Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024half-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	efficientnet_b0_imagenet_full	1.0
2	resnext101_32x32d_wsl	1.0
3	yudixie_resnet18_random_0_240719	1.0
4	resnet_152_v2	1.0
5	cvt_cvt-13-384-in1k_4_LucyV4	1.0
6	mobilenet_v2_0_75_192	1.0
7	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
8	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
9	resnet18_imagenet_full	1.0
10	ReAlnet05_cornet	1.0
11	yudixie_resnet18_rotation_reg_0_240719	1.0
12	ReAlnet05	1.0
13	yudixie_resnet50_random_0_240908	1.0
14	yudixie_resnet50_imagenet1kpret_0_240908	1.0
15	mobilenet_v2_0_5_224	1.0
16	resnet50_imagenet_1_seed-0	1.0
17	alexnet_training_seed_07	1.0
18	alexnet_training_seed_05	1.0
19	yudixie_resnet50_distance_reg_0_240908	1.0
20	convnext_tiny_sup	1.0
21	artResNet18_1	1.0
22	resnet18_ecoset_full	1.0
23	resnet50_tutorial	.975
24	inception_v4	.975
25	convnext_base_imagenet_full_seed-0	.975
26	resnext101_32x8d_wsl	.975
27	resnet-152_v2_pytorch	.975
28	effnetb1_272x240	.975
29	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.942
30	vonegrcnn_52e_full	.942
31	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.942
32	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.942
33	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.942
34	nasnet_mobile	.942
35	vonegrcnn_47e	.942
36	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.942
37	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.942
38	convnext_small_imagenet_1_seed-0	.882
39	convnext_small_imagenet_10_seed-0	.882
40	resnet152_ecoset_full	.852
41	BiT-S-R152x4	.852
42	resnet50-barlow	.852
43	resnet34_imagenet_full	.852
44	alexnet_training_seed_04	.852
45	AdvProp_efficientnet-b8	.798
46	voneresnet-50-non_stochastic	.798
47	focalnet_tiny_lrf_in1k	.798
48	efficientnet-b7	.798
49	yudixie_resnet18_category_class_0_240719	.771
50	resnext101_32x48d_wsl	.771
51	AdvProp_efficientnet-b2	.771
52	efficientnet_b0	.771
53	voneresnet-50-robust	.771
54	AdvProp_efficientnet-b4	.771
55	vit_base_patch16_clip_224:openai_ft_in1k	.771
56	ViT_L_32_imagenet1k	.771
57	vit_large_patch14_clip_336:laion2b_ft_in1k	.771
58	grcnn	.771
59	vit_large_patch14_clip_224:openai_ft_in1k	.771
60	AT_efficientnet-b2	.771
61	convnext_xlarge:fb_in22k_ft_in1k	.771
62	mobilenet_v2_0_5_192	.722
63	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.722
64	AdvProp_efficientnet-b7	.722
65	yudixie_resnet18_translation_reg_0_240719	.722
66	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.722
67	yudixie_resnet50_category_class_0_240908	.722
68	Res2Net50_26w_4s	.698
69	deit_small_imagenet_1_seed-0	.698
70	densenet-121	.698
71	ReAlnet07	.698
72	BiT-S-R101x3	.698
73	vit_large_patch14_clip_224:laion2b_ft_in1k	.698
74	omnivore_swinB	.698
75	vgg_16	.698
76	ReAlnet07_cornet	.698
77	mobilenet_v2_1_0_160	.653
78	yudixie_resnet50_object_class_0_240908	.631
79	yudixie_resnet18_imagenet1kpret_0_240719	.631
80	convnext_large:fb_in22k_ft_in1k	.631
81	yudixie_resnet18_translation_rotation_0_240719	.631
82	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.631
83	convnext_tiny_imagenet_full_seed-0	.631
84	yudixie_resnet18_distance_translation_rotation_0_240719	.631
85	inception_v1	.591
86	mobilenet_v2_0_75_160	.591
87	resnet50-SIN_IN	.591
88	briaai_rmbg_1_4	.591
89	alexnet_training_seed_10	.591
90	alexnet_training_seed_09	.591
91	resnet_152_v1	.571
92	yudixie_resnet18_distance_rotation_0_240719	.571
93	mobilenet_v2_1_0_192	.571
94	ReAlnet02	.571
95	vonegrcnn_62e_nobn	.571
96	pnasnet_large_pytorch	.571
97	resnet50_robust_l2_eps1	.571
98	ReAlnet02_cornet	.571
99	BiT-S-R50x3	.571
100	BiT-S-R50x1	.571
101	convnext_tiny:in12k_ft_in1k	.571
