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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_ewconplus_wzc_2_323	1.0
2	alexnet_fov16	1.0
3	resnet50-vitoimagevidnet8	1.0
4	resnet50-VITO-8deg-cc	1.0
5	resnet50_ewconplus_wzc	1.0
6	resnet18_ecoset_full	1.0
7	ReAlnet04_cornet	1.0
8	ReAlnet04	1.0
9	efficientnet_b1_imagenet_full	1.0
10	resnet50-vicreg	.984
11	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.984
12	resnet34_ecoset_full	.984
13	resnet50_st_wzc_seed3_2_323	.951
14	vonegrcnn_47e	.951
15	AdvProp_efficientnet-b6	.951
16	convnext_small_imagenet_full_seed-0	.951
17	resnet50_st_wzc_seed5_2_323	.848
18	resnet50_ewconplus_wzc_seed4_2_323	.848
19	cv_18_dagger_408_pretrained	.848
20	ReAlnet08_cornet	.848
21	ReAlnet08	.848
22	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.848
23	convnext_base:clip_laiona_augreg_ft_in1k_384	.848
24	convnext_base_fb_in1k	.819
25	resnet50_ewconplus_wzc_seed5_2__323	.819
26	ReAlnet01_cornet_fov16	.819
27	vgg_19	.819
28	yudixie_resnet50_rotation_reg_0_240908	.819
29	shufflenet_v2_x1_0	.819
30	yudixie_resnet18_distance_translation_rotation_0_240719	.819
31	ReAlnet01_cornet_fov4	.730
32	nasnet_large	.730
33	efficientnet_b0	.730
34	cvt_cvt-13-224-in1k_4_LucyV4	.730
35	resnext101_32x32d_wsl	.730
36	yudixie_wbh_object_class_scaling_0415_run_0	.706
37	ReAlnet02_ALL	.706
38	ReAlnet01_ALL	.706
39	ReAlnet10_cornet	.706
40	ReAlnet01_cornet	.706
41	ReAlnet10	.706
42	ReAlnet01	.706
43	vonegrcnn_52e_full	.706
44	convnext_small_imagenet_10_seed-0	.706
45	resnet50_imagenet_100_seed-0	.706
46	deit3_base_patch16_224_fb_in1k	.629
47	deit_small_imagenet_full_seed-0	.629
48	pnasnet_large_halfPrecision	.608
49	mobilenet_v2_1_3_224	.608
50	pnasnet_large	.608
51	convnext_tiny_sup	.608
52	antialiased-r50	.608
53	convnext_large_imagenet_full_seed-0	.608
54	resnet152_imagenet_full	.608
55	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.542
56	resnet50_st_wzc_seed6_2_323	.524
57	resnet_50_v1_spiking_l4a	.524
58	yudixie_resnet50_distance_reg_0_240908	.524
59	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.524
60	vit_relpos_base_patch16_clsgap_224:sw_in1k	.524
61	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
62	resnet50_imagenet_10_seed-0	.524
63	resnet101_ecoset_full	.524
64	ReAlnet06_cornet	.467
65	ReAlnet06	.467
66	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.451
67	pr1_stl10_disentangled_alpha04	.451
68	resnet50_ewconplus_wzc_seed3_2_323	.451
69	AlexNet_SIN_fov4	.451
70	ReAlnet09_ALL	.451
71	resnet50-SIN_IN_IN	.451
72	convnext_tiny_imagenet_full_seed-0	.451
73	yudixie_wbh_object_class_scaling_0415_imagenet	.389
74	ReAlnet04_ALL	.389
75	yudixie_resnet50_category_class_0_240908	.389
76	inception_v1	.389
77	AT_efficientnet-b2	.389
78	AdvProp_efficientnet-b2	.389
79	focalnet_tiny_lrf_in1k	.389
80	resnext101_32x48d_wsl	.389
81	mobilenet_v2_1_4_224	.346
82	resnet50-vicregl0p75	.346
83	mobilenet_v2_1-4_224_pytorch	.346
84	ReAlnet05_cornet	.335
85	resnet_50_v1	.335
86	ReAlnet05	.335
87	resnet50_robust_l2_eps1	.335
88	convnext_femto_ols:d1_in1k	.335
89	AdvProp_efficientnet-b4	.335
90	resnet50-sup	.335
91	yudixie_resnet18_distance_rotation_0_240719	.335
92	mobilenet_v2_0_5_192	.298
93	resnet50-SIN_IN	.298
94	mobilenet_v2_1_0_192	.288
95	resnet_152_v1	.288
96	resnet50-vicregl0p9	.288
