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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	aughost_fair_resnet18	1.0
15	alexnet_training_seed_01_fov16	1.0
16	alexnet_fov4	1.0
17	resnet_50_v1_spiking_l4a	1.0
18	xception	1.0
19	alexnet_training_seed_02	1.0
20	resnet50-moclr8deg	1.0
21	mobilenet_v2_1_0_160	1.0
22	resnet-152_v2_pytorch	1.0
23	yudixie_resnet50_object_class_0_240908	1.0
24	alexnet_training_seed_01	1.0
25	mobilenet_v2_1_0_192	1.0
26	efficientnet-b7	1.0
27	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
28	resnet50_tutorial	1.0
29	resnet152_imagenet_full	1.0
30	resnet34_imagenet_full	1.0
31	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
32	vit_base_patch14_dinov2-lvd142m	1.0
33	compact_resnet50_robust_V4	1.0
34	resnet_50_v1_spiking	1.0
35	vgg_16	1.0
36	efficientnet_b0_imagenet_full	1.0
37	cvt_cvt-13-384-in1k_4_LucyV4	1.0
38	AdvProp_efficientnet-b8	.979
39	cvt_cvt-21-224-in1k_4_LucyV4	.979
40	resnet50_st_wzc_seed7_2_323	.951
41	vonegrcnn_52e_full	.951
42	AdvProp_efficientnet-b4	.951
43	antialiased-r50	.951
44	blt_vs	.951
45	yudixie_resnet18_category_class_0_240719	.951
46	resnet152_ecoset_full	.951
47	pnasnet_large_pytorch	.951
48	resnet50_ewconplus_wzc_seed7_2_323	.888
49	resnet50_ewconplus_wzc_2_323	.888
50	alexnet_training_seed_01_fov4	.888
51	mobilenet_v2_1_0_224	.888
52	mobilenet_v2_0_5_224	.888
53	BiT-S-R50x1	.888
54	BiT-S-R50x3	.888
55	AdvProp_efficientnet-b7	.888
56	yudixie_resnet18_distance_rotation_0_240719	.888
57	yudixie_resnet50_imagenet1kpret_0_240908	.862
58	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
59	AT_efficientnet-b2	.862
60	AdvProp_efficientnet-b2	.862
61	yudixie_resnet18_distance_translation_0_240719	.862
62	efficientnet_b2_imagenet_full	.862
63	focalnet_tiny_lrf_in1k	.862
64	yudixie_wbh_object_class_scaling_0415_run_0	.805
65	predictive_coding_pc	.805
66	resnet18_fair	.805
67	resnet50_primary_visual_cortex	.805
68	mobilenet_v2_0_75_224	.805
69	inception_v1	.805
70	yudixie_resnet18_object_class_0_240719	.805
71	deit_small_imagenet_100_seed-0	.805
72	resnet18_ecoset_full	.805
73	alexnet	.805
74	resnext101_32x32d_wsl	.805
75	resnet50_st_wzc_seed3_2_323	.782
76	resnet50_ewconplus_wzc_seed5_2__323	.782
77	resnet50_ewconplus_wzc_seed4_2_323	.782
78	ReAlnet01_cornet_fov4	.782
79	resnet50_robust_l2_eps1	.782
80	resnet50-vicregl0p9	.782
81	BiT-S-R152x4	.782
82	artResNet18_1	.782
83	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
84	resnet18_imagenet_full	.782
85	ReAlnet01_cornet_fov16	.730
86	mobilenet_v2_0_75_192	.730
87	inception_v3	.730
88	omnivore_swinB	.730
89	yudixie_resnet18_rotation_reg_0_240719	.730
90	resnet50_imagenet_1_seed-0	.730
91	resnet50_st_wzc_noseed_2_323	.709
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	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.601
116	AlexNet_SIN_fov12	.601
117	compact_vgg19_IT	.601
118	alexnet_training_seed_05	.601
119	BiT-S-R152x2	.601
120	yudixie_wbh_object_class_scaling_0415_run_2	.583
121	deit3_base_patch16_224_fb_in1k	.583
122	vit_base_patch16_dinov3-lvd1689m	.583
123	AlexNet_SIN_fov4	.583
124	alexnet_training_seed_08	.583
125	resnet_152_v1	.583
126	inception_v4	.583
127	yudixie_resnet50_translation_reg_0_240908	.583
128	shufflenet_v2_x1_0	.583
129	VOneCORnet-S	.583
130	densenet-169	.583
131	BiT-S-R101x3	.583
132	yudixie_wbh_object_class_scaling_0415_run_1	.545
133	convnext_base_fb_in22k_ft_in1k	.545
134	AdvProp_efficientnet-b6	.545
135	ReAlnet01_cornet_fov12	.529
136	AlexNet_SIN	.529
137	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.529
138	yudixie_resnet50_distance_reg_0_240908	.529
139	mobilenet_v2_1_4_224	.529
140	mobilenet_v2_0_75_160	.529
141	vonegrcnn_62e_nobn	.529
142	resnet50-vicreg	.529
143	resnet-18_test_m	.529
144	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
145	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
146	resnet50-vicregl0p75	.529
147	vonegrcnn_47e	.529
148	yudixie_resnet18_distance_translation_rotation_0_240719	.529
149	mobilenet_v2_1-4_224_pytorch	.529
150	yudixie_wbh_object_class_scaling_0415_run_3	.494
151	alexnet_training_seed_04	.494
152	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
153	deit3_base_patch16_224_fb_in22k_ft_in1k	.480
154	resnet_50_v1	.480
155	densenet-201	.480
