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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	deit_base_imagenet_full_seed-0	1.0
3	alexnet_training_seed_06	1.0
4	vit_large_patch14_clip_224:openai_ft_in1k	1.0
5	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
6	mobilenet_v2_1_0_128	1.0
7	deit_small_imagenet_10_seed-0	1.0
8	resnet50_imagenet_100_seed-0	1.0
9	ViT_L_32_imagenet1k	1.0
10	alexnet_training_seed_10	1.0
11	efficientnet_b1_imagenet_full	1.0
12	resnet50-SIN_IN_IN	1.0
13	convnext_femto_ols:d1_in1k	1.0
14	alexnet_training_seed_02	1.0
15	alexnet_fov4	1.0
16	resnet_50_v1_spiking_l4a	1.0
17	mobilenet_v2_1_0_160	1.0
18	xception	1.0
19	resnet50-moclr8deg	1.0
20	alexnet_training_seed_01_fov16	1.0
21	resnet-152_v2_pytorch	1.0
22	resnet152_imagenet_full	1.0
23	resnet34_imagenet_full	1.0
24	yudixie_resnet50_object_class_0_240908	1.0
25	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
26	resnet50_tutorial	1.0
27	mobilenet_v2_1_0_192	1.0
28	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
29	alexnet_training_seed_01	1.0
30	efficientnet-b7	1.0
31	resnet_50_v1_spiking	1.0
32	cvt_cvt-13-384-in1k_4_LucyV4	1.0
33	compact_resnet50_robust_V4	1.0
34	efficientnet_b0_imagenet_full	1.0
35	vgg_16	1.0
36	cvt_cvt-21-224-in1k_4_LucyV4	.979
37	AdvProp_efficientnet-b8	.979
38	blt_vs	.951
39	resnet152_ecoset_full	.951
40	pnasnet_large_pytorch	.951
41	yudixie_resnet18_category_class_0_240719	.951
42	antialiased-r50	.951
43	AdvProp_efficientnet-b4	.951
44	vonegrcnn_52e_full	.951
45	mobilenet_v2_0_5_224	.888
46	yudixie_resnet18_distance_rotation_0_240719	.888
47	mobilenet_v2_1_0_224	.888
48	alexnet_training_seed_01_fov4	.888
49	AdvProp_efficientnet-b7	.888
50	BiT-S-R50x3	.888
51	BiT-S-R50x1	.888
52	yudixie_resnet50_imagenet1kpret_0_240908	.862
53	efficientnet_b2_imagenet_full	.862
54	focalnet_tiny_lrf_in1k	.862
55	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
56	yudixie_resnet18_distance_translation_0_240719	.862
57	AdvProp_efficientnet-b2	.862
58	AT_efficientnet-b2	.862
59	deit_small_imagenet_100_seed-0	.805
60	mobilenet_v2_0_75_224	.805
61	resnext101_32x32d_wsl	.805
62	alexnet	.805
63	resnet18_ecoset_full	.805
64	yudixie_resnet18_object_class_0_240719	.805
65	inception_v1	.805
66	resnet50_primary_visual_cortex	.805
67	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
68	resnet18_imagenet_full	.782
69	ReAlnet01_cornet_fov4	.782
70	resnet50_robust_l2_eps1	.782
71	artResNet18_1	.782
72	BiT-S-R152x4	.782
73	resnet50-vicregl0p9	.782
74	inception_v3	.730
75	mobilenet_v2_0_75_192	.730
76	resnet50_imagenet_1_seed-0	.730
77	yudixie_resnet18_rotation_reg_0_240719	.730
78	omnivore_swinB	.730
79	ReAlnet01_cornet_fov16	.730
80	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.709
81	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.709
82	resnext101_32x48d_wsl	.709
83	yudixie_resnet18_translation_rotation_0_240719	.709
84	resnet50-VITO-8deg-cc	.709
85	efficientnet_b0	.709
86	resnet50-vitoimagevidnet8	.709
87	omnivore_swinS	.709
88	convnext_tiny_sup	.709
89	BiT-S-R101x1	.709
90	mobilenet_v2_1_3_224	.662
91	resnet_SIN_IN_FT_IN	.662
92	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.643
93	convnext_xlarge:fb_in22k_ft_in1k	.643
94	mobilenet_v2_0_5_192	.643
95	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.643
96	alexnet_fov16	.643
97	yudixie_resnet18_random_0_240719	.643
98	ReAlnet01_ALL	.643
99	alexnet_training_seed_01_fov12	.643
100	resnet_101_v1	.643
101	alexnet_training_seed_05	.601
102	compact_vgg19_IT	.601
103	AlexNet_SIN_fov12	.601
104	BiT-S-R152x2	.601
105	resnet_152_v1	.583
106	alexnet_training_seed_08	.583
107	inception_v4	.583
108	yudixie_resnet50_translation_reg_0_240908	.583
109	shufflenet_v2_x1_0	.583
110	AlexNet_SIN_fov4	.583
111	VOneCORnet-S	.583
112	BiT-S-R101x3	.583
113	densenet-169	.583
114	AdvProp_efficientnet-b6	.545
115	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.529
116	AlexNet_SIN	.529
117	yudixie_resnet50_distance_reg_0_240908	.529
118	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
119	mobilenet_v2_0_75_160	.529
120	mobilenet_v2_1-4_224_pytorch	.529
121	ReAlnet01_cornet_fov12	.529
122	resnet-18_test_m	.529
