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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_10	1.0
2	alexnet_training_seed_06	1.0
3	alexnet_training_seed_09	1.0
4	mobilenet_v2_1_0_128	1.0
5	resnet50-SIN_IN_IN	1.0
6	vit_large_patch14_clip_224:openai_ft_in1k	1.0
7	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
8	convnext_femto_ols:d1_in1k	1.0
9	deit_small_imagenet_10_seed-0	1.0
10	deit_base_imagenet_full_seed-0	1.0
11	efficientnet_b1_imagenet_full	1.0
12	resnet50_imagenet_100_seed-0	1.0
13	ViT_L_32_imagenet1k	1.0
14	dinov2_vitl14_reg_lc	1.0
15	aughost_fair_resnet18	1.0
16	alexnet_training_seed_01_fov16	1.0
17	alexnet_fov4	1.0
18	resnet_50_v1_spiking_l4a	1.0
19	xception	1.0
20	alexnet_training_seed_02	1.0
21	resnet50-moclr8deg	1.0
22	mobilenet_v2_1_0_160	1.0
23	resnet-152_v2_pytorch	1.0
24	dinov2_vitl14_lc_res336	1.0
25	yudixie_resnet50_object_class_0_240908	1.0
26	alexnet_training_seed_01	1.0
27	mobilenet_v2_1_0_192	1.0
28	efficientnet-b7	1.0
29	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
30	resnet50_tutorial	1.0
31	resnet152_imagenet_full	1.0
32	resnet34_imagenet_full	1.0
33	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
34	dinov2_vitg14_reg_lc	1.0
35	vit_base_patch14_dinov2-lvd142m	1.0
36	compact_resnet50_robust_V4	1.0
37	resnet_50_v1_spiking	1.0
38	vgg_16	1.0
39	efficientnet_b0_imagenet_full	1.0
40	cvt_cvt-13-384-in1k_4_LucyV4	1.0
41	AdvProp_efficientnet-b8	.979
42	cvt_cvt-21-224-in1k_4_LucyV4	.979
43	resnet50_st_wzc_seed7_2_323	.951
44	vonegrcnn_52e_full	.951
45	AdvProp_efficientnet-b4	.951
46	antialiased-r50	.951
47	blt_vs	.951
48	yudixie_resnet18_category_class_0_240719	.951
49	resnet152_ecoset_full	.951
50	pnasnet_large_pytorch	.951
51	alexnet_training_seed_01_fov4	.888
52	mobilenet_v2_1_0_224	.888
53	mobilenet_v2_0_5_224	.888
54	BiT-S-R50x1	.888
55	BiT-S-R50x3	.888
56	AdvProp_efficientnet-b7	.888
57	yudixie_resnet18_distance_rotation_0_240719	.888
58	yudixie_resnet50_imagenet1kpret_0_240908	.862
59	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
60	AT_efficientnet-b2	.862
61	AdvProp_efficientnet-b2	.862
62	yudixie_resnet18_distance_translation_0_240719	.862
63	efficientnet_b2_imagenet_full	.862
64	focalnet_tiny_lrf_in1k	.862
65	yudixie_wbh_object_class_scaling_0415_run_0	.805
66	predictive_coding_pc	.805
67	resnet18_fair	.805
68	resnet50_primary_visual_cortex	.805
69	mobilenet_v2_0_75_224	.805
70	inception_v1	.805
71	yudixie_resnet18_object_class_0_240719	.805
72	deit_small_imagenet_100_seed-0	.805
73	resnet18_ecoset_full	.805
74	alexnet	.805
75	resnext101_32x32d_wsl	.805
76	resnet50_st_wzc_seed3_2_323	.782
77	resnet50_ewconplus_wzc_seed5_2__323	.782
78	ReAlnet01_cornet_fov4	.782
79	vit_huge_clip336_laion	.782
80	resnet50_robust_l2_eps1	.782
81	resnet50-vicregl0p9	.782
82	BiT-S-R152x4	.782
83	artResNet18_1	.782
84	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
85	resnet18_imagenet_full	.782
86	ReAlnet01_cornet_fov16	.730
87	mobilenet_v2_0_75_192	.730
88	inception_v3	.730
89	omnivore_swinB	.730
90	yudixie_resnet18_rotation_reg_0_240719	.730
91	resnet50_imagenet_1_seed-0	.730
92	resnet50-vitoimagevidnet8	.709
93	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.709
94	omnivore_swinS	.709
95	efficientnet_b0	.709
96	resnet50-VITO-8deg-cc	.709
97	BiT-S-R101x1	.709
