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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	cvt_cvt-13-384-in1k_4_LucyV4	1.0
2	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
3	efficientnet_b0_imagenet_full	1.0
4	resnext101_32x32d_wsl	1.0
5	mobilenet_v2_0_75_192	1.0
6	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
7	yudixie_resnet18_random_0_240719	1.0
8	resnet_152_v2	1.0
9	ReAlnet05	1.0
10	yudixie_resnet50_random_0_240908	1.0
11	yudixie_resnet50_imagenet1kpret_0_240908	1.0
12	alexnet_training_seed_05	1.0
13	resnet18_ecoset_full	1.0
14	yudixie_resnet50_distance_reg_0_240908	1.0
15	mobilenet_v2_0_5_224	1.0
16	resnet18_imagenet_full	1.0
17	alexnet_training_seed_07	1.0
18	resnet50_imagenet_1_seed-0	1.0
19	ReAlnet05_cornet	1.0
20	yudixie_resnet18_rotation_reg_0_240719	1.0
21	artResNet18_1	1.0
22	convnext_tiny_sup	1.0
23	resnet50_tutorial	.975
24	convnext_base_imagenet_full_seed-0	.975
25	inception_v4	.975
26	resnext101_32x8d_wsl	.975
27	effnetb1_272x240	.975
28	resnet-152_v2_pytorch	.975
29	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.942
30	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.942
31	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.942
32	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.942
33	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.942
34	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.942
35	nasnet_mobile	.942
36	vonegrcnn_47e	.942
37	vonegrcnn_52e_full	.942
38	convnext_small_imagenet_1_seed-0	.882
39	convnext_small_imagenet_10_seed-0	.882
40	resnet34_imagenet_full	.852
41	resnet_50_v1_spiking_l4a	.852
42	alexnet_training_seed_04	.852
43	resnet152_ecoset_full	.852
44	resnet50-barlow	.852
45	BiT-S-R152x4	.852
46	voneresnet-50-non_stochastic	.798
47	focalnet_tiny_lrf_in1k	.798
48	efficientnet-b7	.798
49	resnet_50_v1_spiking_l3	.798
50	AdvProp_efficientnet-b8	.798
51	convnext_xlarge:fb_in22k_ft_in1k	.771
52	vit_large_patch14_clip_224:openai_ft_in1k	.771
53	vit_large_patch14_clip_336:laion2b_ft_in1k	.771
54	resnext101_32x48d_wsl	.771
55	ViT_L_32_imagenet1k	.771
56	yudixie_resnet18_category_class_0_240719	.771
57	efficientnet_b0	.771
58	grcnn	.771
59	voneresnet-50-robust	.771
60	AdvProp_efficientnet-b4	.771
61	AdvProp_efficientnet-b2	.771
62	AT_efficientnet-b2	.771
63	vit_base_patch16_clip_224:openai_ft_in1k	.771
64	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.722
65	yudixie_resnet50_category_class_0_240908	.722
66	mobilenet_v2_0_5_192	.722
67	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.722
68	yudixie_resnet18_translation_reg_0_240719	.722
69	AdvProp_efficientnet-b7	.722
70	ReAlnet07	.698
71	vit_large_patch14_clip_224:laion2b_ft_in1k	.698
72	Res2Net50_26w_4s	.698
73	deit_small_imagenet_1_seed-0	.698
74	ReAlnet07_cornet	.698
75	vgg_16	.698
76	omnivore_swinB	.698
77	BiT-S-R101x3	.698
78	densenet-121	.698
79	mobilenet_v2_1_0_160	.653
80	yudixie_resnet50_object_class_0_240908	.631
81	convnext_large:fb_in22k_ft_in1k	.631
82	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.631
83	convnext_tiny_imagenet_full_seed-0	.631
84	yudixie_resnet18_translation_rotation_0_240719	.631
85	yudixie_resnet18_distance_translation_rotation_0_240719	.631
86	yudixie_resnet18_imagenet1kpret_0_240719	.631
87	alexnet_training_seed_09	.591
88	mobilenet_v2_0_75_160	.591
89	briaai_rmbg_1_4	.591
90	alexnet_training_seed_10	.591
91	resnet50-SIN_IN	.591
92	inception_v1	.591
93	resnet_152_v1	.571
94	resnet_50_v1_spiking	.571
95	convnext_tiny:in12k_ft_in1k	.571
96	mobilenet_v2_1_0_192	.571
97	pnasnet_large_pytorch	.571
98	ReAlnet02_cornet	.571
99	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.571
100	yudixie_resnet18_distance_rotation_0_240719	.571
101	resnet50_robust_l2_eps1	.571
102	vonegrcnn_62e_nobn	.571
103	BiT-S-R50x3	.571
