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

0.83.

Note that scores are relative to this ceiling.

Data: Ferguson2024lle

Metric: value_delta