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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024gray_easy-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	mehrer2020_alexnet_training_seed_03	1.0
2	mehrer2020_alexnet_training_seed_01	1.0
3	regnety_032	1.0
4	convnext_large_in22k_supervised	1.0
5	resnet50_robust_l2_eps1	1.0
6	convnext_xxlarge_clip	1.0
7	resnet_101_v2	1.0
8	densenet-121	1.0
9	BiT-S-R50x3	1.0
10	custom_model_cv_18_dagger_408	1.0
11	convnext_large_clip_laion2b_finelayers	.973
12	convnext_base_fb_in22k_ft_in1k	.973
13	mobilenet_v2_1_3_224	.973
14	yudixie_resnet50_translation_rotation_0_240908	.973
15	resnet50-vitoimagevidnet8	.973
16	resnet50-VITO-8deg-cc	.973
17	deepeisnn_ei_cifar10_resnet18	.932
18	resnet_50_v1_spiking	.932
19	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.882
20	cv_18_dagger_408_pretrained	.882
21	nasnet_large	.882
22	resnet50-moclr8deg	.882
23	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.882
24	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.882
25	BiT-S-R152x2	.882
26	deit_small_imagenet_full_seed-0	.882
27	resnet152_imagenet_full	.882
28	alexnet	.882
29	vit_huge_clip336_laion	.845
30	vit_large_clip336_openai	.845
31	dinov2_vitl14_reg_lc_featread	.845
32	dinov2_vitl14_lc_res336	.845
33	dinov2_vitl14_reg_lc	.845
34	eva02_large_in22k	.845
35	dinov2_vitg14_reg_lc	.845
36	dinov2_vitg14_lc	.845
37	dinov2_vitl14_lc	.845
38	deit3_base_patch16_224_fb_in1k	.845
39	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.845
40	vit_base_patch16_dinov3-lvd1689m	.845
41	vit_base_patch14_reg4_dinov2-lvd142m	.845
42	vit_base_patch14_dinov2-lvd142m	.845
43	compact_resnet50_V4	.845
44	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.845
45	vit_large_patch14_clip_336:laion2b_ft_in1k	.845
46	vit_large_patch14_clip_224:openai_ft_in1k	.845
47	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.845
48	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.845
49	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.845
50	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.845
51	vit_relpos_base_patch16_clsgap_224:sw_in1k	.845
52	vit_large_patch14_clip_224:laion2b_ft_in1k	.845
53	vit_base_patch16_clip_224:openai_ft_in1k	.845
54	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.845
55	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.845
56	convnext_large:fb_in22k_ft_in1k	.845
57	BiT-S-R152x4	.845
58	AdvProp_efficientnet-b8	.845
59	AdvProp_efficientnet-b7	.845
60	deit_large_imagenet_full_seed-0	.845
61	deit_base_imagenet_full_seed-0	.845
62	resnet101_ecoset_full	.845
63	cvt_cvt-21-384-in1k_4_LucyV4	.845
64	cvt_cvt-13-384-in1k_4_LucyV4	.845
65	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.845
66	ViT_L_32_imagenet1k	.845
67	compact_vgg19_V4	.800
68	compact_resnet50_IT	.800
69	nasnet_mobile	.800
70	BiT-S-R101x3	.800
71	gabor_filter_mean_abs_4x4_v2	.767
72	AlexNet_SIN_fov12	.767
73	vonegrcnn_62e_nobn	.767
74	grcnn	.767
75	densenet-169	.767
76	mehrer2020_alexnet_training_seed_02	.725
77	mehrer2020_alexnet_training_seed_01_fov12	.725
78	alexnet_training_seed_01_fov4	.725
79	resnet_152_v1	.725
80	omnivore_swinS	.725
81	convnext_xlarge:fb_in22k_ft_in1k	.725
82	yudixie_resnet18_translation_reg_0_240719	.725
83	mobilenet_v2_1_0_128	.695
84	convnext_tiny:in12k_ft_in1k	.695
85	AdvProp_efficientnet-b6	.695
86	resnet152_ecoset_full	.695
87	resnext101_32x16d_wsl	.658
88	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.658
89	yudixie_resnet50_random_0_240908	.630
90	yudixie_resnet18_distance_translation_0_240719	.630
91	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.630
92	resnet-50-robust	.630
93	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.630