102	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.571
103	mobilenet_v2_1_3_224	.535
104	resnet50-vicregl0p9	.535
105	VOneCORnet-S	.535
106	resnet50_ecoset_full	.517
107	vit_relpos_base_patch16_clsgap_224:sw_in1k	.517
108	voneresnet-50	.517
109	alexnet_training_seed_06	.517
110	vgg_19	.517
111	resnet50-vicreg	.517
112	shufflenet_v2_x1_0	.517
113	cvt_cvt-21-384-in1k_4_LucyV4	.517
114	hmax	.517
115	resnet50_imagenet_full	.484
116	nasnet_large	.484
117	yudixie_resnet18_distance_translation_0_240719	.484
118	alexnet_training_seed_03	.467
119	resnet50_imagenet_100_seed-0	.467
120	deit_small_imagenet_10_seed-0	.467
121	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.467
122	deit_large_imagenet_full_seed-0	.467
123	resnet_101_v2	.438
124	deit_base_imagenet_full_seed-0	.423
125	densenet-201	.423
126	mobilenet_v2_1_4_224	.423
127	grcnn_109	.423
128	mobilenet_v2_1-4_224_pytorch	.423
129	yolos_tiny	.423
130	resnet_SIN_IN_FT_IN	.423
131	antialiased-r50	.423
132	alexnet_training_seed_01	.396
133	inception_v3	.383
134	ReAlnet08	.383
135	cvt_cvt-13-224-in1k_4_LucyV4	.383
136	convnext_large_imagenet_full_seed-0	.383
137	resnet-50-robust	.383
138	mobilenet_v2_1_0_224	.383
139	ReAlnet08_cornet	.383
140	omnivore_swinS	.383
141	convnext_base:clip_laiona_augreg_ft_in1k_384	.383
142	resnet50-vicregl0p75	.358
143	mobilenet_v2_0_75_224	.358
144	efficientnet_b2_imagenet_full	.346
145	cvt_cvt-21-224-in1k_4_LucyV4	.346
146	convnext_femto_ols:d1_in1k	.346
147	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.346
148	densenet-169	.324
149	resnet50-SIN	.324
150	custom_model_cv_18_dagger_408	.324
151	resnet50-sup	.324
152	resnet_50_v1	.324
153	resnet50-SIN_IN_IN	.313
154	convnext_small_imagenet_full_seed-0	.313
155	convnext_small_imagenet_100_seed-0	.313
156	yudixie_resnet50_distance_translation_rotation_0_240908	.313
157	BiT-S-R101x1	.313
158	resnet50-vitoimagevidnet8	.283
159	yudixie_resnet18_object_class_0_240719	.283
160	resnet-18_test_m	.283
161	yudixie_resnet50_rotation_reg_0_240908	.283
162	ReAlnet09_cornet	.283
163	resnet50-VITO-8deg-cc	.283
164	blt_vs	.283
165	mobilenet_v2_1_0_128	.283
166	resnet101_ecoset_full	.283
167	ReAlnet09	.283
168	ReAlnet01_cornet	.256
169	ReAlnet_incorrect	.256
170	ReAlnet01	.256
171	yudixie_resnet50_distance_translation_0_240908	.256
172	BiT-S-R152x2	.240
173	yudixie_resnet50_distance_rotation_0_240908	.232
174	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.232
175	resnet101_imagenet_full	.217
176	AdvProp_efficientnet-b6	.210
177	resnet152_imagenet_full	.196
178	resnet_50_v2	.172
179	resnet34_ecoset_full	.172
180	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.172
181	ReAlnet06	.172
182	yudixie_resnet50_translation_reg_0_240908	.172
183	ReAlnet06_cornet	.172
184	ReAlnet10	.172
185	ReAlnet10_cornet	.172
186	ReAlnet03_cornet	.155
187	resnet50_imagenet_10_seed-0	.155
188	yudixie_resnet18_distance_reg_0_240719	.155
189	ReAlnet03	.155
190	resnet_101_v1	.155
191	alexnet_training_seed_08	.145
192	deit_small_imagenet_100_seed-0	.141
193	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.141
194	ReAlnet04	.127
195	ReAlnet04_cornet	.127
196	imagenet_l2_3_0	.115
197	xception	.115
198	resnet50_robust_l2_eps3	.115
199	efficientnet_b1_imagenet_full	.115
200	yudixie_resnet50_translation_rotation_0_240908	.108
201	alexnet_training_seed_02	.104
202	resnet50-moclr8deg	.104
203	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.094
204	deit_small_imagenet_full_seed-0	.077
205	pnasnet_large	X

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

0.90.

Note that scores are relative to this ceiling.

Data: Ferguson2024half

Metric: value_delta