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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024round_f-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_tiny:in12k_ft_in1k	1.0
2	convnext_small_imagenet_10_seed-0	1.0
3	yudixie_resnet18_translation_rotation_0_240719	1.0
4	alexnet_training_seed_01	1.0
5	resnet-18_test_m	1.0
6	yudixie_resnet50_translation_reg_0_240908	1.0
7	resnet50-vicreg	1.0
8	briaai_rmbg_1_4	1.0
9	compact_vgg19_V4	1.0
10	vit_base_patch16_clip_224:openai_ft_in1k	1.0
11	VOneCORnet-S	1.0
12	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.961
13	cvt_cvt-13-224-in1k_4_LucyV4	.961
14	resnext101_32x32d_wsl	.961
15	resnet-152_v2_pytorch	.961
16	inception_v4	.961
17	resnet_101_v1	.961
18	convnext_base:clip_laiona_augreg_ft_in1k_384	.961
19	yudixie_resnet50_random_0_240908	.906
20	compact_resnet50_robust_V4	.906
21	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.906
22	yudixie_resnet50_distance_rotation_0_240908	.906
23	compact_vgg19_IT	.906
24	inception_v1	.906
25	mobilenet_v2_1_0_160	.867
26	alexnet_training_seed_10	.867
27	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.867
28	resnet50_ecoset_full	.867
29	yudixie_resnet18_rotation_reg_0_240719	.867
30	resnet_50_v2	.867
31	inception_v3	.818
32	convnext_xlarge:fb_in22k_ft_in1k	.818
33	yudixie_resnet18_distance_rotation_0_240719	.818
34	deit_small_imagenet_full_seed-0	.783
35	resnet50_imagenet_10_seed-0	.783
36	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.783
37	alexnet_training_seed_04	.783
38	resnet18_imagenet_full	.783
39	alexnet_training_seed_07	.783
40	resnet_152_v2	.783
41	AdvProp_efficientnet-b4	.783
42	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.739
43	compact_cornets_V4	.739
44	resnet_101_v2	.739
45	deit_base_imagenet_full_seed-0	.707
46	yolos_tiny	.707
47	efficientnet_b2_imagenet_full	.707
48	ReAlnet02_cornet	.707
49	BiT-S-R152x2	.707
50	ReAlnet02	.707
51	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.667
52	resnet101_imagenet_full	.667
53	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.667
54	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.667
55	yudixie_resnet18_random_0_240719	.667
56	yudixie_resnet50_distance_translation_rotation_0_240908	.667
57	yudixie_resnet50_object_class_0_240908	.638
58	vit_large_patch14_clip_224:openai_ft_in1k	.638
59	alexnet_training_seed_02	.638
60	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.638
61	resnet_50_v1_spiking_l4a	.638
62	cvt_cvt-21-224-in1k_4_LucyV4	.638
63	compact_resnet50_IT	.638
64	imagenet_l2_3_0	.638
65	resnet50_robust_l2_eps3	.638
66	BiT-S-R101x3	.638
67	BiT-S-R101x1	.638
68	ReAlnet08_ALL	.638
69	deit_small_imagenet_100_seed-0	.602
70	resnext101_32x8d_wsl	.576
71	alexnet_training_seed_06	.576
72	efficientnet_b0	.576
73	yudixie_resnet50_translation_rotation_0_240908	.576
74	pnasnet_large	.576
75	BiT-S-R50x1	.576
76	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.544
77	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.544
78	vit_large_patch14_clip_224:laion2b_ft_in1k	.544
79	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.544
80	mobilenet_v2_1-4_224_pytorch	.544
81	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.544
82	compact_resnet50_V4	.544
83	mobilenet_v2_1_4_224	.544
84	convnext_large:fb_in22k_ft_in1k	.544
85	deit_small_imagenet_10_seed-0	.520
86	alexnet_training_seed_09	.520
87	ReAlnet10_ALL	.520
88	ReAlnet09	.470
89	convnext_base_imagenet_full_seed-0	.470
90	yudixie_resnet18_translation_reg_0_240719	.470
91	resnet50-moclr8deg	.470
92	ReAlnet09_cornet	.470
93	convnext_small_imagenet_1_seed-0	.443
94	yudixie_resnet18_distance_reg_0_240719	.443
95	efficientnet_b1_imagenet_full	.424
96	mobilenet_v2_0_75_224	.424
97	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.424
98	efficientnet_b0_imagenet_full	.424
99	xception	.424
100	voneresnet-50	.424
101	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.400
102	vit_large_patch14_clip_336:laion2b_ft_in1k	.400
103	deit_small_imagenet_1_seed-0	.400
