Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024lle-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	mobilenet_v2_0_5_224	1.0
2	resnet50_imagenet_1_seed-0	1.0
3	AdvProp_efficientnet-b8	1.0
4	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
5	ReAlnet10	1.0
6	alexnet_training_seed_08	1.0
7	alexnet_training_seed_03	1.0
8	ReAlnet10_cornet	1.0
9	mobilenet_v2_1_0_160	1.0
10	resnet50-vicregl0p9	1.0
11	resnet50_tutorial	1.0
12	densenet-169	1.0
13	resnext101_32x48d_wsl	1.0
14	deit_small_imagenet_10_seed-0	1.0
15	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
16	focalnet_tiny_lrf_in1k	1.0
17	yudixie_resnet50_random_0_240908	1.0
18	vgg_16	1.0
19	resnet50-vicregl0p75	1.0
20	ReAlnet08_cornet	1.0
21	ReAlnet08	1.0
22	resnet50_robust_l2_eps1	1.0
23	resnet50-SIN_IN	1.0
24	yudixie_resnet50_distance_rotation_0_240908	1.0
25	vgg_19	1.0
26	cvt_cvt-21-384-in1k_4_LucyV4	1.0
27	vit_base_patch16_clip_224:openai_ft_in1k	1.0
28	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
29	deit_base_imagenet_full_seed-0	1.0
30	resnet152_imagenet_full	1.0
31	shufflenet_v2_x1_0	.967
32	omnivore_swinS	.967
33	mobilenet_v2_1_3_224	.967
34	Res2Net50_26w_4s	.911
35	inception_v1	.911
36	yudixie_resnet50_imagenet1kpret_0_240908	.911
37	resnet152_ecoset_full	.911
38	BiT-S-R152x2	.911
39	alexnet_training_seed_01	.911
40	efficientnet_b0	.911
41	alexnet_training_seed_02	.875
42	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.875
43	resnext101_32x32d_wsl	.875
44	yudixie_resnet50_rotation_reg_0_240908	.875
45	yudixie_resnet50_distance_translation_rotation_0_240908	.875
46	ReAlnet04_cornet	.825
47	resnet-50-robust	.825
48	artResNet18_1	.825
49	ReAlnet04	.825
50	briaai_rmbg_1_4	.825
51	convnext_tiny_imagenet_full_seed-0	.825
52	AdvProp_efficientnet-b2	.793
53	convnext_xlarge:fb_in22k_ft_in1k	.793
54	AT_efficientnet-b2	.793
55	efficientnet_b1_imagenet_full	.747
56	inception_v3	.747
57	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.747
58	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
59	resnet34_ecoset_full	.747
60	yudixie_resnet18_random_0_240719	.718
61	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.718
62	mobilenet_v2_0_75_224	.718
63	BiT-S-R101x1	.718
64	voneresnet-50-non_stochastic	.718
65	mobilenet_v2_1_0_192	.676
66	cvt_cvt-21-224-in1k_4_LucyV4	.676
67	cvt_cvt-13-224-in1k_4_LucyV4	.676
68	resnet_50_v1	.650
69	AdvProp_efficientnet-b6	.650
70	resnet50-sup	.650
71	resnet_50_v2	.650
72	nasnet_mobile	.612
73	yolos_tiny	.612
74	resnet50_imagenet_full	.612
75	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.612
76	resnet_50_v1_spiking	.588
77	resnet_50_v1_spiking_l4a	.588
78	resnet50-vicreg	.588
79	resnet50-SIN_IN_IN	.554
80	resnet34_imagenet_full	.554
81	yudixie_resnet18_translation_reg_0_240719	.554
82	vit_relpos_base_patch16_clsgap_224:sw_in1k	.554
83	vit_large_patch14_clip_336:laion2b_ft_in1k	.554
84	efficientnet-b7	.532
85	convnext_tiny:in12k_ft_in1k	.532
86	alexnet_training_seed_06	.532
87	ReAlnet06_cornet	.532
88	BiT-S-R50x1	.532
89	ReAlnet06	.532
90	vonegrcnn_62e_nobn	.532
91	resnet-18_test_m	.532
92	custom_model_cv_18_dagger_408	.502
93	antialiased-r50	.502
94	resnet_50_v1_spiking_l4	.502
95	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.502
96	mobilenet_v2_0_75_192	.502
97	VOneCORnet-S	.502
98	blt_vs	.502
99	alexnet_training_seed_09	.502
100	yudixie_resnet18_distance_translation_0_240719	.502
101	ReAlnet07	.482
102	ReAlnet07_cornet	.482
103	resnext101_32x8d_wsl	.454
104	resnet50-barlow	.454
105	voneresnet-50	.454
106	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.454
107	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.454
108	efficientnet_b2_imagenet_full	.436
109	resnet50_primary_visual_cortex	.436
