Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024llh-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	alexnet_training_seed_09	1.0
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
3	ViT_L_32_imagenet1k	1.0
4	deit_small_imagenet_10_seed-0	1.0
5	convnext_femto_ols:d1_in1k	1.0
6	deit_base_imagenet_full_seed-0	1.0
7	alexnet_training_seed_06	1.0
8	alexnet_training_seed_10	1.0
9	resnet50-SIN_IN_IN	1.0
10	vit_large_patch14_clip_224:openai_ft_in1k	1.0
11	efficientnet_b1_imagenet_full	1.0
12	resnet50_imagenet_100_seed-0	1.0
13	mobilenet_v2_1_0_128	1.0
14	xception	1.0
15	mobilenet_v2_1_0_160	1.0
16	resnet50-moclr8deg	1.0
17	alexnet_training_seed_02	1.0
18	resnet-152_v2_pytorch	1.0
19	alexnet_training_seed_01	1.0
20	mobilenet_v2_1_0_192	1.0
21	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
22	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
23	resnet50_tutorial	1.0
24	yudixie_resnet50_object_class_0_240908	1.0
25	efficientnet-b7	1.0
26	resnet152_imagenet_full	1.0
27	resnet34_imagenet_full	1.0
28	vgg_16	1.0
29	cvt_cvt-13-384-in1k_4_LucyV4	1.0
30	efficientnet_b0_imagenet_full	1.0
31	cvt_cvt-21-224-in1k_4_LucyV4	.979
32	AdvProp_efficientnet-b8	.979
33	vonegrcnn_52e_full	.951
34	yudixie_resnet18_category_class_0_240719	.951
35	resnet152_ecoset_full	.951
36	pnasnet_large_pytorch	.951
37	antialiased-r50	.951
38	AdvProp_efficientnet-b4	.951
39	blt_vs	.951
40	AdvProp_efficientnet-b7	.888
41	BiT-S-R50x1	.888
42	yudixie_resnet18_distance_rotation_0_240719	.888
43	BiT-S-R50x3	.888
44	mobilenet_v2_1_0_224	.888
45	mobilenet_v2_0_5_224	.888
46	yudixie_resnet50_imagenet1kpret_0_240908	.862
47	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
48	yudixie_resnet18_distance_translation_0_240719	.862
49	focalnet_tiny_lrf_in1k	.862
50	AT_efficientnet-b2	.862
51	efficientnet_b2_imagenet_full	.862
52	AdvProp_efficientnet-b2	.862
53	inception_v1	.805
54	resnet18_ecoset_full	.805
55	mobilenet_v2_0_75_224	.805
56	yudixie_resnet18_object_class_0_240719	.805
57	resnext101_32x32d_wsl	.805
58	deit_small_imagenet_100_seed-0	.805
59	resnet50_robust_l2_eps1	.782
60	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
61	resnet18_imagenet_full	.782
62	BiT-S-R152x4	.782
63	resnet50-vicregl0p9	.782
64	artResNet18_1	.782
65	yudixie_resnet18_rotation_reg_0_240719	.730
66	inception_v3	.730
67	omnivore_swinB	.730
68	mobilenet_v2_0_75_192	.730
69	resnet50_imagenet_1_seed-0	.730
70	resnet50-VITO-8deg-cc	.709
71	omnivore_swinS	.709
72	convnext_tiny_sup	.709
73	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.709
74	efficientnet_b0	.709
75	yudixie_resnet18_translation_rotation_0_240719	.709
76	BiT-S-R101x1	.709
77	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.709
78	resnext101_32x48d_wsl	.709
79	resnet50-vitoimagevidnet8	.709
80	resnet_SIN_IN_FT_IN	.662
81	mobilenet_v2_1_3_224	.662
82	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.643
83	mobilenet_v2_0_5_192	.643
84	yudixie_resnet18_random_0_240719	.643
85	resnet_101_v1	.643
86	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.643
87	convnext_xlarge:fb_in22k_ft_in1k	.643
88	BiT-S-R152x2	.601
89	alexnet_training_seed_05	.601
90	resnet_152_v1	.583
91	VOneCORnet-S	.583
92	yudixie_resnet50_translation_reg_0_240908	.583
93	inception_v4	.583
94	alexnet_training_seed_08	.583
95	shufflenet_v2_x1_0	.583
96	BiT-S-R101x3	.583
97	densenet-169	.583
98	AdvProp_efficientnet-b6	.545
99	mobilenet_v2_1-4_224_pytorch	.529
100	resnet50-vicregl0p75	.529
101	yudixie_resnet50_distance_reg_0_240908	.529
102	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
103	mobilenet_v2_0_75_160	.529
104	vonegrcnn_47e	.529
105	mobilenet_v2_1_4_224	.529
