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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	resnet50_simclr_linhead_01norm	.882
20	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.882
21	cv_18_dagger_408_pretrained	.882
22	nasnet_large	.882
23	resnet50-moclr8deg	.882
24	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.882
25	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.882
26	BiT-S-R152x2	.882
27	deit_small_imagenet_full_seed-0	.882
28	resnet152_imagenet_full	.882
29	alexnet	.882
30	ijepa_vith14_linhead	.845
31	vit_huge_clip336_laion	.845
32	vit_large_clip336_openai	.845
33	dinov2_vitl14_reg_lc_featread	.845
34	dinov2_vitl14_lc_res336	.845
35	dinov2_vitl14_reg_lc	.845
36	eva02_large_in22k	.845
37	dinov2_vitg14_reg_lc	.845
38	dinov2_vitg14_lc	.845
39	dinov2_vitl14_lc	.845
40	deit3_base_patch16_224_fb_in1k	.845
41	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.845
42	vit_base_patch16_dinov3-lvd1689m	.845
43	vit_base_patch14_reg4_dinov2-lvd142m	.845
44	vit_base_patch14_dinov2-lvd142m	.845
45	compact_resnet50_V4	.845
46	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.845
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.845
48	vit_large_patch14_clip_224:openai_ft_in1k	.845
49	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.845
50	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.845
51	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.845
52	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.845
53	vit_relpos_base_patch16_clsgap_224:sw_in1k	.845
54	vit_large_patch14_clip_224:laion2b_ft_in1k	.845
55	vit_base_patch16_clip_224:openai_ft_in1k	.845
56	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.845
57	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.845
58	convnext_large:fb_in22k_ft_in1k	.845
59	BiT-S-R152x4	.845
60	AdvProp_efficientnet-b8	.845
61	AdvProp_efficientnet-b7	.845
62	deit_large_imagenet_full_seed-0	.845
63	deit_base_imagenet_full_seed-0	.845
64	resnet101_ecoset_full	.845
65	cvt_cvt-21-384-in1k_4_LucyV4	.845
66	cvt_cvt-13-384-in1k_4_LucyV4	.845
67	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.845
68	ViT_L_32_imagenet1k	.845
69	compact_vgg19_V4	.800
70	compact_resnet50_IT	.800
71	nasnet_mobile	.800
72	BiT-S-R101x3	.800
73	gabor_filter_mean_abs_4x4_v2	.767
74	AlexNet_SIN_fov12	.767
75	vonegrcnn_62e_nobn	.767
76	grcnn	.767
77	densenet-169	.767
78	mehrer2020_alexnet_training_seed_02	.725
79	mehrer2020_alexnet_training_seed_01_fov12	.725
80	alexnet_training_seed_01_fov4	.725
81	resnet_152_v1	.725
82	omnivore_swinS	.725
83	convnext_xlarge:fb_in22k_ft_in1k	.725
84	yudixie_resnet18_translation_reg_0_240719	.725
85	mobilenet_v2_1_0_128	.695
86	convnext_tiny:in12k_ft_in1k	.695
87	AdvProp_efficientnet-b6	.695
88	resnet152_ecoset_full	.695
89	resnext101_32x16d_wsl	.658
90	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.658
91	yudixie_resnet50_random_0_240908	.630
92	yudixie_resnet18_distance_translation_0_240719	.630
93	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.630
94	resnet-50-robust	.630
95	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.630
96	deit_small_imagenet_100_seed-0	.596
97	cvt_cvt-13-224-in1k_4_LucyV4	.596
98	resnet101_imagenet_full	.596
99	yolos_tiny	.572
100	resnet50_robust_l2_eps3	.572
101	imagenet_l2_3_0	.572
102	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.572
103	alexnet_fov12	.541
104	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.541
105	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.541