94	deit_small_imagenet_100_seed-0	.596
95	cvt_cvt-13-224-in1k_4_LucyV4	.596
96	resnet101_imagenet_full	.596
97	yolos_tiny	.572
98	resnet50_robust_l2_eps3	.572
99	imagenet_l2_3_0	.572
100	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.572
101	alexnet_fov12	.541
102	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.541
103	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.541
104	convnext_base:clip_laiona_augreg_ft_in1k_384	.541
105	pnasnet_large_halfPrecision	.518
106	mobilenet_v2_1_4_224	.518
107	pnasnet_large	.518
108	resnet50-barlow	.518
109	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.518
110	mobilenet_v2_1-4_224_pytorch	.518
111	focalnet_tiny_lrf_in1k	.518
112	resnet-152_v2_pytorch	.518
113	compact_cornets_IT	.490
114	alexnet_training_seed_01	.490
115	resnet50-vicregl0p75	.490
116	mehrer2020_alexnet_training_seed_08	.470
117	mehrer2020_alexnet_training_seed_07	.470
118	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.470
119	resnet_101_v1	.470
120	BiT-S-R50x1	.470
121	BiT-S-R101x1	.470
122	cvt_cvt-21-224-in1k_4_LucyV4	.470
123	resnet50_ecoset_full	.470
124	resnet34_ecoset_full	.470
125	resnet50_imagenet_full	.470
126	effnetb1_272x240	.470
127	compact_vgg19_IT	.445
128	alexnet_fov16	.445
129	alexnet_training_seed_10	.445
130	resnext101_32x8d_wsl	.445
131	mehrer2020_alexnet_training_seed_09	.426
132	AlexNet_SIN_fov16	.426
133	ReAlnet10_cornet	.426
134	ReAlnet09_cornet	.426
135	ReAlnet10	.426
136	ReAlnet09	.426
137	resnet50-vicreg	.426
138	blt_vs	.426
139	yudixie_resnet18_random_0_240719	.426
140	pnasnet_large_pytorch	.426
141	mehrer2020_alexnet_training_seed_01_fov16	.403
142	deepeisnn_ei_cifar10_vgg19	.403
143	yudixie_wbh_object_class_scaling_0415_run_2	.403
144	resnext101_32x48d_wsl	.403
145	resnext101_32x32d_wsl	.403
146	mehrer2020_alexnet_training_seed_10	.387
147	pr1_stl10_disentangled_alpha04	.387
148	resnet_50_v1_spiking_l4	.387
149	mobilenet_v2_1_0_192	.387
150	ReAlnet07_ALL	.351
151	resnet_SIN_IN_FT_IN	.351
152	gabor_filter_entropy_4x4	.332
153	ReAlnet01_cornet_fov16	.332
154	xception	.332
155	alexnet_training_seed_07	.332
156	alexnet_training_seed_09	.332
157	mehrer2020_alexnet_training_seed_06	.318
158	ReAlnet01_cornet_fov12	.318
159	ReAlnet07_cornet	.318
160	inception_v3	.318
161	ReAlnet07	.318
162	voneresnet-50-robust	.318
163	convnext_small_imagenet_1_seed-0	.318
164	deepeisnn_ei_imagenet_resnet18	.301
165	compact_resnet50_robust_V4	.301
166	AlexNet_SIN	.288
167	yudixie_resnet50_distance_rotation_0_240908	.288
168	vonegrcnn_52e_full	.288
169	antialiased-r50	.288
170	artResNet18_1	.288
171	yudixie_resnet18_distance_reg_0_240719	.288
172	yudixie_resnet18_rotation_reg_0_240719	.288
173	ReAlnet01_ALL	.261
174	resnet_50_v1_spiking_l3	.261
175	ReAlnet05_cornet	.261
176	ReAlnet05	.261
177	yudixie_resnet18_distance_translation_rotation_0_240719	.261
178	alexnet_training_seed_02	.247
179	omnivore_swinB	.247
180	mehrer2020_alexnet_training_seed_04	.237
181	yudixie_wbh_object_class_scaling_0415_imagenet	.237
182	ReAlnet10_ALL	.237
183	densenet-201	.237
184	efficientnet_b0	.237
185	convnext_large_imagenet_full_seed-0	.237
186	resnet50_imagenet_100_seed-0	.237
187	resnet50_imagenet_1_seed-0	.237
188	gabor_filter_entropy_4x4_v2	.224
189	eicircuit_resnet18_bn_20260919	.215
190	seresnext50_32x4d	.215
191	yudixie_resnet50_rotation_reg_0_240908	.215
192	vonegrcnn_47e	.215
193	efficientnet_b2_imagenet_full	.215
194	resnet34_imagenet_full	.215
195	alexnet_training_seed_01_fov16	.203
196	mehrer2020_alexnet_training_seed_01_fov4	.195
197	resnet50_st_wzc_seed3_2_323	.195
198	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.195
199	ReAlnet02_ALL	.195
200	resnet_50_v2	.195
