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

0.90.

Note that scores are relative to this ceiling.

Data: Ferguson2024color

Metric: value_delta