110	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.411
111	resnet_SIN_IN_FT_IN	.411
112	alexnet_training_seed_10	.411
113	convnext_base:clip_laiona_augreg_ft_in1k_384	.411
114	ReAlnet01	.411
115	ReAlnet01_cornet	.411
116	alexnet_training_seed_05	.411
117	yudixie_resnet18_category_class_0_240719	.411
118	voneresnet-50-robust	.395
119	resnet101_ecoset_full	.372
120	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.372
121	resnet_152_v2	.372
122	yudixie_resnet18_distance_translation_rotation_0_240719	.372
123	resnet-152_v2_pytorch	.372
124	ReAlnet03_cornet	.358
125	inception_v4	.358
126	ReAlnet03	.358
127	yudixie_resnet50_translation_rotation_0_240908	.358
128	BiT-S-R50x3	.337
129	convnext_large:fb_in22k_ft_in1k	.337
130	yudixie_resnet18_distance_reg_0_240719	.337
131	deit_small_imagenet_1_seed-0	.337
132	ReAlnet05	.337
133	resnet50-moclr8deg	.337
134	yudixie_resnet18_translation_rotation_0_240719	.337
135	mobilenet_v2_1_0_128	.337
136	ReAlnet05_cornet	.337
137	BiT-S-R152x4	.324
138	vonegrcnn_47e	.324
139	vonegrcnn_52e_full	.305
140	resnet18_ecoset_full	.305
141	pnasnet_large	.305
142	BiT-S-R101x3	.305
143	omnivore_swinB	.293
144	resnet50_imagenet_100_seed-0	.276
145	mobilenet_v2_0_5_192	.276
146	alexnet_training_seed_04	.276
147	cvt_cvt-13-384-in1k_4_LucyV4	.276
148	resnet_50_v1_spiking_l3	.276
149	vit_large_patch14_clip_224:openai_ft_in1k	.276
150	nasnet_large	.276
151	convnext_tiny_sup	.265
152	deit_small_imagenet_100_seed-0	.250
153	yudixie_resnet50_category_class_0_240908	.250
154	yudixie_resnet50_object_class_0_240908	.250
155	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.226
156	convnext_small_imagenet_full_seed-0	.226
157	mobilenet_v2_0_75_160	.226
158	vit_large_patch14_clip_224:laion2b_ft_in1k	.226
159	yudixie_resnet18_imagenet1kpret_0_240719	.205
160	yudixie_resnet18_object_class_0_240719	.205
161	grcnn	.205
162	mobilenet_v2_1_4_224	.205
163	mobilenet_v2_1-4_224_pytorch	.205
164	yudixie_resnet50_distance_translation_0_240908	.205
165	resnet_101_v1	.186
166	resnet_101_v2	.178
167	effnetb1_272x240	.168
168	convnext_small_imagenet_100_seed-0	.168
169	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.168
170	AdvProp_efficientnet-b7	.168
171	resnet_152_v1	.161
172	xception	.152
173	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.152
174	imagenet_l2_3_0	.152
175	resnet50_robust_l2_eps3	.152
176	yudixie_resnet18_rotation_reg_0_240719	.146
177	ReAlnet09_cornet	.138
178	ReAlnet09	.138
179	yudixie_resnet18_distance_rotation_0_240719	.138
180	resnet50-vitoimagevidnet8	.125
181	resnet50-VITO-8deg-cc	.125
182	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.125
183	resnet50_imagenet_10_seed-0	.125
184	yudixie_resnet50_distance_reg_0_240908	.125
185	convnext_base_imagenet_full_seed-0	.113
186	convnext_large_imagenet_full_seed-0	.113
187	resnet18_imagenet_full	.113
188	convnext_femto_ols:d1_in1k	.113
189	densenet-201	.108
190	ViT_L_32_imagenet1k	.108
191	pnasnet_large_pytorch	.092
192	ReAlnet02_cornet	.069
193	ReAlnet02	.069
194	yudixie_resnet50_translation_reg_0_240908	.069
195	efficientnet_b0_imagenet_full	.069
196	convnext_small_imagenet_10_seed-0	.069
197	resnet50_ecoset_full	.069
198	grcnn_109	.062
199	resnet50-SIN	.062
200	convnext_small_imagenet_1_seed-0	.062
201	AdvProp_efficientnet-b4	.056
202	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.051
203	alexnet_training_seed_07	.051
204	densenet-121	.046
205	deit_small_imagenet_full_seed-0	.046
206	deit_large_imagenet_full_seed-0	.025
207	resnet101_imagenet_full	.023
208	mobilenet_v2_1_0_224
209	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

0.83.

Note that scores are relative to this ceiling.

Data: Ferguson2024lle

Metric: value_delta