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