201	convnext_femto_ols:d1_in1k	.195
202	yudixie_wbh_object_class_scaling_0415_run_0	.184
203	compact_resnet50_robust_IT	.184
204	alexnet_training_seed_05	.184
205	ReAlnet03_ALL	.177
206	AlexNet_SIN_fov4	.177
207	mobilenet_v2_0_75_160	.177
208	mobilenet_v2_0_5_224	.177
209	efficientnet-b7	.177
210	mehrer2020_alexnet_training_seed_05	.160
211	resnet50_primary_visual_cortex	.160
212	ReAlnet01_cornet_fov4	.160
213	alexnet_fov4	.160
214	ReAlnet01_cornet	.160
215	resnet_152_v2	.160
216	grcnn_109	.160
217	ReAlnet01	.160
218	convnext_small_imagenet_full_seed-0	.160
219	resnet18_imagenet_full	.160
220	compact_cornets_V4	.152
221	alexnet_training_seed_03	.152
222	deit_small_imagenet_10_seed-0	.152
223	resnet18_fair	.145
224	ReAlnet02_cornet	.145
225	ReAlnet02	.145
226	resnet50-vicregl0p9	.145
227	gabor_filter_entropy_4x4_v2_forcedCosine	.138
228	yudixie_wbh_object_class_scaling_0415_run_1	.138
229	hmax	.138
230	ReAlnet04_cornet	.132
231	ReAlnet04	.132
232	alexnet_training_seed_08	.125
233	ReAlnet04_ALL	.120
234	resnet_50_v1_spiking_l4a	.120
235	yudixie_resnet50_category_class_0_240908	.120
236	deit_small_imagenet_1_seed-0	.120
237	yudixie_resnet18_distance_rotation_0_240719	.120
238	yudixie_wbh_object_class_scaling_0415_run_3	.113
239	alexnet_training_seed_01_fov12	.113
240	resnet50_st_wzc_seed6_2_323	.108
241	ReAlnet05_ALL	.108
242	Res2Net50_26w_4s	.108
243	resnet50-SIN_IN_IN	.108
244	convnext_small_imagenet_10_seed-0	.108
245	convnext_base_imagenet_full_seed-0	.108
246	briaai_rmbg_1_4	.103
247	ReAlnet06_ALL	.098
248	ReAlnet03_cornet	.098
249	inception_v4	.098
250	ReAlnet03	.098
251	yudixie_resnet18_translation_rotation_0_240719	.098
252	resnet50_hvs_wzc	.089
253	mobilenet_v2_0_5_192	.089
254	yudixie_resnet50_translation_reg_0_240908	.089
255	AT_efficientnet-b2	.089
256	AdvProp_efficientnet-b2	.089
257	yudixie_resnet18_object_class_0_240719	.089
258	resnet50_imagenet_10_seed-0	.089
259	resnet-18_test_m	.081
260	resnet18_ecoset_full	.081
261	resnet50_tutorial	.081
262	alexnet_training_seed_04	.076
263	resnet50_ewconplus_wzc_seed5_2__323	.073
264	resnet50_st_wzc_seed7_2_323	.073
265	ReAlnet09_ALL	.073
266	ReAlnet08_ALL	.073
267	resnet50_ewconplus_wzc	.073
268	ReAlnet08_cornet	.073
269	vgg_19	.073
270	yudixie_resnet50_distance_translation_0_240908	.073
271	ReAlnet08	.073
272	shufflenet_v2_x1_0	.073
273	resnet50-SIN	.073
274	resnet50-SIN_IN	.073
275	convnext_base_fb_in1k	.066
276	yudixie_resnet50_distance_translation_rotation_0_240908	.066
277	voneresnet-50	.066
278	convnext_tiny_imagenet_full_seed-0	.066
279	convnext_base_fb_in1k_gram_aligned_dinov3	.060
280	resnet50_st_wzc_2	.060
281	yudixie_resnet50_object_class_0_240908	.060
282	yudixie_resnet50_imagenet1kpret_0_240908	.060
283	ReAlnet06_cornet	.060
284	vgg_16	.060
285	ReAlnet06	.060
286	VOneCORnet-S	.060
287	convnext_tiny_sup	.060
288	predictive_coding_pc	.055
289	yudixie_resnet50_distance_reg_0_240908	.055
290	mobilenet_v2_0_75_224	.055
291	convnext_small_imagenet_100_seed-0	.055
292	yudixie_resnet18_imagenet1kpret_0_240719	.055
293	alexnet_training_seed_06	.052
294	mobilenet_v2_1_0_160	.050
295	yudixie_resnet18_category_class_0_240719	.050
296	voneresnet-50-non_stochastic	.050
297	inception_v1	.041
298	efficientnet_b1_imagenet_full	.041
299	efficientnet_b0_imagenet_full	.041
300	resnet50_ewconplus_wzc_seed6_2_323	.037
301	mobilenet_v2_1_0_224	.037
302	resnet_50_v1	.034
303	resnet50-sup	.034
304	AdvProp_efficientnet-b4	.028
305	mobilenet_v2_0_75_192	.025
306	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.019

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

0.91.

Note that scores are relative to this ceiling.

Data: Ferguson2024gray_easy

Metric: value_delta