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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024color-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	seresnext50_32x4d	1.0
2	regnety_032	1.0
3	vit_huge_clip336_laion	1.0
4	convnext_xxlarge_clip	1.0
5	vit_large_clip336_openai	1.0
6	dinov2_vitl14_reg_lc_featread	1.0
7	dinov2_vitl14_lc_res336	1.0
8	dinov2_vitl14_reg_lc	1.0
9	eva02_large_in22k	1.0
10	dinov2_vitg14_reg_lc	1.0
11	dinov2_vitg14_lc	1.0
12	dinov2_vitl14_lc	1.0
13	convnext_large_clip_laion2b_finelayers	1.0
14	deit3_base_patch16_224_fb_in1k	1.0
15	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	1.0
16	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	1.0
17	convnext_base_fb_in1k	1.0
18	resnet18_fair	1.0
19	resnet50_st_wzc_seed7_2_323	1.0
20	vit_base_patch16_dinov3-lvd1689m	1.0
21	vit_base_patch14_reg4_dinov2-lvd142m	1.0
22	vit_base_patch14_dinov2-lvd142m	1.0
23	cv_18_dagger_408_pretrained	1.0
24	AlexNet_SIN	1.0
25	ReAlnet06_ALL	1.0
26	ijepa_vith14_linhead	1.0
27	mehrer2020_alexnet_training_seed_10	1.0
28	mehrer2020_alexnet_training_seed_04	1.0
29	mehrer2020_alexnet_training_seed_01_fov4	1.0
30	efficientnet-b7	1.0
31	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
32	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
33	vit_large_patch14_clip_224:openai_ft_in1k	1.0
34	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
35	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
36	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
37	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
38	omnivore_swinS	1.0
39	efficientnet_b0	1.0
40	omnivore_swinB	1.0
41	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	1.0
42	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
43	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
44	vit_base_patch16_clip_224:openai_ft_in1k	1.0
45	vit_base_patch16_clip_224:openai_ft_in12k_in1k	1.0
46	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	1.0
47	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
48	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
49	convnext_xlarge:fb_in22k_ft_in1k	1.0
50	convnext_large:fb_in22k_ft_in1k	1.0
51	convnext_base:clip_laiona_augreg_ft_in1k_384	1.0
52	AT_efficientnet-b2	1.0
53	resnet50-vicregl0p9	1.0
54	BiT-S-R101x1	1.0
55	BiT-S-R50x1	1.0
56	BiT-S-R152x2	1.0
57	BiT-S-R101x3	1.0
58	BiT-S-R152x4	1.0
59	convnext_tiny_sup	1.0
60	AdvProp_efficientnet-b8	1.0
61	BiT-S-R50x3	1.0
62	resnet50_robust_l2_eps3	1.0
63	imagenet_l2_3_0	1.0
64	AdvProp_efficientnet-b2	1.0
65	AdvProp_efficientnet-b4	1.0
66	AdvProp_efficientnet-b7	1.0
67	AdvProp_efficientnet-b6	1.0
68	convnext_large_imagenet_full_seed-0	1.0
69	convnext_base_imagenet_full_seed-0	1.0
70	yudixie_resnet18_translation_rotation_0_240719	1.0
71	deit_base_imagenet_full_seed-0	1.0
72	efficientnet_b2_imagenet_full	1.0
73	efficientnet_b1_imagenet_full	1.0
74	cvt_cvt-21-384-in1k_4_LucyV4	1.0
75	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	1.0
76	cvt_cvt-13-384-in1k_4_LucyV4	1.0
77	cvt_cvt-21-224-in1k_4_LucyV4	1.0
78	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
79	cvt_cvt-13-224-in1k_4_LucyV4	1.0
80	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
81	ViT_L_32_imagenet1k	1.0
82	custom_model_cv_18_dagger_408	1.0
83	focalnet_tiny_lrf_in1k	1.0
84	resnet-152_v2_pytorch	1.0
85	predictive_coding_pc	.968
86	mehrer2020_alexnet_training_seed_09	.968
87	resnet_50_v1	.968
88	voneresnet-50	.968
89	resnet50-vitoimagevidnet8	.968
90	resnet50-VITO-8deg-cc	.968
91	densenet-169	.968
92	resnet50-sup	.968
93	resnet50_imagenet_100_seed-0	.968
94	pnasnet_large_halfPrecision	.952
95	resnet50_hvs_wzc	.952
96	yolos_tiny	.952
97	pnasnet_large	.952
98	mobilenet_v2_1_0_192	.952
99	resnet_152_v2	.952
100	inception_v4	.952
