Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

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