106	convnext_base:clip_laiona_augreg_ft_in1k_384	.541
107	pnasnet_large_halfPrecision	.518
108	mobilenet_v2_1_4_224	.518
109	pnasnet_large	.518
110	resnet50-barlow	.518
111	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.518
112	mobilenet_v2_1-4_224_pytorch	.518
113	focalnet_tiny_lrf_in1k	.518
114	resnet-152_v2_pytorch	.518
115	compact_cornets_IT	.490
116	alexnet_training_seed_01	.490
117	resnet50-vicregl0p75	.490
118	mehrer2020_alexnet_training_seed_08	.470
119	mehrer2020_alexnet_training_seed_07	.470
120	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.470
121	resnet_101_v1	.470
122	BiT-S-R50x1	.470
123	BiT-S-R101x1	.470
124	cvt_cvt-21-224-in1k_4_LucyV4	.470
125	resnet50_ecoset_full	.470
126	resnet34_ecoset_full	.470
127	resnet50_imagenet_full	.470
128	effnetb1_272x240	.470
129	compact_vgg19_IT	.445
130	alexnet_fov16	.445
131	alexnet_training_seed_10	.445
132	resnext101_32x8d_wsl	.445
133	mehrer2020_alexnet_training_seed_09	.426
134	AlexNet_SIN_fov16	.426
135	ReAlnet10_cornet	.426
136	ReAlnet09_cornet	.426
137	ReAlnet10	.426
138	ReAlnet09	.426
139	resnet50-vicreg	.426
140	blt_vs	.426
141	yudixie_resnet18_random_0_240719	.426
142	pnasnet_large_pytorch	.426
143	mehrer2020_alexnet_training_seed_01_fov16	.403
144	deepeisnn_ei_cifar10_vgg19	.403
145	yudixie_wbh_object_class_scaling_0415_run_2	.403
146	resnext101_32x48d_wsl	.403
147	resnext101_32x32d_wsl	.403
148	mehrer2020_alexnet_training_seed_10	.387
149	pr1_stl10_disentangled_alpha04	.387
150	resnet_50_v1_spiking_l4	.387
151	mobilenet_v2_1_0_192	.387
152	ReAlnet07_ALL	.351
153	resnet_SIN_IN_FT_IN	.351
154	gabor_filter_entropy_4x4	.332
155	ReAlnet01_cornet_fov16	.332
156	xception	.332
157	alexnet_training_seed_07	.332
158	alexnet_training_seed_09	.332
159	mehrer2020_alexnet_training_seed_06	.318
160	ReAlnet01_cornet_fov12	.318
161	ReAlnet07_cornet	.318
162	inception_v3	.318
163	ReAlnet07	.318
164	voneresnet-50-robust	.318
165	convnext_small_imagenet_1_seed-0	.318
166	deepeisnn_ei_imagenet_resnet18	.301
167	compact_resnet50_robust_V4	.301
168	resnet50_vicreg_linhead	.288
169	AlexNet_SIN	.288
170	yudixie_resnet50_distance_rotation_0_240908	.288
171	vonegrcnn_52e_full	.288
172	antialiased-r50	.288
173	artResNet18_1	.288
174	yudixie_resnet18_distance_reg_0_240719	.288
175	yudixie_resnet18_rotation_reg_0_240719	.288
176	ReAlnet01_ALL	.261
177	resnet_50_v1_spiking_l3	.261
178	ReAlnet05_cornet	.261
179	ReAlnet05	.261
180	yudixie_resnet18_distance_translation_rotation_0_240719	.261
181	alexnet_training_seed_02	.247
182	omnivore_swinB	.247
183	mehrer2020_alexnet_training_seed_04	.237
184	yudixie_wbh_object_class_scaling_0415_imagenet	.237
185	ReAlnet10_ALL	.237
186	densenet-201	.237
187	efficientnet_b0	.237
188	convnext_large_imagenet_full_seed-0	.237
189	resnet50_imagenet_100_seed-0	.237
190	resnet50_imagenet_1_seed-0	.237
191	gabor_filter_entropy_4x4_v2	.224
192	eicircuit_resnet18_bn_20260919	.215
193	seresnext50_32x4d	.215
194	yudixie_resnet50_rotation_reg_0_240908	.215
195	vonegrcnn_47e	.215
196	efficientnet_b2_imagenet_full	.215
197	resnet34_imagenet_full	.215
198	alexnet_training_seed_01_fov16	.203
199	mehrer2020_alexnet_training_seed_01_fov4	.195
200	resnet50_st_wzc_seed3_2_323	.195
201	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.195
202	ReAlnet02_ALL	.195
203	resnet_50_v2	.195
204	convnext_femto_ols:d1_in1k	.195
205	yudixie_wbh_object_class_scaling_0415_run_0	.184
206	compact_resnet50_robust_IT	.184
207	alexnet_training_seed_05	.184