104	resnet_50_v1_spiking	.383
105	resnet18_ecoset_full	.383
106	convnext_tiny_imagenet_full_seed-0	.383
107	voneresnet-50-non_stochastic	.383
108	pnasnet_large_pytorch	.383
109	ReAlnet05_ALL	.383
110	ReAlnet06_ALL	.383
111	compact_resnet50_robust_IT	.361
112	convnext_small_imagenet_100_seed-0	.346
113	hmax	.346
114	yudixie_resnet50_rotation_reg_0_240908	.346
115	yudixie_resnet18_imagenet1kpret_0_240719	.346
116	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.346
117	artResNet18_1	.346
118	omnivore_swinS	.346
119	resnet_50_v1_spiking_l4	.326
120	resnext101_32x48d_wsl	.326
121	convnext_femto_ols:d1_in1k	.326
122	resnet34_imagenet_full	.312
123	resnet50_ewconplus_wzc	.312
124	mobilenet_v2_0_5_224	.312
125	resnet152_ecoset_full	.312
126	nasnet_large	.312
127	ReAlnet09_ALL	.312
128	alexnet_training_seed_03	.312
129	cvt_cvt-21-384-in1k_4_LucyV4	.282
130	deit_large_imagenet_full_seed-0	.282
131	ReAlnet01_cornet	.282
132	nasnet_mobile	.282
133	ReAlnet01	.282
134	resnet50_imagenet_100_seed-0	.255
135	custom_model_cv_18_dagger_408	.255
136	resnet50-SIN_IN	.255
137	resnet50-SIN	.255
138	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.255
139	shufflenet_v2_x1_0	.255
140	ReAlnet02_ALL	.255
141	grcnn	.255
142	vonegrcnn_52e_full	.255
143	ReAlnet07_ALL	.255
144	yudixie_resnet50_distance_reg_0_240908	.230
145	yudixie_resnet18_distance_translation_rotation_0_240719	.230
146	yudixie_resnet50_distance_translation_0_240908	.230
147	yudixie_resnet18_category_class_0_240719	.230
148	omnivore_swinB	.230
149	ReAlnet03_ALL	.230
150	ReAlnet04_ALL	.230
151	resnet_SIN_IN_FT_IN	.230
152	densenet-121	.230
153	ReAlnet07	.208
154	ReAlnet03	.208
155	convnext_small_imagenet_full_seed-0	.208
156	ReAlnet03_cornet	.208
157	ReAlnet04_cornet	.208
158	resnet_50_v1_spiking_l3	.208
159	ReAlnet07_cornet	.208
160	ReAlnet01_ALL	.208
161	ReAlnet04	.208
162	ReAlnet08	.187
163	AdvProp_efficientnet-b6	.187
164	resnet50-VITO-8deg-cc	.187
165	vgg_16	.187
166	ReAlnet08_cornet	.187
167	resnet50-vitoimagevidnet8	.187
168	resnet50_robust_l2_eps1	.187
169	AdvProp_efficientnet-b2	.187
170	resnet50-vicregl0p9	.187
171	AT_efficientnet-b2	.187
172	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.169
173	convnext_large_imagenet_full_seed-0	.169
174	blt_vs	.160
175	yudixie_resnet18_object_class_0_240719	.160
176	ReAlnet05	.153
177	mobilenet_v2_0_5_192	.153
178	resnet101_ecoset_full	.153
179	ReAlnet05_cornet	.153
180	voneresnet-50-robust	.153
181	vonegrcnn_47e	.153
182	AdvProp_efficientnet-b8	.153
183	yudixie_resnet50_category_class_0_240908	.138
184	densenet-201	.138
185	ReAlnet10	.138
186	mobilenet_v2_0_75_160	.138
187	cvt_cvt-13-384-in1k_4_LucyV4	.138
188	compact_cornets_IT	.138
189	vonegrcnn_62e_nobn	.138
190	ReAlnet10_cornet	.138
191	resnet50_imagenet_1_seed-0	.125
192	resnet152_imagenet_full	.113
193	ReAlnet06	.113
194	yudixie_resnet18_distance_translation_0_240719	.113
195	ReAlnet06_cornet	.113
196	BiT-S-R50x3	.113
197	alexnet_training_seed_08	.102
198	resnet-50-robust	.102
199	ViT_L_32_imagenet1k	.102
200	grcnn_109	.102
201	BiT-S-R152x4	.102
202	resnet_152_v1	.102
203	resnet34_ecoset_full	.092
204	mobilenet_v2_0_75_192	.092
205	resnet50_imagenet_full	.092
206	efficientnet-b7	.092
207	vit_relpos_base_patch16_clsgap_224:sw_in1k	.092
208	resnet50_primary_visual_cortex	.092
209	mobilenet_v2_1_0_128	.083
210	resnet50_tutorial	.075
211	resnet50-barlow	.075
212	mobilenet_v2_1_0_224	.075
213	convnext_tiny_sup	.075
214	resnet50-vicregl0p75	.075
215	densenet-169	.075
216	effnetb1_272x240	.068
217	yudixie_resnet50_imagenet1kpret_0_240908	.061
218	mobilenet_v2_1_3_224	.061
219	focalnet_tiny_lrf_in1k	.055
220	AdvProp_efficientnet-b7	.055
221	alexnet_training_seed_05	.050
222	Res2Net50_26w_4s	.050
223	resnet_50_v1	.033
224	resnet50-sup	.033
225	mobilenet_v2_1_0_192	.030
226	antialiased-r50	.027
227	resnet50-SIN_IN_IN	.018
228	vgg_19	.012

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

0.87.

Note that scores are relative to this ceiling.

Data: Ferguson2024round_f

Metric: value_delta