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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024juncture-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50-vitoimagevidnet8	1.0
2	resnet50-VITO-8deg-cc	1.0
3	resnet18_ecoset_full	1.0
4	ReAlnet04	1.0
5	efficientnet_b1_imagenet_full	1.0
6	ReAlnet04_cornet	1.0
7	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.984
8	resnet34_ecoset_full	.984
9	resnet50-vicreg	.984
10	AdvProp_efficientnet-b6	.951
11	convnext_small_imagenet_full_seed-0	.951
12	vonegrcnn_47e	.951
13	ReAlnet08	.848
14	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.848
15	ReAlnet08_cornet	.848
16	convnext_base:clip_laiona_augreg_ft_in1k_384	.848
17	yudixie_resnet18_distance_translation_rotation_0_240719	.819
18	yudixie_resnet50_rotation_reg_0_240908	.819
19	shufflenet_v2_x1_0	.819
20	vgg_19	.819
21	cvt_cvt-13-224-in1k_4_LucyV4	.730
22	resnext101_32x32d_wsl	.730
23	nasnet_large	.730
24	efficientnet_b0	.730
25	ReAlnet10	.706
26	ReAlnet01_cornet	.706
27	convnext_small_imagenet_10_seed-0	.706
28	resnet50_imagenet_100_seed-0	.706
29	ReAlnet01_ALL	.706
30	ReAlnet02_ALL	.706
31	ReAlnet01	.706
32	ReAlnet10_cornet	.706
33	vonegrcnn_52e_full	.706
34	deit_small_imagenet_full_seed-0	.629
35	convnext_large_imagenet_full_seed-0	.608
36	resnet152_imagenet_full	.608
37	pnasnet_large	.608
38	mobilenet_v2_1_3_224	.608
39	antialiased-r50	.608
40	convnext_tiny_sup	.608
41	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.524
42	resnet50_imagenet_10_seed-0	.524
43	vit_relpos_base_patch16_clsgap_224:sw_in1k	.524
44	resnet_50_v1_spiking_l4a	.524
45	yudixie_resnet50_distance_reg_0_240908	.524
46	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
47	resnet101_ecoset_full	.524
48	ReAlnet06	.467
49	ReAlnet06_cornet	.467
50	convnext_tiny_imagenet_full_seed-0	.451
51	resnet50-SIN_IN_IN	.451
52	ReAlnet09_ALL	.451
53	yudixie_resnet50_category_class_0_240908	.389
54	resnext101_32x48d_wsl	.389
55	focalnet_tiny_lrf_in1k	.389
56	inception_v1	.389
57	ReAlnet04_ALL	.389
58	AdvProp_efficientnet-b2	.389
59	AT_efficientnet-b2	.389
60	mobilenet_v2_1-4_224_pytorch	.346
61	mobilenet_v2_1_4_224	.346
62	resnet50-vicregl0p75	.346
63	ReAlnet05	.335
64	yudixie_resnet18_distance_rotation_0_240719	.335
65	ReAlnet05_cornet	.335
66	resnet50_robust_l2_eps1	.335
67	resnet_50_v1	.335
68	resnet50-sup	.335
69	AdvProp_efficientnet-b4	.335
70	convnext_femto_ols:d1_in1k	.335
71	mobilenet_v2_0_5_192	.298
72	resnet50-SIN_IN	.298
73	mobilenet_v2_1_0_192	.288
74	convnext_small_imagenet_1_seed-0	.288
75	resnext101_32x8d_wsl	.288
76	resnet50-vicregl0p9	.288
77	resnet_152_v1	.288
78	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.257
79	resnet50_imagenet_full	.248
80	mobilenet_v2_0_75_224	.248
81	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.248
82	resnet50_tutorial	.248
83	ReAlnet03_ALL	.248
84	ReAlnet06_ALL	.248
85	convnext_small_imagenet_100_seed-0	.214
86	Res2Net50_26w_4s	.214
87	ReAlnet03	.191
88	ReAlnet03_cornet	.191
89	yudixie_resnet50_distance_rotation_0_240908	.191
90	convnext_xlarge:fb_in22k_ft_in1k	.184
91	cvt_cvt-21-224-in1k_4_LucyV4	.184
92	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.184
93	voneresnet-50-non_stochastic	.184
94	resnet-152_v2_pytorch	.184
95	resnet50_ecoset_full	.184
96	xception	.184
97	deit_small_imagenet_1_seed-0	.184
98	VOneCORnet-S	.184
99	resnet50-moclr8deg	.184
100	BiT-S-R50x1	.184
101	resnet50-SIN	.164
102	resnet_50_v2	.159
103	efficientnet_b2_imagenet_full	.159
104	custom_model_cv_18_dagger_408	.159
105	yudixie_resnet18_distance_translation_0_240719	.159
106	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.159
107	ReAlnet08_ALL	.159
108	alexnet_training_seed_03	.159
109	mobilenet_v2_1_0_160	.137
110	resnet152_ecoset_full	.137
111	resnet-50-robust	.137
112	yudixie_resnet18_object_class_0_240719	.137
113	nasnet_mobile	.137
114	omnivore_swinS	.137
