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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	resnet50_ewconplus_wzc	1.0
5	ReAlnet04	1.0
6	efficientnet_b1_imagenet_full	1.0
7	ReAlnet04_cornet	1.0
8	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.984
9	resnet34_ecoset_full	.984
10	resnet50-vicreg	.984
11	AdvProp_efficientnet-b6	.951
12	convnext_small_imagenet_full_seed-0	.951
13	vonegrcnn_47e	.951
14	ReAlnet08	.848
15	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.848
16	ReAlnet08_cornet	.848
17	convnext_base:clip_laiona_augreg_ft_in1k_384	.848
18	yudixie_resnet18_distance_translation_rotation_0_240719	.819
19	yudixie_resnet50_rotation_reg_0_240908	.819
20	shufflenet_v2_x1_0	.819
21	vgg_19	.819
22	cvt_cvt-13-224-in1k_4_LucyV4	.730
23	resnext101_32x32d_wsl	.730
24	nasnet_large	.730
25	efficientnet_b0	.730
26	ReAlnet10	.706
27	ReAlnet01_cornet	.706
28	convnext_small_imagenet_10_seed-0	.706
29	resnet50_imagenet_100_seed-0	.706
30	ReAlnet01_ALL	.706
31	ReAlnet02_ALL	.706
32	ReAlnet01	.706
33	ReAlnet10_cornet	.706
34	vonegrcnn_52e_full	.706
35	deit_small_imagenet_full_seed-0	.629
36	convnext_large_imagenet_full_seed-0	.608
37	resnet152_imagenet_full	.608
38	pnasnet_large	.608
39	mobilenet_v2_1_3_224	.608
40	antialiased-r50	.608
41	convnext_tiny_sup	.608
42	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.524
43	resnet50_imagenet_10_seed-0	.524
44	vit_relpos_base_patch16_clsgap_224:sw_in1k	.524
45	resnet_50_v1_spiking_l4a	.524
46	yudixie_resnet50_distance_reg_0_240908	.524
47	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
48	resnet101_ecoset_full	.524
49	ReAlnet06	.467
50	ReAlnet06_cornet	.467
51	convnext_tiny_imagenet_full_seed-0	.451
52	resnet50-SIN_IN_IN	.451
53	ReAlnet09_ALL	.451
54	yudixie_resnet50_category_class_0_240908	.389
55	resnext101_32x48d_wsl	.389
56	focalnet_tiny_lrf_in1k	.389
57	inception_v1	.389
58	ReAlnet04_ALL	.389
59	AdvProp_efficientnet-b2	.389
60	AT_efficientnet-b2	.389
61	mobilenet_v2_1-4_224_pytorch	.346
62	mobilenet_v2_1_4_224	.346
63	resnet50-vicregl0p75	.346
64	ReAlnet05	.335
65	yudixie_resnet18_distance_rotation_0_240719	.335
66	ReAlnet05_cornet	.335
67	resnet50_robust_l2_eps1	.335
68	resnet_50_v1	.335
69	resnet50-sup	.335
70	AdvProp_efficientnet-b4	.335
71	convnext_femto_ols:d1_in1k	.335
72	mobilenet_v2_0_5_192	.298
73	resnet50-SIN_IN	.298
74	mobilenet_v2_1_0_192	.288
75	convnext_small_imagenet_1_seed-0	.288
76	resnext101_32x8d_wsl	.288
77	resnet50-vicregl0p9	.288
78	resnet_152_v1	.288
79	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.257
80	resnet50_imagenet_full	.248
81	mobilenet_v2_0_75_224	.248
82	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.248
83	resnet50_tutorial	.248
84	ReAlnet03_ALL	.248
85	ReAlnet06_ALL	.248
86	convnext_small_imagenet_100_seed-0	.214
87	Res2Net50_26w_4s	.214
88	ReAlnet03	.191
89	ReAlnet03_cornet	.191
90	yudixie_resnet50_distance_rotation_0_240908	.191
91	convnext_xlarge:fb_in22k_ft_in1k	.184
92	cvt_cvt-21-224-in1k_4_LucyV4	.184
93	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.184
94	voneresnet-50-non_stochastic	.184
95	resnet-152_v2_pytorch	.184
96	resnet50_ecoset_full	.184
97	xception	.184
98	deit_small_imagenet_1_seed-0	.184
99	VOneCORnet-S	.184
100	resnet50-moclr8deg	.184
101	BiT-S-R50x1	.184
102	resnet50-SIN	.164
103	resnet_50_v2	.159
104	efficientnet_b2_imagenet_full	.159
105	custom_model_cv_18_dagger_408	.159
106	yudixie_resnet18_distance_translation_0_240719	.159
107	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.159
108	compact_vgg19_IT	.159
109	ReAlnet08_ALL	.159
110	alexnet_training_seed_03	.159
111	mobilenet_v2_1_0_160	.137
112	resnet152_ecoset_full	.137
113	resnet-50-robust	.137
114	yudixie_resnet18_object_class_0_240719	.137
115	nasnet_mobile	.137
116	omnivore_swinS	.137
117	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.118
118	yudixie_resnet50_object_class_0_240908	.118
