55	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.361
56	resnext101_32x48d_wsl	.361
57	resnet18_ecoset_full	.361
58	AdvProp_efficientnet-b2	.361
59	BiT-S-R50x3	.361
60	AT_efficientnet-b2	.361
61	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.327
62	deit_small_imagenet_full_seed-0	.327
63	convnext_small_imagenet_10_seed-0	.327
64	deit_large_imagenet_full_seed-0	.327
65	resnet-18_test_m	.327
66	yudixie_resnet18_translation_reg_0_240719	.327
67	resnet34_ecoset_full	.296
68	convnext_large_imagenet_full_seed-0	.296
69	yudixie_resnet50_distance_rotation_0_240908	.296
70	efficientnet-b7	.296
71	convnext_base:clip_laiona_augreg_ft_in1k_384	.296
72	deit_small_imagenet_1_seed-0	.268
73	mobilenet_v2_1_3_224	.268
74	resnet50-vicregl0p75	.268
75	resnet34_imagenet_full	.243
76	convnext_tiny_sup	.243
77	BiT-S-R152x4	.243
78	resnet50-vicreg	.220
79	resnet_101_v2	.220
80	vonegrcnn_52e_full	.220
81	BiT-S-R101x1	.220
82	mobilenet_v2_0_5_224	.199
83	cvt_cvt-13-384-in1k_4_LucyV4	.199
84	Res2Net50_26w_4s	.199
85	mobilenet_v2_1_0_224	.199
86	ReAlnet04_ALL	.199
87	ReAlnet06_ALL	.199
88	BiT-S-R50x1	.199
89	ReAlnet10_ALL	.180
90	resnet-152_v2_pytorch	.180
91	convnext_base_imagenet_full_seed-0	.180
92	mobilenet_v2_0_75_192	.180
93	resnet50-SIN_IN_IN	.180
94	resnet50_primary_visual_cortex	.180
95	yudixie_resnet18_distance_translation_0_240719	.163
96	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.163
97	ReAlnet08_ALL	.163
98	resnet50_imagenet_full	.148
99	deit_base_imagenet_full_seed-0	.148
100	pnasnet_large_pytorch	.148
101	efficientnet_b2_imagenet_full	.148
102	pnasnet_large	.148
103	resnet_50_v1_spiking_l3	.148
104	ReAlnet01_ALL	.148
105	resnet50-moclr8deg	.148
106	BiT-S-R101x3	.148
107	densenet-201	.134
108	efficientnet_b1_imagenet_full	.134
109	resnet50-SIN	.134
110	ReAlnet02_ALL	.134
111	grcnn	.134
112	voneresnet-50	.134
113	grcnn_109	.134
114	resnet_50_v2	.134
115	yudixie_resnet50_imagenet1kpret_0_240908	.121
116	convnext_small_imagenet_full_seed-0	.121
117	ViT_L_32_imagenet1k	.121
118	resnet152_imagenet_full	.121
119	yudixie_resnet18_translation_rotation_0_240719	.121
120	yudixie_resnet50_rotation_reg_0_240908	.121
121	yudixie_resnet18_object_class_0_240719	.121
122	artResNet18_1	.121
123	inception_v3	.110
124	convnext_tiny_imagenet_full_seed-0	.110
125	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.110
126	VOneCORnet-S	.110
127	resnet50_imagenet_10_seed-0	.110
128	xception	.110
129	antialiased-r50	.110
130	AdvProp_efficientnet-b8	.110
131	convnext_tiny:in12k_ft_in1k	.099
132	alexnet_training_seed_08	.099
133	deit_small_imagenet_100_seed-0	.099
134	yolos_tiny	.099
135	convnext_small_imagenet_100_seed-0	.099
136	yudixie_resnet18_distance_rotation_0_240719	.099
137	nasnet_mobile	.099
138	vgg_19	.099
139	yudixie_resnet50_distance_translation_rotation_0_240908	.099
140	alexnet_training_seed_09	.099
141	vgg_16	.090
142	alexnet_training_seed_02	.081
143	ReAlnet09	.081
144	mobilenet_v2_0_75_160	.081
145	mobilenet_v2_1-4_224_pytorch	.081
146	shufflenet_v2_x1_0	.081
147	ReAlnet09_cornet	.081
148	efficientnet_b0	.081
149	mobilenet_v2_1_4_224	.081
150	yudixie_resnet50_object_class_0_240908	.081
151	yudixie_resnet18_distance_reg_0_240719	.074
152	ReAlnet08	.067
153	inception_v4	.067
154	ReAlnet04_cornet	.067
155	ReAlnet08_cornet	.067
156	resnet_152_v2	.067
157	ReAlnet04	.067
158	resnet50_tutorial	.060
159	resnet18_imagenet_full	.060
160	resnet101_ecoset_full	.060
161	resnet_152_v1	.060
162	resnet101_imagenet_full	.055
163	resnet50-barlow	.055
164	alexnet_training_seed_03	.055
165	yudixie_resnet50_category_class_0_240908	.050
166	yudixie_resnet18_random_0_240719	.050
167	vonegrcnn_62e_nobn	.050
168	ReAlnet09_ALL	.050
169	yudixie_resnet18_rotation_reg_0_240719	.045
170	ReAlnet06	.041
171	briaai_rmbg_1_4	.041
172	mobilenet_v2_0_5_192	.041
173	ReAlnet06_cornet	.041
174	vonegrcnn_47e	.041
175	ReAlnet07_ALL	.041
176	ReAlnet10	.037
177	resnet_50_v1_spiking_l4a	.037
178	resnet50_imagenet_100_seed-0	.037
179	yudixie_resnet50_distance_translation_0_240908	.037
180	ReAlnet10_cornet	.037
181	AdvProp_efficientnet-b7	.037
182	convnext_femto_ols:d1_in1k	.037
183	alexnet_training_seed_06	.033
184	mobilenet_v2_1_0_128	.033
185	alexnet_training_seed_07	.033
186	inception_v1	.030
187	ReAlnet03	.027
188	resnet50_ecoset_full	.027
189	ReAlnet03_cornet	.027
190	resnet_101_v1	.027
191	resnet50-vicregl0p9	.027
192	resnet-50-robust	.025
193	resnet50-VITO-8deg-cc	.025
194	resnet_50_v1	.025
195	resnet50-vitoimagevidnet8	.025
196	resnet50-sup	.025
197	ReAlnet05	.022
198	ReAlnet05_cornet	.022
199	voneresnet-50-robust	.022
200	blt_vs	.020
201	ReAlnet02_cornet	.020
202	ReAlnet02	.020
203	efficientnet_b0_imagenet_full	.018
204	ReAlnet07	.017
205	resnet50-SIN_IN	.017
206	ReAlnet07_cornet	.017
207	yudixie_resnet50_translation_rotation_0_240908	.017
208	yudixie_resnet50_random_0_240908	.015
209	resnet50_robust_l2_eps1	.014
210	alexnet_training_seed_04	.011
211	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.011
212	alexnet_training_seed_10	.011
213	ReAlnet01_cornet	.010
214	voneresnet-50-non_stochastic	.010
215	ReAlnet01	.010
216	resnet50_robust_l2_eps3	.008
217	imagenet_l2_3_0	.008
218	resnet50_imagenet_1_seed-0	.006
219	hmax

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