115	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.118
116	yudixie_resnet50_object_class_0_240908	.118
117	deit_base_imagenet_full_seed-0	.118
118	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.118
119	yolos_tiny	.118
120	ViT_L_32_imagenet1k	.118
121	briaai_rmbg_1_4	.118
122	yudixie_resnet50_random_0_240908	.118
123	yudixie_resnet50_imagenet1kpret_0_240908	.118
124	resnet50_primary_visual_cortex	.118
125	convnext_tiny:in12k_ft_in1k	.105
126	resnet_50_v1_spiking	.102
127	resnet34_imagenet_full	.102
128	efficientnet_b0_imagenet_full	.102
129	convnext_base_imagenet_full_seed-0	.102
130	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.102
131	vit_base_patch16_clip_224:openai_ft_in1k	.102
132	yudixie_resnet18_distance_reg_0_240719	.102
133	voneresnet-50-robust	.102
134	imagenet_l2_3_0	.102
135	resnet50_robust_l2_eps3	.102
136	BiT-S-R152x2	.102
137	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.087
138	AdvProp_efficientnet-b8	.087
139	convnext_large:fb_in22k_ft_in1k	.087
140	resnet18_imagenet_full	.078
141	ReAlnet07	.075
142	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.075
143	ReAlnet09	.075
144	deit_small_imagenet_10_seed-0	.075
145	yudixie_resnet18_imagenet1kpret_0_240719	.075
146	ReAlnet07_cornet	.075
147	ReAlnet09_cornet	.075
148	grcnn_109	.075
149	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.065
150	vit_large_patch14_clip_224:laion2b_ft_in1k	.065
151	inception_v4	.065
152	resnet_50_v1_spiking_l3	.065
153	resnet50-barlow	.065
154	vonegrcnn_62e_nobn	.065
155	ReAlnet07_ALL	.065
156	yudixie_resnet50_distance_translation_rotation_0_240908	.065
157	BiT-S-R50x3	.065
158	pnasnet_large_pytorch	.056
159	mobilenet_v2_0_75_192	.056
160	resnet101_imagenet_full	.056
161	resnet_101_v2	.056
162	AdvProp_efficientnet-b7	.056
163	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.048
164	mobilenet_v2_1_0_128	.048
165	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.048
166	ReAlnet05_ALL	.048
167	resnet_SIN_IN_FT_IN	.048
168	densenet-169	.048
169	resnet_50_v1_spiking_l4	.041
170	alexnet_training_seed_07	.041
171	efficientnet-b7	.041
172	yudixie_resnet50_distance_translation_0_240908	.041
173	BiT-S-R101x1	.041
174	yudixie_resnet18_translation_rotation_0_240719	.036
175	yudixie_resnet50_translation_rotation_0_240908	.036
176	voneresnet-50	.036
177	resnet-18_test_m	.031
178	grcnn	.031
179	resnet_152_v2	.031
180	BiT-S-R101x3	.031
181	densenet-201	.027
182	mobilenet_v2_0_75_160	.027
183	yudixie_resnet18_category_class_0_240719	.027
184	yudixie_resnet18_random_0_240719	.027
185	ReAlnet02_cornet	.023
186	ReAlnet02	.023
187	alexnet_training_seed_09	.020
188	vit_large_patch14_clip_224:openai_ft_in1k	.020
189	alexnet_training_seed_04	.020
190	resnet_101_v1	.020
191	alexnet_training_seed_10	.017
192	yudixie_resnet18_translation_reg_0_240719	.017
193	inception_v3	.015
194	deit_large_imagenet_full_seed-0	.015
195	resnet50_imagenet_1_seed-0	.015
196	alexnet_training_seed_01	.015
197	alexnet_training_seed_02	.013
198	mobilenet_v2_0_5_224	.013
199	yudixie_resnet18_rotation_reg_0_240719	.013
200	omnivore_swinB	.013
201	densenet-121	.013
202	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.011
203	vit_large_patch14_clip_336:laion2b_ft_in1k	.011
204	alexnet_training_seed_06	.009
205	yudixie_resnet50_translation_reg_0_240908	.009
206	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.009
207	ReAlnet10_ALL	.008
208	vgg_16	.008
209	deit_small_imagenet_100_seed-0	.006
210	cvt_cvt-13-384-in1k_4_LucyV4	.006
211	artResNet18_1	.005
212	effnetb1_272x240	.004
213	alexnet_training_seed_05	.004
214	BiT-S-R152x4	.004
215	blt_vs	.003
216	alexnet_training_seed_08	.003
217	cvt_cvt-21-384-in1k_4_LucyV4	.002
218	hmax
219	mobilenet_v2_1_0_224

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

0.77.

Note that scores are relative to this ceiling.

Data: Ferguson2024juncture

Metric: value_delta