101	mobilenet_v2_0_75_160	.952
102	yudixie_resnet18_distance_rotation_0_240719	.952
103	voneresnet-50-non_stochastic	.952
104	gabor_filter_mean_abs_4x4_v2	.877
105	convnext_large_in22k_supervised	.877
106	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.877
107	convnext_base_fb_in1k_gram_aligned_dinov3	.877
108	convnext_base_fb_in22k_ft_in1k	.877
109	ReAlnet01_ALL	.877
110	mehrer2020_alexnet_training_seed_05	.877
111	ReAlnet10_cornet	.877
112	ReAlnet09_cornet	.877
113	grcnn_109	.877
114	vonegrcnn_62e_nobn	.877
115	ReAlnet10	.877
116	ReAlnet09	.877
117	resnet50-SIN_IN_IN	.877
118	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.877
119	resnet_SIN_IN_FT_IN	.877
120	vonegrcnn_47e	.877
121	deit_large_imagenet_full_seed-0	.877
122	efficientnet_b0_imagenet_full	.877
123	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.877
124	resnext101_32x8d_wsl	.877
125	deepeisnn_ei_imagenet_resnet18	.862
126	mehrer2020_alexnet_training_seed_01_fov12	.862
127	mobilenet_v2_0_75_224	.862
128	inception_v3	.862
129	voneresnet-50-robust	.862
130	resnet-18_test_m	.862
131	blt_vs	.862
132	convnext_small_imagenet_full_seed-0	.862
133	resnet50_imagenet_full	.862
134	eicircuit_resnet18_bn_20260919	.794
135	yudixie_wbh_object_class_scaling_0415_imagenet	.794
136	yudixie_wbh_object_class_scaling_0415_run_0	.794
137	resnet50_ewconplus_wzc_seed5_2__323	.794
138	resnet50_ewconplus_wzc_seed2_2__323	.794
139	ReAlnet04_ALL	.794
140	resnet_50_v1_spiking_l3	.794
141	mehrer2020_alexnet_training_seed_03	.794
142	ReAlnet02_cornet	.794
143	nasnet_large	.794
144	grcnn	.794
145	ReAlnet02	.794
146	resnet50-vicreg	.794
147	resnet34_imagenet_full	.794
148	effnetb1_272x240	.794
149	resnet50_ewconplus_wzc_seed6_2_323	.780
150	resnet50_st_wzc_seed6_2_323	.780
151	mobilenet_v2_0_5_224	.780
152	densenet-201	.780
153	compact_resnet50_V4	.780
154	resnet50_imagenet_1_seed-0	.780
155	yudixie_wbh_object_class_scaling_0415_run_2	.719
156	alexnet_fov16	.719
157	ReAlnet03_ALL	.719
158	resnet_152_v1	.719
159	convnext_tiny_imagenet_full_seed-0	.719
160	deit_small_imagenet_full_seed-0	.719
161	alexnet	.719
162	resnext101_32x48d_wsl	.719
163	resnext101_32x32d_wsl	.719
164	resnet_101_v2	.706
165	yudixie_resnet50_distance_rotation_0_240908	.706
166	convnext_femto_ols:d1_in1k	.706
167	convnext_small_imagenet_100_seed-0	.706
168	resnet50_st_wzc_seed3_2_323	.650
169	alexnet_training_seed_01_fov12	.650
170	resnet50_simclr_linhead_01norm	.650
171	yudixie_resnet50_random_0_240908	.650
172	resnet50_robust_l2_eps1	.650
173	vonegrcnn_52e_full	.650
174	compact_resnet50_robust_IT	.650
175	resnet152_imagenet_full	.650
176	ReAlnet09_ALL	.640
177	ReAlnet05_cornet	.640
178	mobilenet_v2_1_0_128	.640
179	ReAlnet05	.640
180	antialiased-r50	.640
181	resnext101_32x16d_wsl	.589
182	mobilenet_v2_1_3_224	.589
183	inception_v1	.589
184	Res2Net50_26w_4s	.589
185	convnext_tiny:in12k_ft_in1k	.589
186	yudixie_resnet18_category_class_0_240719	.589
187	resnet50_ewconplus_wzc	.579
188	resnet_50_v1_spiking_l4a	.579
189	yudixie_resnet50_imagenet1kpret_0_240908	.579
190	resnet_50_v2	.579
191	yudixie_resnet18_imagenet1kpret_0_240719	.579
192	compact_vgg19_V4	.579
193	resnet34_ecoset_full	.579
194	ReAlnet01_cornet_fov16	.533
195	ReAlnet08_ALL	.533
196	pnasnet_large_pytorch	.533
197	resnet50_st_wzc_2	.524
198	mehrer2020_alexnet_training_seed_08	.524
199	mehrer2020_alexnet_training_seed_06	.524
200	yudixie_resnet50_distance_translation_rotation_0_240908	.524
201	ReAlnet10_ALL	.483
202	yudixie_resnet50_distance_reg_0_240908	.483
203	ReAlnet08_cornet	.483
204	ReAlnet08	.483
205	deit_small_imagenet_100_seed-0	.483
206	resnet101_imagenet_full	.483
207	ReAlnet05_ALL	.474
208	mobilenet_v2_0_5_192	.474
209	AlexNet_SIN_fov12	.437
210	xception	.437
