Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

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	cvt_cvt-21-384-in1k_4_LucyV4	1.0
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
3	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
4	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
5	convnext_large:fb_in22k_ft_in1k	1.0
6	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
7	convnext_xlarge:fb_in22k_ft_in1k	1.0
8	AlexNet_SIN	1.0
9	vit_large_patch14_clip_224:openai_ft_in1k	1.0
10	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
11	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
12	cv_18_dagger_408_pretrained	1.0
13	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
14	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	1.0
15	cvt_cvt-21-224-in1k_4_LucyV4	1.0
16	cvt_cvt-13-224-in1k_4_LucyV4	1.0
17	vit_base_patch16_dinov3-lvd1689m	1.0
18	convnext_base_imagenet_full_seed-0	1.0
19	convnext_large_imagenet_full_seed-0	1.0
20	AdvProp_efficientnet-b6	1.0
21	efficientnet_b2_imagenet_full	1.0
22	focalnet_tiny_lrf_in1k	1.0
23	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
24	custom_model_cv_18_dagger_408	1.0
25	ViT_L_32_imagenet1k	1.0
26	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
27	cvt_cvt-13-384-in1k_4_LucyV4	1.0
28	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	1.0
29	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
30	deit_base_imagenet_full_seed-0	1.0
31	efficientnet_b1_imagenet_full	1.0
32	vit_base_patch16_clip_224:openai_ft_in12k_in1k	1.0
33	vit_base_patch16_clip_224:openai_ft_in1k	1.0
34	vit_base_patch14_dinov2-lvd142m	1.0
35	vit_base_patch14_reg4_dinov2-lvd142m	1.0
36	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
37	yudixie_resnet18_translation_rotation_0_240719	1.0
38	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
39	efficientnet-b7	1.0
40	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	1.0
41	omnivore_swinB	1.0
42	efficientnet_b0	1.0
43	omnivore_swinS	1.0
44	ReAlnet06_ALL	1.0
45	AdvProp_efficientnet-b7	1.0
46	AdvProp_efficientnet-b4	1.0
47	AdvProp_efficientnet-b2	1.0
48	imagenet_l2_3_0	1.0
49	resnet50_robust_l2_eps3	1.0
50	BiT-S-R50x3	1.0
51	AdvProp_efficientnet-b8	1.0
52	convnext_tiny_sup	1.0
53	BiT-S-R152x4	1.0
54	BiT-S-R101x3	1.0
55	BiT-S-R152x2	1.0
56	BiT-S-R50x1	1.0
57	BiT-S-R101x1	1.0
58	resnet50-vicregl0p9	1.0
59	AT_efficientnet-b2	1.0
60	convnext_base:clip_laiona_augreg_ft_in1k_384	1.0
61	resnet18_fair	1.0
62	resnet50_st_wzc_seed7_2_323	1.0
63	convnext_base_fb_in1k	1.0
64	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	1.0
65	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	1.0
66	deit3_base_patch16_224_fb_in1k	1.0
67	convnext_large_clip_laion2b_finelayers	1.0
68	dinov2_vitl14_lc	1.0
69	dinov2_vitg14_lc	1.0
70	dinov2_vitg14_reg_lc	1.0
71	eva02_large_in22k	1.0
72	dinov2_vitl14_reg_lc	1.0
73	dinov2_vitl14_lc_res336	1.0
74	dinov2_vitl14_reg_lc_featread	1.0
75	vit_large_clip336_openai	1.0
76	convnext_xxlarge_clip	1.0
77	vit_huge_clip336_laion	1.0
78	resnet-152_v2_pytorch	1.0
79	resnet50_imagenet_100_seed-0	.968
80	resnet50-VITO-8deg-cc	.968
81	resnet50-vitoimagevidnet8	.968
82	voneresnet-50	.968
83	resnet_50_v1	.968
84	resnet50-sup	.968
85	densenet-169	.968
86	predictive_coding_pc	.968
87	mobilenet_v2_1_0_192	.952