119	deit_base_imagenet_full_seed-0	.118
120	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.118
121	yolos_tiny	.118
122	ViT_L_32_imagenet1k	.118
123	briaai_rmbg_1_4	.118
124	yudixie_resnet50_random_0_240908	.118
125	yudixie_resnet50_imagenet1kpret_0_240908	.118
126	resnet50_primary_visual_cortex	.118
127	convnext_tiny:in12k_ft_in1k	.105
128	resnet_50_v1_spiking	.102
129	resnet34_imagenet_full	.102
130	efficientnet_b0_imagenet_full	.102
131	convnext_base_imagenet_full_seed-0	.102
132	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.102
133	vit_base_patch16_clip_224:openai_ft_in1k	.102
134	yudixie_resnet18_distance_reg_0_240719	.102
135	voneresnet-50-robust	.102
136	imagenet_l2_3_0	.102
137	resnet50_robust_l2_eps3	.102
138	BiT-S-R152x2	.102
139	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.087
140	AdvProp_efficientnet-b8	.087
141	convnext_large:fb_in22k_ft_in1k	.087
142	resnet18_imagenet_full	.078
143	ReAlnet07	.075
144	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.075
145	ReAlnet09	.075
146	deit_small_imagenet_10_seed-0	.075
147	yudixie_resnet18_imagenet1kpret_0_240719	.075
148	ReAlnet07_cornet	.075
149	ReAlnet09_cornet	.075
150	grcnn_109	.075
151	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.065
152	vit_large_patch14_clip_224:laion2b_ft_in1k	.065
153	inception_v4	.065
154	resnet_50_v1_spiking_l3	.065
155	resnet50-barlow	.065
156	vonegrcnn_62e_nobn	.065
157	ReAlnet07_ALL	.065
158	yudixie_resnet50_distance_translation_rotation_0_240908	.065
159	BiT-S-R50x3	.065
160	pnasnet_large_pytorch	.056
161	mobilenet_v2_0_75_192	.056
162	resnet101_imagenet_full	.056
163	resnet_101_v2	.056
164	AdvProp_efficientnet-b7	.056
165	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.048
166	mobilenet_v2_1_0_128	.048
167	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.048
168	ReAlnet05_ALL	.048
169	resnet_SIN_IN_FT_IN	.048
170	densenet-169	.048
171	resnet_50_v1_spiking_l4	.041
172	alexnet_training_seed_07	.041
173	efficientnet-b7	.041
174	yudixie_resnet50_distance_translation_0_240908	.041
175	BiT-S-R101x1	.041
176	yudixie_resnet18_translation_rotation_0_240719	.036
177	yudixie_resnet50_translation_rotation_0_240908	.036
178	voneresnet-50	.036
179	resnet-18_test_m	.031
180	grcnn	.031
181	resnet_152_v2	.031
182	BiT-S-R101x3	.031
183	densenet-201	.027
184	mobilenet_v2_0_75_160	.027
185	yudixie_resnet18_category_class_0_240719	.027
186	yudixie_resnet18_random_0_240719	.027
187	ReAlnet02_cornet	.023
188	ReAlnet02	.023
189	alexnet_training_seed_09	.020
190	vit_large_patch14_clip_224:openai_ft_in1k	.020
191	alexnet_training_seed_04	.020
192	resnet_101_v1	.020
193	compact_resnet50_robust_IT	.020
194	alexnet_training_seed_10	.017
195	yudixie_resnet18_translation_reg_0_240719	.017
196	inception_v3	.015
197	deit_large_imagenet_full_seed-0	.015
198	resnet50_imagenet_1_seed-0	.015
199	alexnet_training_seed_01	.015
200	compact_vgg19_V4	.015
201	alexnet_training_seed_02	.013
202	mobilenet_v2_0_5_224	.013
203	yudixie_resnet18_rotation_reg_0_240719	.013
204	omnivore_swinB	.013
205	densenet-121	.013
206	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.011
207	vit_large_patch14_clip_336:laion2b_ft_in1k	.011
208	compact_cornets_V4	.011
209	alexnet_training_seed_06	.009
210	yudixie_resnet50_translation_reg_0_240908	.009
211	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.009
212	ReAlnet10_ALL	.008
213	compact_resnet50_IT	.008
214	vgg_16	.008
215	deit_small_imagenet_100_seed-0	.006
216	cvt_cvt-13-384-in1k_4_LucyV4	.006
217	artResNet18_1	.005
218	effnetb1_272x240	.004
219	compact_resnet50_V4	.004
220	alexnet_training_seed_05	.004
221	BiT-S-R152x4	.004
222	blt_vs	.003
223	alexnet_training_seed_08	.003
224	compact_cornets_IT	.003
225	cvt_cvt-21-384-in1k_4_LucyV4	.002
226	compact_resnet50_robust_V4	.001
227	hmax
228	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