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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	mobilenet_v2_0_5_224	1.0
2	yudixie_resnet50_translation_reg_0_240908	1.0
3	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
4	omnivore_swinB	1.0
5	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
6	resnet50_ewconplus_wzc_seed4_2_323	1.0
7	pnasnet_large_halfPrecision	1.0
8	resnet50_primary_visual_cortex	1.0
9	mobilenet_v2_0_75_160	1.0
10	cv_18_dagger_408_pretrained	1.0
11	alexnet_training_seed_04	1.0
12	resnet_50_v1	1.0
13	resnet50-sup	1.0
14	resnet50_ecoset_full	1.0
15	resnext101_32x8d_wsl	1.0
16	resnet_152_v1	.950
17	inception_v4	.950
18	mobilenet_v2_0_75_192	.950
19	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.950
20	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.950
21	convnext_large:fb_in22k_ft_in1k	.950
22	deit_large_imagenet_full_seed-0	.950
23	resnet34_ecoset_full	.950
24	resnet18_imagenet_full	.950
25	ViT_L_32_imagenet1k	.950
26	effnetb1_272x240	.950
27	BiT-S-R152x2	.923
28	resnet18_ecoset_full	.923
29	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.923
30	resnet_50_v1_spiking_l4a	.923
31	resnext101_32x48d_wsl	.923
32	cvt_cvt-21-224-in1k_4_LucyV4	.860
33	mobilenet_v2_1_0_224	.836
34	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.836
35	convnext_tiny:in12k_ft_in1k	.836
36	resnet_SIN_IN_FT_IN	.836
37	antialiased-r50	.836
38	resnet50_tutorial	.836
39	ReAlnet01_cornet_fov16	.836
40	vit_large_patch14_clip_336:laion2b_ft_in1k	.779
41	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.779
42	convnext_base_fb_in22k_ft_in1k	.757
43	yudixie_resnet50_category_class_0_240908	.757
44	grcnn	.757
45	efficientnet_b0	.757
46	deit_small_imagenet_1_seed-0	.757
47	resnet50_st_wzc_seed3_2_323	.757
48	ReAlnet01_cornet_fov4	.757
49	alexnet_training_seed_05	.706
50	BiT-S-R152x4	.706
51	yudixie_resnet18_distance_reg_0_240719	.706
52	yudixie_resnet18_imagenet1kpret_0_240719	.706
53	cvt_cvt-21-384-in1k_4_LucyV4	.706
54	resnet_50_v1_spiking	.686
55	yudixie_resnet50_distance_translation_rotation_0_240908	.686
56	resnet_50_v2	.686
57	AT_efficientnet-b2	.686
58	AdvProp_efficientnet-b2	.686
59	convnext_large_imagenet_full_seed-0	.686
60	convnext_base_imagenet_full_seed-0	.686
61	resnet18_fair	.686
62	voneresnet-50-non_stochastic	.686
63	convnext_xlarge:fb_in22k_ft_in1k	.639
64	predictive_coding_pc	.621
65	efficientnet-b7	.621
66	convnext_tiny_sup	.621
67	convnext_small_imagenet_full_seed-0	.621
68	resnet50_ewconplus_wzc_seed5_2__323	.621
69	artResNet18_1	.579
70	alexnet_training_seed_10	.563
71	alexnet_training_seed_06	.563
72	vonegrcnn_62e_nobn	.563
73	resnet50_robust_l2_eps3	.563
74	imagenet_l2_3_0	.563
75	AdvProp_efficientnet-b7	.563
76	efficientnet_b2_imagenet_full	.563
77	resnet50_imagenet_1_seed-0	.563
78	resnet50_st_wzc_2	.563
79	convnext_base_fb_in1k_gram_aligned_dinov3	.524
80	cvt_cvt-13-224-in1k_4_LucyV4	.524
81	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.524
82	vit_base_patch14_dinov2-lvd142m	.524
83	yudixie_resnet50_imagenet1kpret_0_240908	.510
84	mobilenet_v2_1_0_128	.510
85	vgg_16	.510
86	resnet50-SIN_IN_IN	.510
87	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.510