123	yudixie_resnet18_distance_translation_rotation_0_240719	.529
124	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
125	resnet50-vicreg	.529
126	vonegrcnn_62e_nobn	.529
127	mobilenet_v2_1_4_224	.529
128	vonegrcnn_47e	.529
129	resnet50-vicregl0p75	.529
130	alexnet_training_seed_04	.494
131	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
132	densenet-201	.480
133	resnet_50_v1	.480
134	resnet50-sup	.480
135	yudixie_resnet18_distance_reg_0_240719	.448
136	yudixie_resnet50_translation_rotation_0_240908	.448
137	cvt_cvt-21-384-in1k_4_LucyV4	.435
138	resnet50_ewconplus_wzc	.435
139	yudixie_resnet50_category_class_0_240908	.435
140	resnet50_ecoset_full	.435
141	compact_resnet50_IT	.435
142	ReAlnet02_ALL	.435
143	nasnet_mobile	.435
144	grcnn	.435
145	convnext_small_imagenet_10_seed-0	.406
146	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
147	resnet_152_v2	.406
148	alexnet_fov12	.395
149	compact_resnet50_V4	.395
150	yudixie_resnet50_distance_rotation_0_240908	.395
151	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
152	compact_cornets_V4	.395
153	ReAlnet04_ALL	.395
154	resnet50_imagenet_10_seed-0	.369
155	resnet_50_v1_spiking_l4	.369
156	custom_model_cv_18_dagger_408	.369
157	alexnet_training_seed_07	.369
158	yudixie_resnet50_random_0_240908	.358
159	resnet50-SIN	.358
160	yudixie_resnet50_rotation_reg_0_240908	.358
161	effnetb1_272x240	.358
162	briaai_rmbg_1_4	.334
163	compact_resnet50_robust_IT	.334
164	deit_small_imagenet_full_seed-0	.325
165	vit_base_patch16_clip_224:openai_ft_in1k	.325
166	grcnn_109	.325
167	resnet50_robust_l2_eps3	.325
168	imagenet_l2_3_0	.325
169	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
170	convnext_small_imagenet_full_seed-0	.294
171	Res2Net50_26w_4s	.294
172	yudixie_resnet18_translation_reg_0_240719	.294
173	densenet-121	.294
174	deit_large_imagenet_full_seed-0	.275
175	convnext_tiny:in12k_ft_in1k	.267
176	convnext_base_imagenet_full_seed-0	.267
177	yolos_tiny	.267
178	AlexNet_SIN_fov16	.267
179	resnet_50_v2	.267
180	ReAlnet06	.242
181	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
182	ReAlnet02_cornet	.242
183	resnet50_imagenet_full	.242
184	deit_small_imagenet_1_seed-0	.242
185	yudixie_resnet50_distance_translation_0_240908	.242
186	ReAlnet06_cornet	.242
187	resnet50-barlow	.242
188	pnasnet_large	.242
189	resnet_101_v2	.242
190	ReAlnet02	.242
191	ReAlnet10_ALL	.242
192	alexnet_training_seed_03	.226
193	ReAlnet06_ALL	.220
194	resnet_50_v1_spiking_l3	.205
195	resnet101_imagenet_full	.199
196	voneresnet-50-non_stochastic	.199
197	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
198	convnext_large_imagenet_full_seed-0	.181
199	ReAlnet07_ALL	.181
200	ReAlnet09_ALL	.181
201	yudixie_resnet50_distance_translation_rotation_0_240908	.164
202	ReAlnet09	.164
203	resnet-50-robust	.164
204	cvt_cvt-13-224-in1k_4_LucyV4	.164
205	resnet50-SIN_IN	.164
206	nasnet_large	.164
207	voneresnet-50	.164
208	ReAlnet09_cornet	.164
209	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
210	resnet101_ecoset_full	.149
211	ReAlnet05	.135
212	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
213	ReAlnet05_cornet	.135
214	compact_cornets_IT	.135
215	convnext_small_imagenet_1_seed-0	.126
216	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
217	vgg_19	.122
218	convnext_small_imagenet_100_seed-0	.111
219	yudixie_resnet18_imagenet1kpret_0_240719	.111
220	voneresnet-50-robust	.111
221	compact_vgg19_V4	.101
222	ReAlnet05_ALL	.101
223	ReAlnet08_ALL	.101
224	ReAlnet01_cornet	.083
225	ReAlnet01	.083
226	ReAlnet03_ALL	.075
227	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
228	cv_18_dagger_408_pretrained	.068
229	resnext101_32x8d_wsl	.068
230	convnext_large:fb_in22k_ft_in1k	.068
231	ReAlnet03	.062
232	ReAlnet03_cornet	.062
233	ReAlnet10	.051
234	ReAlnet10_cornet	.051
235	ReAlnet08	.046
236	resnet34_ecoset_full	.046
237	ReAlnet08_cornet	.046
238	ReAlnet07	.042
239	ReAlnet07_cornet	.042
240	convnext_tiny_imagenet_full_seed-0	.034
241	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
242	ReAlnet04_cornet	.016
243	ReAlnet04	.016
244	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

0.81.

Note that scores are relative to this ceiling.

Data: Ferguson2024llh

Metric: value_delta