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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	convnext_xxlarge_clip	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	convnext_large_in22k_supervised	1.0
8	ReAlnet04_cornet	1.0
9	ReAlnet04	1.0
10	efficientnet_b1_imagenet_full	1.0
11	regnety_032	.984
12	dinov2_vitl14_reg_lc_featread	.984
13	resnet50-vicreg	.984
14	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.984
15	resnet34_ecoset_full	.984
16	resnet50_st_wzc_seed3_2_323	.951
17	vonegrcnn_47e	.951
18	AdvProp_efficientnet-b6	.951
19	convnext_small_imagenet_full_seed-0	.951
20	cv_18_dagger_408_pretrained	.848
21	ReAlnet08_cornet	.848
22	ReAlnet08	.848
23	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.848
24	convnext_base:clip_laiona_augreg_ft_in1k_384	.848
25	convnext_base_fb_in1k	.819
26	resnet50_ewconplus_wzc_seed5_2__323	.819
27	ReAlnet01_cornet_fov16	.819
28	vgg_19	.819
29	yudixie_resnet50_rotation_reg_0_240908	.819
30	shufflenet_v2_x1_0	.819
31	yudixie_resnet18_distance_translation_rotation_0_240719	.819
32	ReAlnet01_cornet_fov4	.730
33	nasnet_large	.730
34	efficientnet_b0	.730
35	cvt_cvt-13-224-in1k_4_LucyV4	.730
36	resnext101_32x32d_wsl	.730
37	yudixie_wbh_object_class_scaling_0415_run_0	.706
38	ReAlnet02_ALL	.706
39	ReAlnet01_ALL	.706
40	ReAlnet10_cornet	.706
41	ReAlnet01_cornet	.706
42	ReAlnet10	.706
43	ReAlnet01	.706
44	vonegrcnn_52e_full	.706
45	convnext_small_imagenet_10_seed-0	.706
46	resnet50_imagenet_100_seed-0	.706
47	eicircuit_resnet18_bn_20260919	.629
48	eva02_large_in22k	.629
49	deit3_base_patch16_224_fb_in1k	.629
50	deit_small_imagenet_full_seed-0	.629
51	dinov2_vitg14_reg_lc	.608
52	pnasnet_large_halfPrecision	.608
53	resnet50_hvs_wzc	.608
54	mobilenet_v2_1_3_224	.608
55	pnasnet_large	.608
56	convnext_tiny_sup	.608
57	antialiased-r50	.608
58	convnext_large_imagenet_full_seed-0	.608
59	resnet152_imagenet_full	.608
60	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.542
61	resnet50_st_wzc_seed6_2_323	.524
62	resnet_50_v1_spiking_l4a	.524
63	yudixie_resnet50_distance_reg_0_240908	.524
64	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.524
65	vit_relpos_base_patch16_clsgap_224:sw_in1k	.524
66	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
67	resnet50_imagenet_10_seed-0	.524
68	resnet101_ecoset_full	.524
69	ReAlnet06_cornet	.467
70	ReAlnet06	.467
71	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.451
72	pr1_stl10_disentangled_alpha04	.451
73	AlexNet_SIN_fov4	.451
74	ReAlnet09_ALL	.451
75	resnet50-SIN_IN_IN	.451
76	convnext_tiny_imagenet_full_seed-0	.451
77	yudixie_wbh_object_class_scaling_0415_imagenet	.389
78	ReAlnet04_ALL	.389
79	yudixie_resnet50_category_class_0_240908	.389
80	inception_v1	.389
81	AT_efficientnet-b2	.389
82	AdvProp_efficientnet-b2	.389
83	focalnet_tiny_lrf_in1k	.389
84	resnext101_32x48d_wsl	.389
85	mobilenet_v2_1_4_224	.346
86	resnet50-vicregl0p75	.346
87	mobilenet_v2_1-4_224_pytorch	.346
88	ReAlnet05_cornet	.335
89	resnet_50_v1	.335
90	ReAlnet05	.335
91	resnet50_robust_l2_eps1	.335
92	convnext_femto_ols:d1_in1k	.335
93	AdvProp_efficientnet-b4	.335
94	resnet50-sup	.335
95	yudixie_resnet18_distance_rotation_0_240719	.335
96	mobilenet_v2_0_5_192	.298
97	resnet50-SIN_IN	.298
98	mobilenet_v2_1_0_192	.288
99	resnet_152_v1	.288
100	resnet50-vicregl0p9	.288
101	convnext_small_imagenet_1_seed-0	.288
102	resnext101_32x8d_wsl	.288