98	convnext_tiny_sup	.709
99	yudixie_resnet18_translation_rotation_0_240719	.709
100	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.709
101	resnext101_32x48d_wsl	.709
102	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.662
103	mobilenet_v2_1_3_224	.662
104	resnet_SIN_IN_FT_IN	.662
105	yudixie_wbh_object_class_scaling_0415_imagenet	.643
106	alexnet_training_seed_01_fov12	.643
107	alexnet_fov16	.643
108	ReAlnet01_ALL	.643
109	resnet_101_v1	.643
110	mobilenet_v2_0_5_192	.643
111	convnext_xlarge:fb_in22k_ft_in1k	.643
112	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.643
113	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.643
114	yudixie_resnet18_random_0_240719	.643
115	convnext_large_in22k_supervised	.601
116	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.601
117	AlexNet_SIN_fov12	.601
118	compact_vgg19_IT	.601
119	alexnet_training_seed_05	.601
120	BiT-S-R152x2	.601
121	yudixie_wbh_object_class_scaling_0415_run_2	.583
122	deit3_base_patch16_224_fb_in1k	.583
123	vit_base_patch16_dinov3-lvd1689m	.583
124	AlexNet_SIN_fov4	.583
125	alexnet_training_seed_08	.583
126	resnet_152_v1	.583
127	inception_v4	.583
128	yudixie_resnet50_translation_reg_0_240908	.583
129	shufflenet_v2_x1_0	.583
130	VOneCORnet-S	.583
131	densenet-169	.583
132	BiT-S-R101x3	.583
133	yudixie_wbh_object_class_scaling_0415_run_1	.545
134	convnext_base_fb_in22k_ft_in1k	.545
135	AdvProp_efficientnet-b6	.545
136	ReAlnet01_cornet_fov12	.529
137	AlexNet_SIN	.529
138	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.529
139	yudixie_resnet50_distance_reg_0_240908	.529
140	mobilenet_v2_1_4_224	.529
141	mobilenet_v2_0_75_160	.529
142	vonegrcnn_62e_nobn	.529
143	resnet50-vicreg	.529
144	resnet-18_test_m	.529
145	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
146	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
147	resnet50-vicregl0p75	.529
148	vonegrcnn_47e	.529
149	yudixie_resnet18_distance_translation_rotation_0_240719	.529
150	mobilenet_v2_1-4_224_pytorch	.529
151	yudixie_wbh_object_class_scaling_0415_run_3	.494
152	alexnet_training_seed_04	.494
153	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
154	dinov2_vitl14_reg_lc_featread	.480
155	deit3_base_patch16_224_fb_in22k_ft_in1k	.480
156	resnet_50_v1	.480
157	densenet-201	.480
158	resnet50-sup	.480
159	yudixie_resnet50_translation_rotation_0_240908	.448
160	yudixie_resnet18_distance_reg_0_240719	.448
161	resnet50_ewconplus_wzc	.435
162	compact_resnet50_IT	.435
163	ReAlnet02_ALL	.435
164	yudixie_resnet50_category_class_0_240908	.435
165	nasnet_mobile	.435
166	grcnn	.435
167	cvt_cvt-21-384-in1k_4_LucyV4	.435
168	resnet50_ecoset_full	.435
169	resnet_152_v2	.406
170	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
171	convnext_small_imagenet_10_seed-0	.406
172	alexnet_fov12	.395
173	compact_cornets_V4	.395
174	compact_resnet50_V4	.395
175	ReAlnet04_ALL	.395
176	convnext_xxlarge_clip	.395
177	yudixie_resnet50_distance_rotation_0_240908	.395
178	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
179	resnet_50_v1_spiking_l4	.369
180	alexnet_training_seed_07	.369
181	resnet50_imagenet_10_seed-0	.369
182	custom_model_cv_18_dagger_408	.369
183	eva02_large_in22k	.358
184	vit_base_patch14_reg4_dinov2-lvd142m	.358
185	yudixie_resnet50_random_0_240908	.358
186	yudixie_resnet50_rotation_reg_0_240908	.358