106	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
107	vonegrcnn_62e_nobn	.529
108	resnet50-vicreg	.529
109	resnet-18_test_m	.529
110	yudixie_resnet18_distance_translation_rotation_0_240719	.529
111	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
112	alexnet_training_seed_04	.494
113	densenet-201	.480
114	resnet50-sup	.480
115	resnet_50_v1	.480
116	yudixie_resnet18_distance_reg_0_240719	.448
117	yudixie_resnet50_translation_rotation_0_240908	.448
118	resnet50_ecoset_full	.435
119	grcnn	.435
120	cvt_cvt-21-384-in1k_4_LucyV4	.435
121	nasnet_mobile	.435
122	yudixie_resnet50_category_class_0_240908	.435
123	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
124	convnext_small_imagenet_10_seed-0	.406
125	resnet_152_v2	.406
126	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
127	yudixie_resnet50_distance_rotation_0_240908	.395
128	resnet50_imagenet_10_seed-0	.369
129	custom_model_cv_18_dagger_408	.369
130	alexnet_training_seed_07	.369
131	yudixie_resnet50_random_0_240908	.358
132	resnet50-SIN	.358
133	yudixie_resnet50_rotation_reg_0_240908	.358
134	effnetb1_272x240	.358
135	briaai_rmbg_1_4	.334
136	vit_base_patch16_clip_224:openai_ft_in1k	.325
137	grcnn_109	.325
138	resnet50_robust_l2_eps3	.325
139	imagenet_l2_3_0	.325
140	deit_small_imagenet_full_seed-0	.325
141	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
142	convnext_small_imagenet_full_seed-0	.294
143	yudixie_resnet18_translation_reg_0_240719	.294
144	densenet-121	.294
145	Res2Net50_26w_4s	.294
146	deit_large_imagenet_full_seed-0	.275
147	convnext_base_imagenet_full_seed-0	.267
148	yolos_tiny	.267
149	convnext_tiny:in12k_ft_in1k	.267
150	resnet_50_v2	.267
151	resnet50_imagenet_full	.242
152	ReAlnet06_cornet	.242
153	resnet_101_v2	.242
154	yudixie_resnet50_distance_translation_0_240908	.242
155	resnet50-barlow	.242
156	deit_small_imagenet_1_seed-0	.242
157	ReAlnet06	.242
158	pnasnet_large	.242
159	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
160	ReAlnet02	.242
161	ReAlnet02_cornet	.242
162	alexnet_training_seed_03	.226
163	resnet101_imagenet_full	.199
164	voneresnet-50-non_stochastic	.199
165	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
166	convnext_large_imagenet_full_seed-0	.181
167	ReAlnet09_cornet	.164
168	nasnet_large	.164
169	resnet50-SIN_IN	.164
170	voneresnet-50	.164
171	cvt_cvt-13-224-in1k_4_LucyV4	.164
172	resnet-50-robust	.164
173	ReAlnet09	.164
174	yudixie_resnet50_distance_translation_rotation_0_240908	.164
175	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
176	resnet101_ecoset_full	.149
177	ReAlnet05_cornet	.135
178	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
179	ReAlnet05	.135
180	convnext_small_imagenet_1_seed-0	.126
181	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
182	vgg_19	.122
183	yudixie_resnet18_imagenet1kpret_0_240719	.111
184	voneresnet-50-robust	.111
185	convnext_small_imagenet_100_seed-0	.111
186	ReAlnet01	.083
187	ReAlnet_incorrect	.083
188	ReAlnet01_cornet	.083
189	resnext101_32x8d_wsl	.068
190	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
191	convnext_large:fb_in22k_ft_in1k	.068
192	ReAlnet03_cornet	.062
193	ReAlnet03	.062
194	ReAlnet10_cornet	.051
195	ReAlnet10	.051
196	ReAlnet08_cornet	.046
197	ReAlnet08	.046
198	resnet34_ecoset_full	.046
199	ReAlnet07_cornet	.042
200	ReAlnet07	.042
201	convnext_tiny_imagenet_full_seed-0	.034
202	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
203	ReAlnet04	.016
204	ReAlnet04_cornet	.016
205	hmax	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

0.81.

Note that scores are relative to this ceiling.

Data: Ferguson2024llh

Metric: value_delta