88	densenet-201	.510
89	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.510
90	resnet50_robust_l2_eps1	.510
91	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.510
92	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.510
93	densenet-121	.510
94	resnet50-vicregl0p75	.510
95	BiT-S-R50x3	.510
96	deit_base_imagenet_full_seed-0	.510
97	resnet50_imagenet_100_seed-0	.510
98	resnet101_imagenet_full	.510
99	vit_base_patch16_dinov3-lvd1689m	.510
100	ReAlnet01_cornet_fov12	.510
101	resnet50-vicreg	.475
102	BiT-S-R50x1	.475
103	deit_small_imagenet_full_seed-0	.475
104	custom_model_cv_18_dagger_408	.475
105	resnet_50_v1_spiking_l3	.475
106	resnext101_32x32d_wsl	.475
107	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.475
108	yudixie_wbh_object_class_scaling_0415_run_3	.461
109	inception_v3	.461
110	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.461
111	densenet-169	.461
112	vonegrcnn_47e	.461
113	resnet-152_v2_pytorch	.461
114	AlexNet_SIN	.461
115	mobilenet_v2_1_0_160	.430
116	yudixie_resnet50_rotation_reg_0_240908	.430
117	vit_relpos_base_patch16_clsgap_224:sw_in1k	.430
118	yudixie_resnet18_random_0_240719	.430
119	yudixie_wbh_object_class_scaling_0415_run_0	.418
120	deit3_base_patch16_224_fb_in22k_ft_in1k	.418
121	mobilenet_v2_0_5_192	.418
122	grcnn_109	.418
123	Res2Net50_26w_4s	.418
124	yudixie_resnet18_distance_rotation_0_240719	.418
125	resnet50_ewconplus_noseed_2_323	.418
126	vit_base_patch16_clip_224:openai_ft_in1k	.390
127	yudixie_resnet18_distance_translation_0_240719	.390
128	vit_large_patch14_clip_224:openai_ft_in1k	.379
129	convnext_base:clip_laiona_augreg_ft_in1k_384	.379
130	blt_vs	.379
131	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.379
132	resnet50_imagenet_10_seed-0	.379
133	focalnet_tiny_lrf_in1k	.379
134	resnet50_st_wzc_noseed_2_323	.379
135	alexnet_training_seed_01_fov4	.379
136	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.353
137	pr1_stl10_disentangled_alpha04	.343
138	xception	.343
139	yudixie_resnet18_distance_translation_rotation_0_240719	.343
140	resnet-18_test_m	.320
141	briaai_rmbg_1_4	.311
142	alexnet_training_seed_02	.311
143	ReAlnet05_cornet	.311
144	yudixie_resnet50_distance_rotation_0_240908	.311
145	ReAlnet05	.311
146	compact_resnet50_IT	.311
147	nasnet_mobile	.289
148	resnet152_ecoset_full	.289
149	deepeisnn_ei_imagenet_resnet18	.281
150	yudixie_resnet50_distance_translation_0_240908	.281
151	deit_small_imagenet_100_seed-0	.281
152	deit_small_imagenet_10_seed-0	.281
153	efficientnet_b1_imagenet_full	.281
154	alexnet_fov16	.281
155	alexnet_fov12	.281
156	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.262
157	cvt_cvt-13-384-in1k_4_LucyV4	.262
158	ReAlnet07_cornet	.255
159	vgg_19	.255
160	ReAlnet07	.255
161	resnet50-SIN	.255
162	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.255
163	resnet152_imagenet_full	.255
164	alexnet	.255
165	resnet50_st_wzc_seed4_2_323	.255
166	resnet50_ewconplus_wzc_seed6_2_323	.255
167	alexnet_training_seed_01_fov12	.255
168	compact_cornets_IT	.255
169	compact_cornets_V4	.255
170	deepeisnn_ei_cifar10_resnet18	.231
171	mobilenet_v2_1_4_224	.231
172	resnet50-barlow	.231
173	BiT-S-R101x3	.231