104	ReAlnet02	.571
105	BiT-S-R50x1	.571
106	VOneCORnet-S	.535
107	mobilenet_v2_1_3_224	.535
108	resnet50-vicregl0p9	.535
109	cvt_cvt-21-384-in1k_4_LucyV4	.517
110	alexnet_training_seed_06	.517
111	vit_relpos_base_patch16_clsgap_224:sw_in1k	.517
112	resnet50_ecoset_full	.517
113	shufflenet_v2_x1_0	.517
114	resnet50-vicreg	.517
115	vgg_19	.517
116	voneresnet-50	.517
117	hmax	.517
118	resnet50_imagenet_full	.484
119	yudixie_resnet18_distance_translation_0_240719	.484
120	nasnet_large	.484
121	alexnet_training_seed_03	.467
122	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.467
123	deit_small_imagenet_10_seed-0	.467
124	deit_large_imagenet_full_seed-0	.467
125	resnet50_imagenet_100_seed-0	.467
126	resnet_101_v2	.438
127	deit_base_imagenet_full_seed-0	.423
128	densenet-201	.423
129	mobilenet_v2_1-4_224_pytorch	.423
130	yolos_tiny	.423
131	mobilenet_v2_1_4_224	.423
132	grcnn_109	.423
133	antialiased-r50	.423
134	resnet_SIN_IN_FT_IN	.423
135	alexnet_training_seed_01	.396
136	inception_v3	.383
137	ReAlnet08	.383
138	cvt_cvt-13-224-in1k_4_LucyV4	.383
139	convnext_large_imagenet_full_seed-0	.383
140	resnet-50-robust	.383
141	mobilenet_v2_1_0_224	.383
142	ReAlnet08_cornet	.383
143	omnivore_swinS	.383
144	convnext_base:clip_laiona_augreg_ft_in1k_384	.383
145	mobilenet_v2_0_75_224	.358
146	resnet50-vicregl0p75	.358
147	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.346
148	efficientnet_b2_imagenet_full	.346
149	cvt_cvt-21-224-in1k_4_LucyV4	.346
150	convnext_femto_ols:d1_in1k	.346
151	custom_model_cv_18_dagger_408	.324
152	resnet50-SIN	.324
153	resnet_50_v1	.324
154	resnet50-sup	.324
155	densenet-169	.324
156	yudixie_resnet50_distance_translation_rotation_0_240908	.313
157	convnext_small_imagenet_full_seed-0	.313
158	convnext_small_imagenet_100_seed-0	.313
159	resnet50-SIN_IN_IN	.313
160	ReAlnet07_ALL	.313
161	BiT-S-R101x1	.313
162	ReAlnet09	.283
163	resnet101_ecoset_full	.283
164	mobilenet_v2_1_0_128	.283
165	blt_vs	.283
166	resnet-18_test_m	.283
167	yudixie_resnet18_object_class_0_240719	.283
168	yudixie_resnet50_rotation_reg_0_240908	.283
169	resnet50-vitoimagevidnet8	.283
170	ReAlnet09_cornet	.283
171	resnet50-VITO-8deg-cc	.283
172	ReAlnet01_cornet	.256
173	yudixie_resnet50_distance_translation_0_240908	.256
174	ReAlnet01	.256
175	BiT-S-R152x2	.240
176	yudixie_resnet50_distance_rotation_0_240908	.232
177	ReAlnet05_ALL	.232
178	ReAlnet08_ALL	.232
179	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.232
180	resnet_50_v1_spiking_l4	.217
181	resnet101_imagenet_full	.217
182	AdvProp_efficientnet-b6	.210
183	resnet152_imagenet_full	.196
184	ReAlnet10_ALL	.190
185	resnet_50_v2	.172
186	ReAlnet06	.172
187	ReAlnet10	.172
188	resnet34_ecoset_full	.172
189	yudixie_resnet50_translation_reg_0_240908	.172
190	ReAlnet06_cornet	.172
191	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.172
192	ReAlnet10_cornet	.172
193	ReAlnet03	.155
194	ReAlnet03_cornet	.155
195	resnet50_imagenet_10_seed-0	.155
196	yudixie_resnet18_distance_reg_0_240719	.155
197	ReAlnet02_ALL	.155
198	resnet_101_v1	.155
199	ReAlnet09_ALL	.155
200	alexnet_training_seed_08	.145
201	deit_small_imagenet_100_seed-0	.141
202	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.141
203	ReAlnet04_cornet	.127
204	ReAlnet04	.127
205	efficientnet_b1_imagenet_full	.115
206	xception	.115
207	ReAlnet04_ALL	.115
208	resnet50_robust_l2_eps3	.115
209	imagenet_l2_3_0	.115
210	yudixie_resnet50_translation_rotation_0_240908	.108
211	alexnet_training_seed_02	.104
212	resnet50-moclr8deg	.104
213	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.094
214	ReAlnet06_ALL	.094
215	deit_small_imagenet_full_seed-0	.077
216	ReAlnet01_ALL	.077
217	ReAlnet03_ALL	.077
218	resnet50_primary_visual_cortex	.072
219	pnasnet_large

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