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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024quarter-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	eva02_large_in22k	1.0
2	mobilenet_v2_0_5_224	1.0
3	yudixie_resnet50_translation_reg_0_240908	1.0
4	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
5	omnivore_swinB	1.0
6	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
7	pnasnet_large_halfPrecision	1.0
8	resnet50_vicreg_linhead	1.0
9	mehrer2020_alexnet_training_seed_01_fov12	1.0
10	resnet50_primary_visual_cortex	1.0
11	mobilenet_v2_0_75_160	1.0
12	cv_18_dagger_408_pretrained	1.0
13	alexnet_training_seed_04	1.0
14	resnet_50_v1	1.0
15	resnet50-sup	1.0
16	resnet50_ecoset_full	1.0
17	resnext101_32x8d_wsl	1.0
18	resnet50_simsiam_linhead	.950
19	resnet_152_v1	.950
20	inception_v4	.950
21	mobilenet_v2_0_75_192	.950
22	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.950
23	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.950
24	convnext_large:fb_in22k_ft_in1k	.950
25	deit_large_imagenet_full_seed-0	.950
26	resnet34_ecoset_full	.950
27	resnet18_imagenet_full	.950
28	ViT_L_32_imagenet1k	.950
29	effnetb1_272x240	.950
30	convnext_xxlarge_clip	.923
31	BiT-S-R152x2	.923
32	resnet18_ecoset_full	.923
33	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.923
34	resnet_50_v1_spiking_l4a	.923
35	resnext101_32x48d_wsl	.923
36	cvt_cvt-21-224-in1k_4_LucyV4	.860
37	ijepa_vith14_linhead	.836
38	seresnext50_32x4d	.836
39	dinov2_vitl14_reg_lc	.836
40	mobilenet_v2_1_0_224	.836
41	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.836
42	convnext_tiny:in12k_ft_in1k	.836
43	resnet_SIN_IN_FT_IN	.836
44	antialiased-r50	.836
45	resnet50_tutorial	.836
46	ReAlnet01_cornet_fov16	.836
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.779
48	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.779
49	mehrer2020_alexnet_training_seed_06	.757
50	convnext_base_fb_in22k_ft_in1k	.757
51	yudixie_resnet50_category_class_0_240908	.757
52	grcnn	.757
53	efficientnet_b0	.757
54	deit_small_imagenet_1_seed-0	.757
55	resnet50_st_wzc_seed3_2_323	.757
56	ReAlnet01_cornet_fov4	.757
57	resnet50_hvs_wzc	.757
58	dinov2_vitl14_lc_res336	.706
59	alexnet_training_seed_05	.706
60	BiT-S-R152x4	.706
61	yudixie_resnet18_distance_reg_0_240719	.706
62	yudixie_resnet18_imagenet1kpret_0_240719	.706
63	cvt_cvt-21-384-in1k_4_LucyV4	.706
64	resnet_50_v1_spiking	.686
65	yudixie_resnet50_distance_translation_rotation_0_240908	.686
66	resnet_50_v2	.686
67	AT_efficientnet-b2	.686
68	AdvProp_efficientnet-b2	.686
69	convnext_large_imagenet_full_seed-0	.686
70	convnext_base_imagenet_full_seed-0	.686
71	resnet18_fair	.686
72	voneresnet-50-non_stochastic	.686
73	convnext_xlarge:fb_in22k_ft_in1k	.639
74	resnet50_byol_linhead	.621
75	mehrer2020_alexnet_training_seed_09	.621
76	mehrer2020_alexnet_training_seed_07	.621
77	convnext_large_clip_laion2b_finelayers	.621
78	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.621
79	predictive_coding_pc	.621
80	efficientnet-b7	.621
81	convnext_tiny_sup	.621
82	convnext_small_imagenet_full_seed-0	.621
83	resnet50_ewconplus_wzc_seed5_2__323	.621
84	artResNet18_1	.579
85	resnet50_simclr_linhead_01norm	.563
86	alexnet_training_seed_10	.563
87	alexnet_training_seed_06	.563
88	vonegrcnn_62e_nobn	.563
89	resnet50_robust_l2_eps3	.563
90	imagenet_l2_3_0	.563
91	AdvProp_efficientnet-b7	.563
92	efficientnet_b2_imagenet_full	.563
93	resnet50_imagenet_1_seed-0	.563
94	resnet50_st_wzc_2	.563
95	dinov2_vitg14_reg_lc	.524
96	convnext_large_in22k_supervised	.524
97	convnext_base_fb_in1k_gram_aligned_dinov3	.524
98	cvt_cvt-13-224-in1k_4_LucyV4	.524
99	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.524