103	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.257
104	deit3_base_patch16_224_fb_in22k_ft_in1k	.248
105	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.248
106	resnet50_ewconplus_wzc_seed6_2_323	.248
107	vit_base_patch14_reg4_dinov2-lvd142m	.248
108	alexnet_fov12	.248
109	ReAlnet06_ALL	.248
110	ReAlnet03_ALL	.248
111	mobilenet_v2_0_75_224	.248
112	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.248
113	resnet50_imagenet_full	.248
114	resnet50_tutorial	.248
115	alexnet	.248
116	seresnext50_32x4d	.214
117	convnext_large_clip_laion2b_finelayers	.214
118	resnet50_st_wzc_seed7_2_323	.214
119	ReAlnet01_cornet_fov12	.214
120	Res2Net50_26w_4s	.214
121	convnext_small_imagenet_100_seed-0	.214
122	ReAlnet03_cornet	.191
123	yudixie_resnet50_distance_rotation_0_240908	.191
124	ReAlnet03	.191
125	dinov2_vitl14_lc_res336	.184
126	dinov2_vitl14_reg_lc	.184
127	xception	.184
128	resnet50-moclr8deg	.184
129	VOneCORnet-S	.184
130	convnext_xlarge:fb_in22k_ft_in1k	.184
131	BiT-S-R50x1	.184
132	deit_small_imagenet_1_seed-0	.184
133	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.184
134	cvt_cvt-21-224-in1k_4_LucyV4	.184
135	resnet50_ecoset_full	.184
136	resnet-152_v2_pytorch	.184
137	voneresnet-50-non_stochastic	.184
138	resnet50-SIN	.164
139	gabor_filter_entropy_4x4	.159
140	dinov2_vitg14_lc	.159
141	predictive_coding_pc	.159
142	alexnet_fov4	.159
143	resnet50_st_wzc_2	.159
144	compact_vgg19_IT	.159
145	ReAlnet08_ALL	.159
146	alexnet_training_seed_03	.159
147	resnet_50_v2	.159
148	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.159
149	yudixie_resnet18_distance_translation_0_240719	.159
150	efficientnet_b2_imagenet_full	.159
151	custom_model_cv_18_dagger_408	.159
152	deepeisnn_ei_cifar10_vgg19	.142
153	gabor_filter_mean_abs_4x4_v2	.137
154	mobilenet_v2_1_0_160	.137
155	nasnet_mobile	.137
156	omnivore_swinS	.137
157	yudixie_resnet18_object_class_0_240719	.137
158	resnet152_ecoset_full	.137
159	resnet-50-robust	.137
160	AlexNet_SIN	.118
161	resnet50_primary_visual_cortex	.118
162	briaai_rmbg_1_4	.118
163	yolos_tiny	.118
164	yudixie_resnet50_object_class_0_240908	.118
165	yudixie_resnet50_imagenet1kpret_0_240908	.118
166	yudixie_resnet50_random_0_240908	.118
167	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.118
168	deit_base_imagenet_full_seed-0	.118
169	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.118
170	ViT_L_32_imagenet1k	.118
171	convnext_tiny:in12k_ft_in1k	.105
172	resnet_50_v1_spiking	.102
173	voneresnet-50-robust	.102
174	vit_base_patch16_clip_224:openai_ft_in1k	.102
175	BiT-S-R152x2	.102
176	resnet50_robust_l2_eps3	.102
177	imagenet_l2_3_0	.102
178	convnext_base_imagenet_full_seed-0	.102
179	yudixie_resnet18_distance_reg_0_240719	.102
180	efficientnet_b0_imagenet_full	.102
181	resnet34_imagenet_full	.102
182	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.102
183	resnet18_fair	.087
184	convnext_large:fb_in22k_ft_in1k	.087
185	AdvProp_efficientnet-b8	.087
186	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.087
187	resnet18_imagenet_full	.078
188	convnext_base_fb_in1k_gram_aligned_dinov3	.075
189	AlexNet_SIN_fov12	.075
190	ReAlnet09_cornet	.075
191	ReAlnet07_cornet	.075
192	grcnn_109	.075
193	ReAlnet09	.075
194	ReAlnet07	.075
195	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.075
196	yudixie_resnet18_imagenet1kpret_0_240719	.075
197	deit_small_imagenet_10_seed-0	.075
198	vit_base_patch16_dinov3-lvd1689m	.065