88	mobilenet_v2_0_75_160	.952
89	pnasnet_large_halfPrecision	.952
90	voneresnet-50-non_stochastic	.952
91	yolos_tiny	.952
92	inception_v4	.952
93	yudixie_resnet18_distance_rotation_0_240719	.952
94	pnasnet_large	.952
95	resnet_152_v2	.952
96	resnet50_hvs_wzc	.952
97	ReAlnet09	.877
98	ReAlnet10	.877
99	deit_large_imagenet_full_seed-0	.877
100	efficientnet_b0_imagenet_full	.877
101	resnext101_32x8d_wsl	.877
102	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.877
103	resnet50-SIN_IN_IN	.877
104	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.877
105	ReAlnet01_ALL	.877
106	vonegrcnn_62e_nobn	.877
107	ReAlnet09_cornet	.877
108	grcnn_109	.877
109	vonegrcnn_47e	.877
110	resnet_SIN_IN_FT_IN	.877
111	ReAlnet10_cornet	.877
112	convnext_base_fb_in22k_ft_in1k	.877
113	convnext_base_fb_in1k_gram_aligned_dinov3	.877
114	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.877
115	convnext_large_in22k_supervised	.877
116	inception_v3	.862
117	blt_vs	.862
118	mobilenet_v2_0_75_224	.862
119	convnext_small_imagenet_full_seed-0	.862
120	resnet50_imagenet_full	.862
121	resnet-18_test_m	.862
122	voneresnet-50-robust	.862
123	deepeisnn_ei_imagenet_resnet18	.862
124	resnet34_imagenet_full	.794
125	effnetb1_272x240	.794
126	ReAlnet02_cornet	.794
127	nasnet_large	.794
128	resnet_50_v1_spiking_l3	.794
129	resnet50-vicreg	.794
130	ReAlnet04_ALL	.794
131	grcnn	.794
132	ReAlnet02	.794
133	resnet50_ewconplus_wzc_seed2_2__323	.794
134	resnet50_ewconplus_wzc_seed5_2__323	.794
135	yudixie_wbh_object_class_scaling_0415_run_0	.794
136	yudixie_wbh_object_class_scaling_0415_imagenet	.794
137	densenet-201	.780
138	mobilenet_v2_0_5_224	.780
139	resnet50_imagenet_1_seed-0	.780
140	compact_resnet50_V4	.780
141	resnet50_st_wzc_seed6_2_323	.780
142	resnet50_ewconplus_wzc_seed6_2_323	.780
143	resnet_152_v1	.719
144	deit_small_imagenet_full_seed-0	.719
145	resnext101_32x32d_wsl	.719
146	convnext_tiny_imagenet_full_seed-0	.719
147	resnext101_32x48d_wsl	.719
148	alexnet	.719
149	alexnet_fov16	.719
150	ReAlnet03_ALL	.719
151	yudixie_wbh_object_class_scaling_0415_run_2	.719
152	convnext_small_imagenet_100_seed-0	.706
153	yudixie_resnet50_distance_rotation_0_240908	.706
154	resnet_101_v2	.706
155	convnext_femto_ols:d1_in1k	.706
156	yudixie_resnet50_random_0_240908	.650
157	resnet152_imagenet_full	.650
158	alexnet_training_seed_01_fov12	.650
159	compact_resnet50_robust_IT	.650
160	resnet50_robust_l2_eps1	.650
161	vonegrcnn_52e_full	.650
162	resnet50_st_wzc_seed3_2_323	.650
163	ReAlnet05	.640
164	mobilenet_v2_1_0_128	.640
165	ReAlnet05_cornet	.640
166	antialiased-r50	.640
167	ReAlnet09_ALL	.640
168	convnext_tiny:in12k_ft_in1k	.589
169	yudixie_resnet18_category_class_0_240719	.589
170	Res2Net50_26w_4s	.589
171	mobilenet_v2_1_3_224	.589
172	inception_v1	.589
173	yudixie_resnet50_imagenet1kpret_0_240908	.579
174	resnet50_ewconplus_wzc	.579
175	resnet_50_v1_spiking_l4a	.579
176	resnet34_ecoset_full	.579
177	compact_vgg19_V4	.579
178	yudixie_resnet18_imagenet1kpret_0_240719	.579
179	resnet_50_v2	.579
180	pnasnet_large_pytorch	.533
181	ReAlnet01_cornet_fov16	.533
182	ReAlnet08_ALL	.533
183	yudixie_resnet50_distance_translation_rotation_0_240908	.524
184	resnet50_st_wzc_2	.524
185	ReAlnet10_ALL	.483
186	ReAlnet08	.483
187	yudixie_resnet50_distance_reg_0_240908	.483
188	deit_small_imagenet_100_seed-0	.483