97	convnext_small_imagenet_1_seed-0	.288
98	resnext101_32x8d_wsl	.288
99	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.257
100	deit3_base_patch16_224_fb_in22k_ft_in1k	.248
101	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.248
102	resnet50_ewconplus_wzc_seed6_2_323	.248
103	vit_base_patch14_reg4_dinov2-lvd142m	.248
104	alexnet_fov12	.248
105	ReAlnet06_ALL	.248
106	ReAlnet03_ALL	.248
107	mobilenet_v2_0_75_224	.248
108	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.248
109	resnet50_imagenet_full	.248
110	resnet50_tutorial	.248
111	alexnet	.248
112	resnet50_st_wzc_seed7_2_323	.214
113	ReAlnet01_cornet_fov12	.214
114	Res2Net50_26w_4s	.214
115	convnext_small_imagenet_100_seed-0	.214
116	ReAlnet03_cornet	.191
117	yudixie_resnet50_distance_rotation_0_240908	.191
118	ReAlnet03	.191
119	xception	.184
120	resnet50-moclr8deg	.184
121	VOneCORnet-S	.184
122	convnext_xlarge:fb_in22k_ft_in1k	.184
123	BiT-S-R50x1	.184
124	deit_small_imagenet_1_seed-0	.184
125	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.184
126	cvt_cvt-21-224-in1k_4_LucyV4	.184
127	resnet50_ecoset_full	.184
128	resnet-152_v2_pytorch	.184
129	voneresnet-50-non_stochastic	.184
130	resnet50-SIN	.164
131	predictive_coding_pc	.159
132	alexnet_fov4	.159
133	resnet50_st_wzc_2	.159
134	compact_vgg19_IT	.159
135	ReAlnet08_ALL	.159
136	alexnet_training_seed_03	.159
137	resnet_50_v2	.159
138	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.159
139	yudixie_resnet18_distance_translation_0_240719	.159
140	efficientnet_b2_imagenet_full	.159
141	custom_model_cv_18_dagger_408	.159
142	deepeisnn_ei_cifar10_vgg19	.142
143	mobilenet_v2_1_0_160	.137
144	nasnet_mobile	.137
145	omnivore_swinS	.137
146	yudixie_resnet18_object_class_0_240719	.137
147	resnet152_ecoset_full	.137
148	resnet-50-robust	.137
149	AlexNet_SIN	.118
150	resnet50_primary_visual_cortex	.118
151	briaai_rmbg_1_4	.118
152	yolos_tiny	.118
153	yudixie_resnet50_object_class_0_240908	.118
154	yudixie_resnet50_imagenet1kpret_0_240908	.118
155	yudixie_resnet50_random_0_240908	.118
156	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.118
157	deit_base_imagenet_full_seed-0	.118
158	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.118
159	ViT_L_32_imagenet1k	.118
160	convnext_tiny:in12k_ft_in1k	.105
161	resnet_50_v1_spiking	.102
162	voneresnet-50-robust	.102
163	vit_base_patch16_clip_224:openai_ft_in1k	.102
164	BiT-S-R152x2	.102
165	resnet50_robust_l2_eps3	.102
166	imagenet_l2_3_0	.102
167	convnext_base_imagenet_full_seed-0	.102
168	yudixie_resnet18_distance_reg_0_240719	.102
169	efficientnet_b0_imagenet_full	.102
170	resnet34_imagenet_full	.102
171	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.102
172	resnet18_fair	.087
173	convnext_large:fb_in22k_ft_in1k	.087
174	AdvProp_efficientnet-b8	.087
175	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.087
176	resnet18_imagenet_full	.078
177	convnext_base_fb_in1k_gram_aligned_dinov3	.075
178	AlexNet_SIN_fov12	.075
179	ReAlnet09_cornet	.075
180	ReAlnet07_cornet	.075
181	grcnn_109	.075
182	ReAlnet09	.075
183	ReAlnet07	.075
184	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.075
185	yudixie_resnet18_imagenet1kpret_0_240719	.075
186	deit_small_imagenet_10_seed-0	.075
187	vit_base_patch16_dinov3-lvd1689m	.065
188	ReAlnet07_ALL	.065
189	resnet_50_v1_spiking_l3	.065