208	ReAlnet03_ALL	.177
209	AlexNet_SIN_fov4	.177
210	mobilenet_v2_0_75_160	.177
211	mobilenet_v2_0_5_224	.177
212	efficientnet-b7	.177
213	resnet50_simsiam_linhead	.160
214	resnet50_barlowtwins_linhead	.160
215	mehrer2020_alexnet_training_seed_05	.160
216	resnet50_primary_visual_cortex	.160
217	ReAlnet01_cornet_fov4	.160
218	alexnet_fov4	.160
219	ReAlnet01_cornet	.160
220	resnet_152_v2	.160
221	grcnn_109	.160
222	ReAlnet01	.160
223	convnext_small_imagenet_full_seed-0	.160
224	resnet18_imagenet_full	.160
225	compact_cornets_V4	.152
226	alexnet_training_seed_03	.152
227	deit_small_imagenet_10_seed-0	.152
228	resnet18_fair	.145
229	ReAlnet02_cornet	.145
230	ReAlnet02	.145
231	resnet50-vicregl0p9	.145
232	gabor_filter_entropy_4x4_v2_forcedCosine	.138
233	yudixie_wbh_object_class_scaling_0415_run_1	.138
234	hmax	.138
235	ReAlnet04_cornet	.132
236	ReAlnet04	.132
237	alexnet_training_seed_08	.125
238	ReAlnet04_ALL	.120
239	resnet_50_v1_spiking_l4a	.120
240	yudixie_resnet50_category_class_0_240908	.120
241	deit_small_imagenet_1_seed-0	.120
242	yudixie_resnet18_distance_rotation_0_240719	.120
243	yudixie_wbh_object_class_scaling_0415_run_3	.113
244	alexnet_training_seed_01_fov12	.113
245	resnet50_st_wzc_seed6_2_323	.108
246	ReAlnet05_ALL	.108
247	Res2Net50_26w_4s	.108
248	resnet50-SIN_IN_IN	.108
249	convnext_small_imagenet_10_seed-0	.108
250	convnext_base_imagenet_full_seed-0	.108
251	briaai_rmbg_1_4	.103
252	ReAlnet06_ALL	.098
253	ReAlnet03_cornet	.098
254	inception_v4	.098
255	ReAlnet03	.098
256	yudixie_resnet18_translation_rotation_0_240719	.098
257	resnet50_hvs_wzc	.089
258	mobilenet_v2_0_5_192	.089
259	yudixie_resnet50_translation_reg_0_240908	.089
260	AT_efficientnet-b2	.089
261	AdvProp_efficientnet-b2	.089
262	yudixie_resnet18_object_class_0_240719	.089
263	resnet50_imagenet_10_seed-0	.089
264	resnet-18_test_m	.081
265	resnet18_ecoset_full	.081
266	resnet50_tutorial	.081
267	alexnet_training_seed_04	.076
268	resnet50_ewconplus_wzc_seed5_2__323	.073
269	resnet50_st_wzc_seed7_2_323	.073
270	ReAlnet09_ALL	.073
271	ReAlnet08_ALL	.073
272	resnet50_ewconplus_wzc	.073
273	ReAlnet08_cornet	.073
274	vgg_19	.073
275	yudixie_resnet50_distance_translation_0_240908	.073
276	ReAlnet08	.073
277	shufflenet_v2_x1_0	.073
278	resnet50-SIN	.073
279	resnet50-SIN_IN	.073
280	convnext_base_fb_in1k	.066
281	yudixie_resnet50_distance_translation_rotation_0_240908	.066
282	voneresnet-50	.066
283	convnext_tiny_imagenet_full_seed-0	.066
284	convnext_base_fb_in1k_gram_aligned_dinov3	.060
285	resnet50_st_wzc_2	.060
286	yudixie_resnet50_object_class_0_240908	.060
287	yudixie_resnet50_imagenet1kpret_0_240908	.060
288	ReAlnet06_cornet	.060
289	vgg_16	.060
290	ReAlnet06	.060
291	VOneCORnet-S	.060
292	convnext_tiny_sup	.060
293	resnet50_byol_linhead	.055
294	predictive_coding_pc	.055
295	yudixie_resnet50_distance_reg_0_240908	.055
296	mobilenet_v2_0_75_224	.055
297	convnext_small_imagenet_100_seed-0	.055
298	yudixie_resnet18_imagenet1kpret_0_240719	.055
299	alexnet_training_seed_06	.052
300	mobilenet_v2_1_0_160	.050
301	yudixie_resnet18_category_class_0_240719	.050
302	voneresnet-50-non_stochastic	.050
303	inception_v1	.041
304	efficientnet_b1_imagenet_full	.041
305	efficientnet_b0_imagenet_full	.041
306	resnet50_ewconplus_wzc_seed6_2_323	.037
307	mobilenet_v2_1_0_224	.037
308	resnet_50_v1	.034
309	resnet50-sup	.034
310	AdvProp_efficientnet-b4	.028
311	mobilenet_v2_0_75_192	.025
312	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