189	resnet101_imagenet_full	.483
190	ReAlnet08_cornet	.483
191	mobilenet_v2_0_5_192	.474
192	ReAlnet05_ALL	.474
193	ReAlnet03	.437
194	ReAlnet03_cornet	.437
195	xception	.437
196	AlexNet_SIN_fov12	.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_pytorch	.430
201	yudixie_resnet50_distance_translation_0_240908	.430
202	nasnet_mobile	.430
203	mobilenet_v2_1_4_224	.430
204	alexnet_fov12	.396
205	deit_small_imagenet_10_seed-0	.396
206	resnet18_imagenet_full	.396
207	aughost_fair_resnet18	.396
208	shufflenet_v2_x1_0	.396
209	vgg_16	.396
210	yudixie_resnet50_object_class_0_240908	.389
211	resnet18_ecoset_full	.389
212	compact_resnet50_robust_V4	.389
213	yudixie_resnet50_translation_rotation_0_240908	.389
214	ReAlnet07	.358
215	alexnet_training_seed_04	.358
216	yudixie_resnet18_distance_translation_rotation_0_240719	.358
217	ReAlnet04_cornet	.358
218	yudixie_resnet18_object_class_0_240719	.358
219	ReAlnet07_cornet	.358
220	mobilenet_v2_1_0_224	.358
221	ReAlnet04	.358
222	deepeisnn_ei_cifar10_resnet18	.358
223	resnet_50_v1_spiking	.352
224	resnet50-SIN_IN	.352
225	resnet_101_v1	.352
226	alexnet_training_seed_06	.324
227	resnet50_ecoset_full	.324
228	AlexNet_SIN_fov16	.324
229	convnext_small_imagenet_10_seed-0	.319
230	alexnet_fov4	.319
231	yudixie_resnet50_rotation_reg_0_240908	.319
232	compact_vgg19_IT	.319
233	ReAlnet06	.293
234	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.293
235	resnet50-SIN	.293
236	ReAlnet01_cornet_fov12	.293
237	ReAlnet06_cornet	.293
238	ReAlnet02_ALL	.293
239	ReAlnet07_ALL	.293
240	resnet_50_v1_spiking_l4	.266
241	yudixie_resnet18_rotation_reg_0_240719	.266
242	yudixie_resnet50_translation_reg_0_240908	.266
243	resnet50-barlow	.266
244	densenet-121	.266
245	mobilenet_v2_0_75_192	.261
246	resnet50_tutorial	.261
247	ReAlnet01_cornet_fov4	.261
248	yudixie_resnet18_distance_translation_0_240719	.261
249	VOneCORnet-S	.261
250	resnet50_imagenet_10_seed-0	.240
251	compact_resnet50_IT	.240
252	pr1_stl10_disentangled_alpha04	.240
253	resnet152_ecoset_full	.236
254	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.236
255	yudixie_resnet18_distance_reg_0_240719	.236
256	resnet101_ecoset_full	.218
257	resnet-50-robust	.218
258	ReAlnet01_cornet	.218
259	ReAlnet01	.218
260	yudixie_wbh_object_class_scaling_0415_run_3	.218
261	yudixie_resnet50_category_class_0_240908	.214
262	alexnet_training_seed_01_fov4	.197
263	alexnet_training_seed_07	.178
264	yudixie_wbh_object_class_scaling_0415_run_1	.178
265	mobilenet_v2_1_0_160	.175
266	convnext_small_imagenet_1_seed-0	.175
267	deit_small_imagenet_1_seed-0	.159
268	yudixie_resnet18_translation_reg_0_240719	.159
269	resnet50_primary_visual_cortex	.159
270	alexnet_training_seed_05	.146
271	alexnet_training_seed_01	.146
272	yudixie_resnet18_random_0_240719	.146
273	deepeisnn_ei_cifar10_vgg19	.132
274	alexnet_training_seed_08	.098
275	vgg_19	.098
276	compact_cornets_IT	.098
277	alexnet_training_seed_02	.089
278	artResNet18_1	.089
279	compact_cornets_V4	.087
280	alexnet_training_seed_09	.066
281	briaai_rmbg_1_4	.060
282	alexnet_training_seed_01_fov16	.054
283	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.039
284	AlexNet_SIN_fov4	.039
285	alexnet_training_seed_03	.022
286	alexnet_training_seed_10
287	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