190	yudixie_resnet50_distance_translation_rotation_0_240908	.065
191	inception_v4	.065
192	vonegrcnn_62e_nobn	.065
193	resnet50-barlow	.065
194	vit_large_patch14_clip_224:laion2b_ft_in1k	.065
195	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.065
196	BiT-S-R50x3	.065
197	pnasnet_large_pytorch	.056
198	convnext_base_fb_in22k_ft_in1k	.056
199	resnet_101_v2	.056
200	mobilenet_v2_0_75_192	.056
201	AdvProp_efficientnet-b7	.056
202	resnet101_imagenet_full	.056
203	yudixie_wbh_object_class_scaling_0415_run_1	.048
204	resnet50_st_wzc_2_323	.048
205	AlexNet_SIN_fov16	.048
206	ReAlnet05_ALL	.048
207	mobilenet_v2_1_0_128	.048
208	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.048
209	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.048
210	densenet-169	.048
211	resnet_SIN_IN_FT_IN	.048
212	resnet50_st_wzc_noseed_2_323	.041
213	resnet_50_v1_spiking_l4	.041
214	alexnet_training_seed_07	.041
215	yudixie_resnet50_distance_translation_0_240908	.041
216	efficientnet-b7	.041
217	BiT-S-R101x1	.041
218	alexnet_training_seed_01_fov4	.036
219	yudixie_resnet50_translation_rotation_0_240908	.036
220	voneresnet-50	.036
221	yudixie_resnet18_translation_rotation_0_240719	.036
222	resnet_152_v2	.031
223	grcnn	.031
224	resnet-18_test_m	.031
225	BiT-S-R101x3	.031
226	mobilenet_v2_0_75_160	.027
227	densenet-201	.027
228	yudixie_resnet18_random_0_240719	.027
229	yudixie_resnet18_category_class_0_240719	.027
230	deepeisnn_ei_imagenet_resnet18	.023
231	yudixie_wbh_object_class_scaling_0415_run_2	.023
232	ReAlnet02_cornet	.023
233	ReAlnet02	.023
234	compact_resnet50_robust_IT	.020
235	alexnet_training_seed_04	.020
236	alexnet_training_seed_09	.020
237	resnet_101_v1	.020
238	vit_large_patch14_clip_224:openai_ft_in1k	.020
239	alexnet_training_seed_10	.017
240	yudixie_resnet18_translation_reg_0_240719	.017
241	yudixie_wbh_object_class_scaling_0415_run_3	.015
242	compact_vgg19_V4	.015
243	alexnet_training_seed_01	.015
244	inception_v3	.015
245	deit_large_imagenet_full_seed-0	.015
246	resnet50_imagenet_1_seed-0	.015
247	alexnet_training_seed_02	.013
248	mobilenet_v2_0_5_224	.013
249	omnivore_swinB	.013
250	densenet-121	.013
251	yudixie_resnet18_rotation_reg_0_240719	.013
252	resnet50_ewconplus_noseed_2_323	.011
253	compact_cornets_V4	.011
254	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.011
255	vit_large_patch14_clip_336:laion2b_ft_in1k	.011
256	alexnet_training_seed_01_fov12	.009
257	alexnet_training_seed_06	.009
258	yudixie_resnet50_translation_reg_0_240908	.009
259	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.009
260	aughost_fair_resnet18	.008
261	compact_resnet50_IT	.008
262	ReAlnet10_ALL	.008
263	vgg_16	.008
264	vit_base_patch14_dinov2-lvd142m	.007
265	deit_small_imagenet_100_seed-0	.006
266	cvt_cvt-13-384-in1k_4_LucyV4	.006
267	artResNet18_1	.005
268	compact_resnet50_V4	.004
269	effnetb1_272x240	.004
270	alexnet_training_seed_05	.004
271	BiT-S-R152x4	.004
272	alexnet_training_seed_01_fov16	.003
273	alexnet_training_seed_08	.003
274	blt_vs	.003
275	deepeisnn_ei_cifar10_resnet18	.003
276	compact_cornets_IT	.003
277	cvt_cvt-21-384-in1k_4_LucyV4	.002
278	compact_resnet50_robust_V4	.001
279	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3
280	mobilenet_v2_1_0_224
281	hmax

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