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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024round_v-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50_simclr_linhead_01norm	1.0
2	mehrer2020_alexnet_training_seed_01_fov4	1.0
3	vit_huge_clip336_laion	1.0
4	vit_large_clip336_openai	1.0
5	dinov2_vitl14_lc_res336	1.0
6	yudixie_wbh_object_class_scaling_0415_run_0	1.0
7	ReAlnet01_cornet	1.0
8	mobilenet_v2_0_75_192	1.0
9	grcnn	1.0
10	ReAlnet01	1.0
11	voneresnet-50-robust	1.0
12	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
13	resnet50_ecoset_full	1.0
14	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
15	yudixie_resnet18_object_class_0_240719	1.0
16	yudixie_resnet18_distance_translation_0_240719	1.0
17	resnet152_ecoset_full	1.0
18	resnet50_vicreg_linhead	1.0
19	resnet50_simsiam_linhead	1.0
20	alexnet_training_seed_01_fov4	1.0
21	ReAlnet08_cornet	1.0
22	resnet_152_v2	1.0
23	nasnet_large	1.0
24	ReAlnet08	1.0
25	resnet50-SIN	1.0
26	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
27	convnext_femto_ols:d1_in1k	1.0
28	ijepa_vith14_linhead	1.0
29	eicircuit_resnet18_bn_20260919	1.0
30	ReAlnet01_cornet_fov4	1.0
31	yudixie_resnet50_category_class_0_240908	1.0
32	alexnet_training_seed_04	1.0
33	ReAlnet06_cornet	1.0
34	ReAlnet04_cornet	1.0
35	inception_v4	1.0
36	ReAlnet06	1.0
37	ReAlnet04	1.0
38	Res2Net50_26w_4s	1.0
39	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
40	convnext_small_imagenet_10_seed-0	1.0
41	resnet34_ecoset_full	1.0
42	ReAlnet01_ALL	.924
43	mobilenet_v2_1_4_224	.924
44	mobilenet_v2_0_5_224	.924
45	omnivore_swinB	.924
46	convnext_xlarge:fb_in22k_ft_in1k	.924
47	convnext_base_imagenet_full_seed-0	.924
48	resnet101_imagenet_full	.924
49	mobilenet_v2_1-4_224_pytorch	.924
50	deepeisnn_ei_imagenet_resnet18	.905
51	vit_base_patch16_dinov3-lvd1689m	.905
52	compact_vgg19_IT	.905
53	voneresnet-50	.905
54	efficientnet-b7	.905
55	vit_large_patch14_clip_336:laion2b_ft_in1k	.905
56	convnext_tiny_imagenet_full_seed-0	.905
57	seresnext50_32x4d	.836
58	AlexNet_SIN_fov12	.836
59	ReAlnet09_cornet	.836
60	nasnet_mobile	.836
61	inception_v1	.836
62	ReAlnet09	.836
63	deit_small_imagenet_100_seed-0	.836
64	deit_large_imagenet_full_seed-0	.836
65	resnet101_ecoset_full	.836
66	dinov2_vitl14_lc	.820
67	convnext_large_in22k_supervised	.820
68	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.820
69	resnet50-vicreg	.820
70	vit_large_patch14_clip_224:openai_ft_in1k	.820
71	blt_vs	.820
72	yudixie_resnet18_distance_reg_0_240719	.820
73	resnet152_imagenet_full	.820
74	resnet18_imagenet_full	.820
75	focalnet_tiny_lrf_in1k	.820
76	resnext101_32x32d_wsl	.820
77	mehrer2020_alexnet_training_seed_08	.757
78	yudixie_resnet50_distance_reg_0_240908	.757
79	alexnet_training_seed_10	.757
80	vgg_16	.757
81	vonegrcnn_62e_nobn	.757
82	resnet34_imagenet_full	.757
83	ViT_L_32_imagenet1k	.757
84	mehrer2020_alexnet_training_seed_03	.742
85	resnet18_fair	.742
86	ReAlnet01_cornet_fov12	.742
87	alexnet_training_seed_01	.742
88	ReAlnet05_cornet	.742
89	ReAlnet05	.742
90	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.742
91	resnext101_32x16d_wsl	.686
92	regnety_032	.686
93	deit3_base_patch16_224_fb_in22k_ft_in1k	.686
94	ReAlnet10_ALL	.686
95	ReAlnet05_ALL	.686
96	ReAlnet02_ALL	.686
97	shufflenet_v2_x1_0	.686
98	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.686
99	resnet50_byol_linhead	.672
100	mehrer2020_alexnet_training_seed_06	.672
101	mehrer2020_alexnet_training_seed_02	.672
102	yudixie_wbh_object_class_scaling_0415_run_3	.672
103	resnet50_st_wzc_seed7_2_323	.672
104	AlexNet_SIN_fov4	.672
105	alexnet_fov4	.672
106	ReAlnet07_ALL	.672
107	resnet_50_v1_spiking_l3	.672
108	resnet_50_v2	.672
109	vgg_19	.672