174	yudixie_resnet18_translation_rotation_0_240719	.231
175	resnet34_imagenet_full	.231
176	mobilenet_v2_1-4_224_pytorch	.231
177	resnet-50-robust	.231
178	AlexNet_SIN_fov12	.231
179	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.215
180	vit_base_patch14_reg4_dinov2-lvd142m	.215
181	yudixie_resnet50_distance_reg_0_240908	.209
182	ReAlnet10_cornet	.209
183	ReAlnet01_cornet	.209
184	ReAlnet10	.209
185	ReAlnet01	.209
186	VOneCORnet-S	.209
187	efficientnet_b0_imagenet_full	.209
188	alexnet_training_seed_01_fov16	.209
189	yudixie_wbh_object_class_scaling_0415_imagenet	.195
190	BiT-S-R101x1	.189
191	convnext_small_imagenet_1_seed-0	.189
192	resnet50_imagenet_full	.189
193	alexnet_fov4	.189
194	alexnet_training_seed_07	.171
195	ReAlnet09_cornet	.171
196	ReAlnet03_cornet	.171
197	resnet_101_v1	.171
198	inception_v1	.171
199	yudixie_resnet50_translation_rotation_0_240908	.171
200	ReAlnet09	.171
201	ReAlnet03	.171
202	shufflenet_v2_x1_0	.171
203	omnivore_swinS	.171
204	resnet101_ecoset_full	.171
205	resnet50_ewconplus_wzc	.171
206	ReAlnet04_cornet	.155
207	ReAlnet02_cornet	.155
208	resnet_152_v2	.155
209	ReAlnet02	.155
210	ReAlnet04	.155
211	voneresnet-50	.155
212	resnet50-vicregl0p9	.155
213	convnext_small_imagenet_10_seed-0	.155
214	yudixie_wbh_object_class_scaling_0415_run_1	.141
215	yudixie_resnet50_object_class_0_240908	.141
216	alexnet_training_seed_01	.141
217	ReAlnet06_cornet	.141
218	mobilenet_v2_1_0_192	.141
219	ReAlnet06	.141
220	resnet50-vitoimagevidnet8	.141
221	resnet50-VITO-8deg-cc	.141
222	convnext_femto_ols:d1_in1k	.141
223	AdvProp_efficientnet-b8	.141
224	convnext_small_imagenet_100_seed-0	.141
225	aughost_fair_resnet18	.141
226	AlexNet_SIN_fov16	.141
227	resnet_50_v1_spiking_l4	.127
228	yudixie_resnet50_random_0_240908	.127
229	ReAlnet08_cornet	.127
230	ReAlnet08	.127
231	compact_resnet50_robust_V4	.127
232	ReAlnet09_ALL	.127
233	pnasnet_large_pytorch	.127
234	resnet_101_v2	.119
235	yolos_tiny	.115
236	mobilenet_v2_1_3_224	.115
237	alexnet_training_seed_08	.115
238	resnet50_ewconplus_wzc_seed7_2_323	.115
239	compact_vgg19_IT	.115
240	AdvProp_efficientnet-b4	.115
241	deepeisnn_ei_cifar10_vgg19	.104
242	yudixie_resnet18_object_class_0_240719	.104
243	ReAlnet07_ALL	.104
244	alexnet_training_seed_03	.095
245	vonegrcnn_52e_full	.095
246	yudixie_resnet18_translation_reg_0_240719	.095
247	compact_resnet50_robust_IT	.095
248	ReAlnet08_ALL	.095
249	yudixie_resnet18_rotation_reg_0_240719	.086
250	alexnet_training_seed_09	.078
251	voneresnet-50-robust	.078
252	resnet50-SIN_IN	.078
253	compact_resnet50_V4	.078
254	ReAlnet03_ALL	.078
255	convnext_tiny_imagenet_full_seed-0	.070
256	ReAlnet04_ALL	.070
257	resnet50-moclr8deg	.064
258	yudixie_resnet18_category_class_0_240719	.064
259	ReAlnet05_ALL	.064
260	ReAlnet01_ALL	.064
261	resnet50_ewconplus_wzc_2_323	.058
262	ReAlnet10_ALL	.058
263	yudixie_wbh_object_class_scaling_0415_run_2	.052
264	ReAlnet06_ALL	.052
265	nasnet_large	.047
266	AdvProp_efficientnet-b6	.043
267	compact_vgg19_V4	.043
268	AlexNet_SIN_fov4	.021
269	ReAlnet02_ALL	.019
270	pnasnet_large
271	mobilenet_v2_0_75_224
272	hmax
273	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