211	ReAlnet03_cornet	.437
212	ReAlnet03	.437
213	resnet50-moclr8deg	.437
214	resnet50-vicregl0p75	.437
215	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.430
216	mobilenet_v2_1_4_224	.430
217	nasnet_mobile	.430
218	yudixie_resnet50_distance_translation_0_240908	.430
219	mobilenet_v2_1-4_224_pytorch	.430
220	alexnet_fov12	.396
221	resnet50_barlowtwins_linhead	.396
222	vgg_16	.396
223	shufflenet_v2_x1_0	.396
224	deit_small_imagenet_10_seed-0	.396
225	resnet18_imagenet_full	.396
226	yudixie_resnet50_object_class_0_240908	.389
227	yudixie_resnet50_translation_rotation_0_240908	.389
228	compact_resnet50_robust_V4	.389
229	resnet18_ecoset_full	.389
230	deepeisnn_ei_cifar10_resnet18	.358
231	mehrer2020_alexnet_training_seed_01	.358
232	mobilenet_v2_1_0_224	.358
233	alexnet_training_seed_04	.358
234	ReAlnet07_cornet	.358
235	ReAlnet04_cornet	.358
236	ReAlnet07	.358
237	ReAlnet04	.358
238	yudixie_resnet18_object_class_0_240719	.358
239	yudixie_resnet18_distance_translation_rotation_0_240719	.358
240	resnet_50_v1_spiking	.352
241	resnet_101_v1	.352
242	resnet50-SIN_IN	.352
243	AlexNet_SIN_fov16	.324
244	alexnet_training_seed_06	.324
245	resnet50_ecoset_full	.324
246	alexnet_fov4	.319
247	yudixie_resnet50_rotation_reg_0_240908	.319
248	convnext_small_imagenet_10_seed-0	.319
249	compact_vgg19_IT	.319
250	ReAlnet01_cornet_fov12	.293
251	ReAlnet07_ALL	.293
252	ReAlnet02_ALL	.293
253	resnet50_vicreg_linhead	.293
254	ReAlnet06_cornet	.293
255	ReAlnet06	.293
256	resnet50-SIN	.293
257	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.293
258	resnet_50_v1_spiking_l4	.266
259	yudixie_resnet50_translation_reg_0_240908	.266
260	resnet50-barlow	.266
261	densenet-121	.266
262	yudixie_resnet18_rotation_reg_0_240719	.266
263	ReAlnet01_cornet_fov4	.261
264	mobilenet_v2_0_75_192	.261
265	VOneCORnet-S	.261
266	yudixie_resnet18_distance_translation_0_240719	.261
267	resnet50_tutorial	.261
268	pr1_stl10_disentangled_alpha04	.240
269	compact_resnet50_IT	.240
270	resnet50_imagenet_10_seed-0	.240
271	yudixie_resnet18_distance_reg_0_240719	.236
272	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.236
273	resnet152_ecoset_full	.236
274	yudixie_wbh_object_class_scaling_0415_run_3	.218
275	mehrer2020_alexnet_training_seed_07	.218
276	mehrer2020_alexnet_training_seed_01_fov16	.218
277	ReAlnet01_cornet	.218
278	ReAlnet01	.218
279	resnet101_ecoset_full	.218
280	resnet-50-robust	.218
281	yudixie_resnet50_category_class_0_240908	.214
282	alexnet_training_seed_01_fov4	.197
283	resnet50_byol_linhead	.197
284	yudixie_wbh_object_class_scaling_0415_run_1	.178
285	resnet50_simsiam_linhead	.178
286	alexnet_training_seed_07	.178
287	mobilenet_v2_1_0_160	.175
288	convnext_small_imagenet_1_seed-0	.175
289	resnet50_primary_visual_cortex	.159
290	deit_small_imagenet_1_seed-0	.159
291	yudixie_resnet18_translation_reg_0_240719	.159
292	alexnet_training_seed_10	.146
293	alexnet_training_seed_01	.146
294	alexnet_training_seed_05	.146
295	yudixie_resnet18_random_0_240719	.146
296	deepeisnn_ei_cifar10_vgg19	.132
297	mehrer2020_alexnet_training_seed_02	.120
298	alexnet_training_seed_08	.098
299	vgg_19	.098
300	compact_cornets_IT	.098
301	gabor_filter_entropy_4x4_v2_forcedCosine	.089
302	gabor_filter_entropy_4x4_v2	.089
303	alexnet_training_seed_02	.089
304	artResNet18_1	.089
305	compact_cornets_V4	.087
306	alexnet_training_seed_09	.066
307	briaai_rmbg_1_4	.060
308	gabor_filter_entropy_4x4	.054
309	alexnet_training_seed_01_fov16	.054
310	hmax	.040
311	AlexNet_SIN_fov4	.039
312	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.039
313	alexnet_training_seed_03	.022

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

0.90.

Note that scores are relative to this ceiling.

Data: Ferguson2024color

Metric: value_delta