110	efficientnet_b0	.672
111	AdvProp_efficientnet-b7	.672
112	efficientnet_b2_imagenet_full	.672
113	custom_model_cv_18_dagger_408	.672
114	ReAlnet08_ALL	.621
115	ReAlnet03_ALL	.621
116	inception_v3	.621
117	omnivore_swinS	.621
118	densenet-169	.621
119	AdvProp_efficientnet-b4	.621
120	convnext_small_imagenet_full_seed-0	.621
121	deit_small_imagenet_10_seed-0	.621
122	deit_base_imagenet_full_seed-0	.621
123	resnet18_ecoset_full	.621
124	resnext101_32x48d_wsl	.621
125	convnext_xxlarge_clip	.609
126	yudixie_wbh_object_class_scaling_0415_run_1	.609
127	compact_cornets_IT	.609
128	compact_cornets_V4	.609
129	yudixie_resnet50_distance_translation_rotation_0_240908	.609
130	ReAlnet07_cornet	.609
131	ReAlnet03_cornet	.609
132	grcnn_109	.609
133	ReAlnet07	.609
134	ReAlnet03	.609
135	vonegrcnn_47e	.609
136	voneresnet-50-non_stochastic	.609
137	mehrer2020_alexnet_training_seed_01	.562
138	alexnet_fov12	.562
139	convnext_tiny_sup	.562
140	AdvProp_efficientnet-b8	.562
141	yudixie_resnet18_imagenet1kpret_0_240719	.562
142	alexnet_training_seed_05	.551
143	ReAlnet02_cornet	.551
144	ReAlnet02	.551
145	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.551
146	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.551
147	resnet_SIN_IN_FT_IN	.551
148	yudixie_resnet18_translation_reg_0_240719	.551
149	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.551
150	resnet-50-robust	.551
151	convnext_large_clip_laion2b_finelayers	.509
152	resnet50_hvs_wzc	.509
153	alexnet_training_seed_03	.509
154	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.509
155	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.509
156	cvt_cvt-21-384-in1k_4_LucyV4	.509
157	hmax	.509
158	dinov2_vitg14_reg_lc	.499
159	resnet50_st_wzc_seed3_2_323	.499
160	compact_resnet50_robust_IT	.499
161	resnet_50_v1_spiking_l4a	.499
162	mobilenet_v2_0_75_224	.499
163	BiT-S-R50x1	.499
164	convnext_small_imagenet_1_seed-0	.499
165	cv_18_dagger_408_pretrained	.461
166	ReAlnet06_ALL	.461
167	vit_base_patch16_clip_224:openai_ft_in1k	.461
168	convnext_large_imagenet_full_seed-0	.461
169	resnet50_imagenet_100_seed-0	.461
170	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.461
171	dinov2_vitl14_reg_lc	.452
172	mehrer2020_alexnet_training_seed_07	.417
173	pr1_stl10_disentangled_alpha04	.417
174	resnet50_primary_visual_cortex	.417
175	resnet-18_test_m	.417
176	resnet50-SIN_IN	.417
177	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.417
178	convnext_base:clip_laiona_augreg_ft_in1k_384	.417
179	cvt_cvt-13-224-in1k_4_LucyV4	.417
180	mehrer2020_alexnet_training_seed_09	.409
181	gabor_filter_mean_abs_4x4_v2	.409
182	dinov2_vitg14_lc	.409
183	vit_base_patch14_dinov2-lvd142m	.409
184	mobilenet_v2_1_3_224	.409
185	resnet_152_v1	.409
186	resnet_101_v2	.409
187	resnet_50_v1	.409
188	mobilenet_v2_0_75_160	.409
189	resnet50-vitoimagevidnet8	.409
190	resnet50-VITO-8deg-cc	.409
191	vit_relpos_base_patch16_clsgap_224:sw_in1k	.409
192	resnet50-sup	.409
193	yudixie_resnet18_distance_rotation_0_240719	.409
194	yudixie_wbh_object_class_scaling_0415_imagenet	.378
195	ReAlnet09_ALL	.378
196	VOneCORnet-S	.378
197	BiT-S-R50x3	.378
198	resnet50_robust_l2_eps3	.378
199	imagenet_l2_3_0	.378
200	effnetb1_272x240	.378
201	AlexNet_SIN_fov16	.370
202	briaai_rmbg_1_4	.370
203	xception	.370
204	ReAlnet10_cornet	.370
205	ReAlnet10	.370
206	resnet50-SIN_IN_IN	.370
207	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.370
208	convnext_large:fb_in22k_ft_in1k	.370
209	resnet50_imagenet_full	.370
210	resnet50-vicregl0p9	.342
211	artResNet18_1	.342
212	cvt_cvt-13-384-in1k_4_LucyV4	.342
213	deit3_base_patch16_224_fb_in1k	.335
214	AlexNet_SIN	.335
215	resnet50_ewconplus_wzc	.335