156	resnet50-sup	.480
157	resnet50_ewconplus_noseed_2_323	.448
158	yudixie_resnet50_translation_rotation_0_240908	.448
159	yudixie_resnet18_distance_reg_0_240719	.448
160	resnet50_ewconplus_wzc	.435
161	compact_resnet50_IT	.435
162	ReAlnet02_ALL	.435
163	yudixie_resnet50_category_class_0_240908	.435
164	nasnet_mobile	.435
165	grcnn	.435
166	cvt_cvt-21-384-in1k_4_LucyV4	.435
167	resnet50_ecoset_full	.435
168	resnet_152_v2	.406
169	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
170	convnext_small_imagenet_10_seed-0	.406
171	alexnet_fov12	.395
172	compact_cornets_V4	.395
173	compact_resnet50_V4	.395
174	ReAlnet04_ALL	.395
175	yudixie_resnet50_distance_rotation_0_240908	.395
176	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
177	resnet_50_v1_spiking_l4	.369
178	alexnet_training_seed_07	.369
179	resnet50_imagenet_10_seed-0	.369
180	custom_model_cv_18_dagger_408	.369
181	vit_base_patch14_reg4_dinov2-lvd142m	.358
182	yudixie_resnet50_random_0_240908	.358
183	yudixie_resnet50_rotation_reg_0_240908	.358
184	resnet50-SIN	.358
185	effnetb1_272x240	.358
186	compact_resnet50_robust_IT	.334
187	briaai_rmbg_1_4	.334
188	resnet50_st_wzc_2	.325
189	grcnn_109	.325
190	vit_base_patch16_clip_224:openai_ft_in1k	.325
191	imagenet_l2_3_0	.325
192	resnet50_robust_l2_eps3	.325
193	deit_small_imagenet_full_seed-0	.325
194	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
195	resnet50_st_wzc_seed5_2_323	.294
196	resnet50_ewconplus_wzc_seed6_2_323	.294
197	Res2Net50_26w_4s	.294
198	densenet-121	.294
199	yudixie_resnet18_translation_reg_0_240719	.294
200	convnext_small_imagenet_full_seed-0	.294
201	deit_large_imagenet_full_seed-0	.275
202	AlexNet_SIN_fov16	.267
203	yolos_tiny	.267
204	resnet_50_v2	.267
205	convnext_tiny:in12k_ft_in1k	.267
206	convnext_base_imagenet_full_seed-0	.267
207	pnasnet_large_halfPrecision	.242
208	ReAlnet10_ALL	.242
209	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
210	pnasnet_large	.242
211	ReAlnet06_cornet	.242
212	ReAlnet02_cornet	.242
213	resnet_101_v2	.242
214	yudixie_resnet50_distance_translation_0_240908	.242
215	ReAlnet06	.242
216	ReAlnet02	.242
217	resnet50-barlow	.242
218	deit_small_imagenet_1_seed-0	.242
219	resnet50_imagenet_full	.242
220	alexnet_training_seed_03	.226
221	deepeisnn_ei_cifar10_vgg19	.220
222	ReAlnet06_ALL	.220
223	resnet_50_v1_spiking_l3	.205
224	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
225	resnet101_imagenet_full	.199
226	voneresnet-50-non_stochastic	.199
227	deepeisnn_ei_imagenet_resnet18	.181
228	deepeisnn_ei_cifar10_resnet18	.181
229	resnet50_st_wzc_seed4_2_323	.181
230	ReAlnet09_ALL	.181
231	ReAlnet07_ALL	.181
232	convnext_large_imagenet_full_seed-0	.181
233	yudixie_resnet50_distance_translation_rotation_0_240908	.164
234	ReAlnet09_cornet	.164
235	nasnet_large	.164
236	ReAlnet09	.164
237	voneresnet-50	.164
238	resnet50-SIN_IN	.164
239	cvt_cvt-13-224-in1k_4_LucyV4	.164
240	resnet-50-robust	.164
241	convnext_base_fb_in1k_gram_aligned_dinov3	.149
242	resnet101_ecoset_full	.149
243	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
244	compact_cornets_IT	.135
245	ReAlnet05_cornet	.135
246	ReAlnet05	.135
247	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
248	convnext_small_imagenet_1_seed-0	.126
249	vgg_19	.122
250	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
251	voneresnet-50-robust	.111
252	convnext_small_imagenet_100_seed-0	.111
253	yudixie_resnet18_imagenet1kpret_0_240719	.111
254	compact_vgg19_V4	.101
255	ReAlnet08_ALL	.101
256	ReAlnet05_ALL	.101
257	convnext_base_fb_in1k	.091
258	ReAlnet01_cornet	.083
259	ReAlnet01	.083
260	ReAlnet03_ALL	.075
261	cv_18_dagger_408_pretrained	.068
262	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
263	convnext_large:fb_in22k_ft_in1k	.068
264	resnext101_32x8d_wsl	.068
265	ReAlnet03_cornet	.062
266	ReAlnet03	.062
267	ReAlnet10_cornet	.051
268	ReAlnet10	.051
269	ReAlnet08_cornet	.046
270	ReAlnet08	.046
271	resnet34_ecoset_full	.046
272	ReAlnet07_cornet	.042
273	ReAlnet07	.042
274	convnext_tiny_imagenet_full_seed-0	.034
275	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
276	ReAlnet04_cornet	.016
277	ReAlnet04	.016
278	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
279	resnet50_st_wzc_2_323
280	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