199	ReAlnet07_ALL	.065
200	resnet_50_v1_spiking_l3	.065
201	yudixie_resnet50_distance_translation_rotation_0_240908	.065
202	inception_v4	.065
203	vonegrcnn_62e_nobn	.065
204	resnet50-barlow	.065
205	vit_large_patch14_clip_224:laion2b_ft_in1k	.065
206	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.065
207	BiT-S-R50x3	.065
208	pnasnet_large_pytorch	.056
209	convnext_base_fb_in22k_ft_in1k	.056
210	resnet_101_v2	.056
211	mobilenet_v2_0_75_192	.056
212	AdvProp_efficientnet-b7	.056
213	resnet101_imagenet_full	.056
214	vit_large_clip336_openai	.048
215	yudixie_wbh_object_class_scaling_0415_run_1	.048
216	AlexNet_SIN_fov16	.048
217	ReAlnet05_ALL	.048
218	mobilenet_v2_1_0_128	.048
219	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.048
220	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.048
221	densenet-169	.048
222	resnet_SIN_IN_FT_IN	.048
223	resnet_50_v1_spiking_l4	.041
224	alexnet_training_seed_07	.041
225	yudixie_resnet50_distance_translation_0_240908	.041
226	efficientnet-b7	.041
227	BiT-S-R101x1	.041
228	alexnet_training_seed_01_fov4	.036
229	yudixie_resnet50_translation_rotation_0_240908	.036
230	voneresnet-50	.036
231	yudixie_resnet18_translation_rotation_0_240719	.036
232	resnet_152_v2	.031
233	grcnn	.031
234	resnet-18_test_m	.031
235	BiT-S-R101x3	.031
236	gabor_filter_entropy_4x4_v2_forcedCosine	.027
237	mobilenet_v2_0_75_160	.027
238	densenet-201	.027
239	yudixie_resnet18_random_0_240719	.027
240	yudixie_resnet18_category_class_0_240719	.027
241	deepeisnn_ei_imagenet_resnet18	.023
242	yudixie_wbh_object_class_scaling_0415_run_2	.023
243	ReAlnet02_cornet	.023
244	ReAlnet02	.023
245	vit_huge_clip336_laion	.020
246	compact_resnet50_robust_IT	.020
247	alexnet_training_seed_04	.020
248	alexnet_training_seed_09	.020
249	resnet_101_v1	.020
250	vit_large_patch14_clip_224:openai_ft_in1k	.020
251	dinov2_vitl14_lc	.017
252	alexnet_training_seed_10	.017
253	yudixie_resnet18_translation_reg_0_240719	.017
254	yudixie_wbh_object_class_scaling_0415_run_3	.015
255	compact_vgg19_V4	.015
256	alexnet_training_seed_01	.015
257	inception_v3	.015
258	deit_large_imagenet_full_seed-0	.015
259	resnet50_imagenet_1_seed-0	.015
260	alexnet_training_seed_02	.013
261	mobilenet_v2_0_5_224	.013
262	omnivore_swinB	.013
263	densenet-121	.013
264	yudixie_resnet18_rotation_reg_0_240719	.013
265	compact_cornets_V4	.011
266	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.011
267	vit_large_patch14_clip_336:laion2b_ft_in1k	.011
268	alexnet_training_seed_01_fov12	.009
269	alexnet_training_seed_06	.009
270	yudixie_resnet50_translation_reg_0_240908	.009
271	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.009
272	gabor_filter_entropy_4x4_v2	.008
273	compact_resnet50_IT	.008
274	ReAlnet10_ALL	.008
275	vgg_16	.008
276	vit_base_patch14_dinov2-lvd142m	.007
277	deit_small_imagenet_100_seed-0	.006
278	cvt_cvt-13-384-in1k_4_LucyV4	.006
279	artResNet18_1	.005
280	compact_resnet50_V4	.004
281	effnetb1_272x240	.004
282	alexnet_training_seed_05	.004
283	BiT-S-R152x4	.004
284	alexnet_training_seed_01_fov16	.003
285	alexnet_training_seed_08	.003
286	blt_vs	.003
287	deepeisnn_ei_cifar10_resnet18	.003
288	compact_cornets_IT	.003
289	cvt_cvt-21-384-in1k_4_LucyV4	.002
290	compact_resnet50_robust_V4	.001
291	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3
292	mobilenet_v2_1_0_224
293	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