216	yudixie_resnet50_object_class_0_240908	.335
217	yudixie_resnet50_random_0_240908	.335
218	mehrer2020_alexnet_training_seed_10	.310
219	mehrer2020_alexnet_training_seed_04	.310
220	convnext_base_fb_in1k	.310
221	yudixie_resnet50_distance_translation_0_240908	.310
222	alexnet_training_seed_01_fov16	.304
223	compact_resnet50_IT	.304
224	yudixie_resnet50_distance_rotation_0_240908	.304
225	resnet50-moclr8deg	.304
226	eva02_large_in22k	.281
227	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.281
228	efficientnet_b0_imagenet_full	.281
229	ReAlnet01_cornet_fov16	.275
230	yudixie_resnet50_imagenet1kpret_0_240908	.275
231	mobilenet_v2_1_0_224	.275
232	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.275
233	densenet-121	.275
234	resnet50_imagenet_10_seed-0	.275
235	vit_base_patch14_reg4_dinov2-lvd142m	.254
236	densenet-201	.254
237	AdvProp_efficientnet-b6	.254
238	deit_small_imagenet_full_seed-0	.254
239	resnet50_barlowtwins_linhead	.249
240	predictive_coding_pc	.249
241	alexnet_training_seed_01_fov12	.249
242	resnet50_robust_l2_eps1	.249
243	BiT-S-R152x2	.249
244	deit_small_imagenet_1_seed-0	.249
245	alexnet	.249
246	mehrer2020_alexnet_training_seed_05	.230
247	yudixie_wbh_object_class_scaling_0415_run_2	.230
248	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.230
249	ReAlnet04_ALL	.230
250	resnet50-barlow	.230
251	AT_efficientnet-b2	.230
252	BiT-S-R152x4	.230
253	AdvProp_efficientnet-b2	.230
254	vonegrcnn_52e_full	.230
255	dinov2_vitl14_reg_lc_featread	.225
256	resnet_50_v1_spiking_l4	.225
257	alexnet_training_seed_08	.225
258	alexnet_training_seed_02	.225
259	alexnet_training_seed_09	.225
260	resnet_101_v1	.225
261	yudixie_resnet50_translation_rotation_0_240908	.225
262	yudixie_resnet18_distance_translation_rotation_0_240719	.225
263	yudixie_resnet18_translation_rotation_0_240719	.225
264	convnext_base_fb_in1k_gram_aligned_dinov3	.208
265	convnext_base_fb_in22k_ft_in1k	.208
266	mobilenet_v2_1_0_128	.208
267	resnet-152_v2_pytorch	.208
268	mehrer2020_alexnet_training_seed_01_fov12	.204
269	compact_vgg19_V4	.204
270	mobilenet_v2_1_0_192	.204
271	mobilenet_v2_1_0_160	.204
272	antialiased-r50	.204
273	mobilenet_v2_0_5_192	.189
274	alexnet_training_seed_06	.185
275	yudixie_resnet50_rotation_reg_0_240908	.185
276	convnext_tiny:in12k_ft_in1k	.185
277	cvt_cvt-21-224-in1k_4_LucyV4	.171
278	alexnet_fov16	.167
279	mehrer2020_alexnet_training_seed_01_fov16	.155
280	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.155
281	resnet50-vicregl0p75	.155
282	resnet50_st_wzc_2	.140
283	efficientnet_b1_imagenet_full	.140
284	alexnet_training_seed_07	.137
285	resnet50_tutorial	.137
286	deepeisnn_ei_cifar10_vgg19	.124
287	pnasnet_large_pytorch	.124
288	resnext101_32x8d_wsl	.102
289	gabor_filter_entropy_4x4_v2	.102
290	deepeisnn_ei_cifar10_resnet18	.102
291	pnasnet_large_halfPrecision	.083
292	BiT-S-R101x3	.083
293	gabor_filter_entropy_4x4	.076
294	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.076
295	convnext_small_imagenet_100_seed-0	.070
296	gabor_filter_entropy_4x4_v2_forcedCosine	.068
297	yudixie_resnet18_rotation_reg_0_240719	.068
298	yudixie_resnet18_category_class_0_240719	.068
299	resnet50_imagenet_1_seed-0	.068
300	pnasnet_large	.062
301	compact_resnet50_robust_V4	.051
302	compact_resnet50_V4	.051
303	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.035
304	yudixie_resnet50_translation_reg_0_240908	.034
305	resnet_50_v1_spiking	.025
306	yolos_tiny	.025
307	BiT-S-R101x1	.025
308	yudixie_resnet18_random_0_240719	.023
309	resnet50_ewconplus_wzc_seed5_2__323

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

0.85.

Note that scores are relative to this ceiling.

Data: Ferguson2024round_v

Metric: value_delta