100	vit_base_patch14_dinov2-lvd142m	.524
101	gabor_filter_mean_abs_4x4_v2	.510
102	vit_huge_clip336_laion	.510
103	vit_large_clip336_openai	.510
104	dinov2_vitl14_reg_lc_featread	.510
105	yudixie_resnet50_imagenet1kpret_0_240908	.510
106	mobilenet_v2_1_0_128	.510
107	vgg_16	.510
108	resnet50-SIN_IN_IN	.510
109	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.510
110	densenet-201	.510
111	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.510
112	resnet50_robust_l2_eps1	.510
113	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.510
114	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.510
115	densenet-121	.510
116	resnet50-vicregl0p75	.510
117	BiT-S-R50x3	.510
118	deit_base_imagenet_full_seed-0	.510
119	resnet50_imagenet_100_seed-0	.510
120	resnet101_imagenet_full	.510
121	vit_base_patch16_dinov3-lvd1689m	.510
122	ReAlnet01_cornet_fov12	.510
123	resnet50-vicreg	.475
124	BiT-S-R50x1	.475
125	deit_small_imagenet_full_seed-0	.475
126	custom_model_cv_18_dagger_408	.475
127	resnet_50_v1_spiking_l3	.475
128	resnext101_32x32d_wsl	.475
129	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.475
130	yudixie_wbh_object_class_scaling_0415_run_3	.461
131	inception_v3	.461
132	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.461
133	densenet-169	.461
134	vonegrcnn_47e	.461
135	resnet-152_v2_pytorch	.461
136	AlexNet_SIN	.461
137	mobilenet_v2_1_0_160	.430
138	yudixie_resnet50_rotation_reg_0_240908	.430
139	vit_relpos_base_patch16_clsgap_224:sw_in1k	.430
140	yudixie_resnet18_random_0_240719	.430
141	gabor_filter_entropy_4x4_v2_forcedCosine	.418
142	yudixie_wbh_object_class_scaling_0415_run_0	.418
143	deit3_base_patch16_224_fb_in22k_ft_in1k	.418
144	mobilenet_v2_0_5_192	.418
145	grcnn_109	.418
146	Res2Net50_26w_4s	.418
147	yudixie_resnet18_distance_rotation_0_240719	.418
148	vit_base_patch16_clip_224:openai_ft_in1k	.390
149	yudixie_resnet18_distance_translation_0_240719	.390
150	vit_large_patch14_clip_224:openai_ft_in1k	.379
151	convnext_base:clip_laiona_augreg_ft_in1k_384	.379
152	blt_vs	.379
153	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.379
154	resnet50_imagenet_10_seed-0	.379
155	focalnet_tiny_lrf_in1k	.379
156	alexnet_training_seed_01_fov4	.379
157	dinov2_vitg14_lc	.353
158	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.353
159	mehrer2020_alexnet_training_seed_01	.343
160	pr1_stl10_disentangled_alpha04	.343
161	xception	.343
162	yudixie_resnet18_distance_translation_rotation_0_240719	.343
163	dinov2_vitl14_lc	.320
164	resnet-18_test_m	.320
165	briaai_rmbg_1_4	.311
166	alexnet_training_seed_02	.311
167	ReAlnet05_cornet	.311
168	yudixie_resnet50_distance_rotation_0_240908	.311
169	ReAlnet05	.311
170	compact_resnet50_IT	.311
171	nasnet_mobile	.289
172	resnet152_ecoset_full	.289
173	deepeisnn_ei_imagenet_resnet18	.281
174	yudixie_resnet50_distance_translation_0_240908	.281
175	deit_small_imagenet_100_seed-0	.281
176	deit_small_imagenet_10_seed-0	.281
177	efficientnet_b1_imagenet_full	.281
178	hmax	.281
179	alexnet_fov16	.281
180	alexnet_fov12	.281
181	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.262
182	cvt_cvt-13-384-in1k_4_LucyV4	.262
183	mehrer2020_alexnet_training_seed_08	.255
184	eicircuit_resnet18_bn_20260919	.255
185	gabor_filter_entropy_4x4_v2	.255
186	ReAlnet07_cornet	.255
187	vgg_19	.255
188	ReAlnet07	.255
189	resnet50-SIN	.255
190	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.255
191	resnet152_imagenet_full	.255
192	alexnet	.255
193	resnet50_ewconplus_wzc_seed6_2_323	.255
194	alexnet_training_seed_01_fov12	.255
195	compact_cornets_IT	.255
196	compact_cornets_V4	.255
197	deepeisnn_ei_cifar10_resnet18	.231
198	mobilenet_v2_1_4_224	.231