187	resnet50-SIN	.358
188	effnetb1_272x240	.358
189	compact_resnet50_robust_IT	.334
190	briaai_rmbg_1_4	.334
191	resnet50_st_wzc_2	.325
192	grcnn_109	.325
193	vit_base_patch16_clip_224:openai_ft_in1k	.325
194	imagenet_l2_3_0	.325
195	resnet50_robust_l2_eps3	.325
196	deit_small_imagenet_full_seed-0	.325
197	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
198	convnext_large_clip_laion2b_finelayers	.294
199	resnet50_ewconplus_wzc_seed6_2_323	.294
200	Res2Net50_26w_4s	.294
201	densenet-121	.294
202	yudixie_resnet18_translation_reg_0_240719	.294
203	convnext_small_imagenet_full_seed-0	.294
204	deit_large_imagenet_full_seed-0	.275
205	AlexNet_SIN_fov16	.267
206	yolos_tiny	.267
207	resnet_50_v2	.267
208	convnext_tiny:in12k_ft_in1k	.267
209	convnext_base_imagenet_full_seed-0	.267
210	dinov2_vitg14_lc	.242
211	pnasnet_large_halfPrecision	.242
212	ReAlnet10_ALL	.242
213	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
214	pnasnet_large	.242
215	ReAlnet06_cornet	.242
216	ReAlnet02_cornet	.242
217	resnet_101_v2	.242
218	yudixie_resnet50_distance_translation_0_240908	.242
219	ReAlnet06	.242
220	ReAlnet02	.242
221	resnet50-barlow	.242
222	deit_small_imagenet_1_seed-0	.242
223	resnet50_imagenet_full	.242
224	alexnet_training_seed_03	.226
225	deepeisnn_ei_cifar10_vgg19	.220
226	ReAlnet06_ALL	.220
227	resnet_50_v1_spiking_l3	.205
228	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
229	resnet101_imagenet_full	.199
230	voneresnet-50-non_stochastic	.199
231	deepeisnn_ei_imagenet_resnet18	.181
232	deepeisnn_ei_cifar10_resnet18	.181
233	ReAlnet09_ALL	.181
234	ReAlnet07_ALL	.181
235	convnext_large_imagenet_full_seed-0	.181
236	yudixie_resnet50_distance_translation_rotation_0_240908	.164
237	ReAlnet09_cornet	.164
238	nasnet_large	.164
239	ReAlnet09	.164
240	voneresnet-50	.164
241	resnet50-SIN_IN	.164
242	cvt_cvt-13-224-in1k_4_LucyV4	.164
243	resnet-50-robust	.164
244	convnext_base_fb_in1k_gram_aligned_dinov3	.149
245	resnet101_ecoset_full	.149
246	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
247	compact_cornets_IT	.135
248	ReAlnet05_cornet	.135
249	ReAlnet05	.135
250	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
251	convnext_small_imagenet_1_seed-0	.126
252	vgg_19	.122
253	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
254	voneresnet-50-robust	.111
255	convnext_small_imagenet_100_seed-0	.111
256	yudixie_resnet18_imagenet1kpret_0_240719	.111
257	compact_vgg19_V4	.101
258	ReAlnet08_ALL	.101
259	ReAlnet05_ALL	.101
260	convnext_base_fb_in1k	.091
261	ReAlnet01_cornet	.083
262	ReAlnet01	.083
263	ReAlnet03_ALL	.075
264	cv_18_dagger_408_pretrained	.068
265	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
266	convnext_large:fb_in22k_ft_in1k	.068
267	resnext101_32x8d_wsl	.068
268	ReAlnet03_cornet	.062
269	ReAlnet03	.062
270	ReAlnet10_cornet	.051
271	ReAlnet10	.051
272	ReAlnet08_cornet	.046
273	ReAlnet08	.046
274	resnet34_ecoset_full	.046
275	ReAlnet07_cornet	.042
276	ReAlnet07	.042
277	convnext_tiny_imagenet_full_seed-0	.034
278	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
279	resnet50_hvs_wzc	.023
280	ReAlnet04_cornet	.016
281	ReAlnet04	.016
282	dinov2_vitl14_lc
283	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
284	vit_large_clip336_openai
285	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