199	resnet50-barlow	.231
200	BiT-S-R101x3	.231
201	yudixie_resnet18_translation_rotation_0_240719	.231
202	resnet34_imagenet_full	.231
203	mobilenet_v2_1-4_224_pytorch	.231
204	resnet-50-robust	.231
205	AlexNet_SIN_fov12	.231
206	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.215
207	vit_base_patch14_reg4_dinov2-lvd142m	.215
208	regnety_032	.209
209	yudixie_resnet50_distance_reg_0_240908	.209
210	ReAlnet10_cornet	.209
211	ReAlnet01_cornet	.209
212	ReAlnet10	.209
213	ReAlnet01	.209
214	VOneCORnet-S	.209
215	efficientnet_b0_imagenet_full	.209
216	alexnet_training_seed_01_fov16	.209
217	yudixie_wbh_object_class_scaling_0415_imagenet	.195
218	BiT-S-R101x1	.189
219	convnext_small_imagenet_1_seed-0	.189
220	resnet50_imagenet_full	.189
221	alexnet_fov4	.189
222	alexnet_training_seed_07	.171
223	ReAlnet09_cornet	.171
224	ReAlnet03_cornet	.171
225	resnet_101_v1	.171
226	inception_v1	.171
227	yudixie_resnet50_translation_rotation_0_240908	.171
228	ReAlnet09	.171
229	ReAlnet03	.171
230	shufflenet_v2_x1_0	.171
231	omnivore_swinS	.171
232	resnet101_ecoset_full	.171
233	resnet50_ewconplus_wzc	.171
234	mehrer2020_alexnet_training_seed_03	.155
235	ReAlnet04_cornet	.155
236	ReAlnet02_cornet	.155
237	resnet_152_v2	.155
238	ReAlnet02	.155
239	ReAlnet04	.155
240	voneresnet-50	.155
241	resnet50-vicregl0p9	.155
242	convnext_small_imagenet_10_seed-0	.155
243	yudixie_wbh_object_class_scaling_0415_run_1	.141
244	yudixie_resnet50_object_class_0_240908	.141
245	alexnet_training_seed_01	.141
246	ReAlnet06_cornet	.141
247	mobilenet_v2_1_0_192	.141
248	ReAlnet06	.141
249	resnet50-vitoimagevidnet8	.141
250	resnet50-VITO-8deg-cc	.141
251	convnext_femto_ols:d1_in1k	.141
252	AdvProp_efficientnet-b8	.141
253	convnext_small_imagenet_100_seed-0	.141
254	AlexNet_SIN_fov16	.141
255	resnext101_32x16d_wsl	.127
256	resnet_50_v1_spiking_l4	.127
257	yudixie_resnet50_random_0_240908	.127
258	ReAlnet08_cornet	.127
259	ReAlnet08	.127
260	compact_resnet50_robust_V4	.127
261	ReAlnet09_ALL	.127
262	pnasnet_large_pytorch	.127
263	resnet_101_v2	.119
264	mehrer2020_alexnet_training_seed_01_fov4	.115
265	yolos_tiny	.115
266	mobilenet_v2_1_3_224	.115
267	alexnet_training_seed_08	.115
268	compact_vgg19_IT	.115
269	AdvProp_efficientnet-b4	.115
270	deepeisnn_ei_cifar10_vgg19	.104
271	yudixie_resnet18_object_class_0_240719	.104
272	ReAlnet07_ALL	.104
273	alexnet_training_seed_03	.095
274	vonegrcnn_52e_full	.095
275	yudixie_resnet18_translation_reg_0_240719	.095
276	compact_resnet50_robust_IT	.095
277	ReAlnet08_ALL	.095
278	mehrer2020_alexnet_training_seed_10	.086
279	yudixie_resnet18_rotation_reg_0_240719	.086
280	alexnet_training_seed_09	.078
281	voneresnet-50-robust	.078
282	resnet50-SIN_IN	.078
283	compact_resnet50_V4	.078
284	ReAlnet03_ALL	.078
285	resnet50_barlowtwins_linhead	.070
286	mehrer2020_alexnet_training_seed_05	.070
287	convnext_tiny_imagenet_full_seed-0	.070
288	ReAlnet04_ALL	.070
289	mehrer2020_alexnet_training_seed_01_fov16	.064
290	resnet50-moclr8deg	.064
291	yudixie_resnet18_category_class_0_240719	.064
292	ReAlnet05_ALL	.064
293	ReAlnet01_ALL	.064
294	ReAlnet10_ALL	.058
295	gabor_filter_entropy_4x4	.052
296	yudixie_wbh_object_class_scaling_0415_run_2	.052
297	ReAlnet06_ALL	.052
298	mehrer2020_alexnet_training_seed_02	.047
299	nasnet_large	.047
300	AdvProp_efficientnet-b6	.043
301	compact_vgg19_V4	.043
302	mehrer2020_alexnet_training_seed_04	.032
303	AlexNet_SIN_fov4	.021
304	ReAlnet02_ALL	.019
305	pnasnet_large
306	mobilenet_v2_0_75_224
307	convnext_base_fb_in1k

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

0.88.

Note that scores are relative to this ceiling.

Data: Ferguson2024quarter

Metric: value_delta