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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024convergence-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	ReAlnet09_cornet	1.0
2	ReAlnet09	1.0
3	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
4	resnet18_ecoset_full	1.0
5	resnet101_imagenet_full	1.0
6	pnasnet_large_pytorch	1.0
7	alexnet_training_seed_01_fov4	1.0
8	AlexNet_SIN_fov4	1.0
9	compact_resnet50_robust_V4	1.0
10	yudixie_resnet50_random_0_240908	1.0
11	densenet-121	1.0
12	convnext_small_imagenet_10_seed-0	1.0
13	resnet34_ecoset_full	1.0
14	resnet-152_v2_pytorch	1.0
15	AlexNet_SIN_fov16	1.0
16	yudixie_resnet50_distance_translation_rotation_0_240908	1.0
17	alexnet_training_seed_07	1.0
18	artResNet18_1	1.0
19	resnet50_imagenet_100_seed-0	1.0
20	resnet50_imagenet_1_seed-0	1.0
21	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.985
22	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.985
23	resnet152_ecoset_full	.985
24	vit_base_patch16_dinov3:lvd1689m	.925
25	alexnet_training_seed_08	.925
26	alexnet_training_seed_02	.925
27	yudixie_resnet18_object_class_0_240719	.894
28	compact_cornets_IT	.839
29	vgg_19	.839
30	yudixie_resnet50_translation_reg_0_240908	.839
31	vit_large_patch14_clip_224:openai_ft_in1k	.839
32	convnext_base:clip_laiona_augreg_ft_in1k_384	.839
33	antialiased-r50	.839
34	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.811
35	ReAlnet04_cornet	.811
36	ReAlnet04	.811
37	resnet_50_v1_spiking_l4	.811
38	mobilenet_v2_1_4_224	.762
39	ReAlnet10_cornet	.762
40	resnet_152_v2	.762
41	ReAlnet10	.762
42	blt_vs	.762
43	mobilenet_v2_1-4_224_pytorch	.762
44	ReAlnet07_ALL	.762
45	resnet_50_v1_spiking_l3	.762
46	yudixie_resnet50_distance_reg_0_240908	.736
47	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.736
48	resnet152_imagenet_full	.736
49	mobilenet_v2_0_5_192	.691
50	voneresnet-50	.691
51	resnet50-moclr8deg	.691
52	resnet50-SIN	.691
53	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.691
54	convnext_tiny:in12k_ft_in1k	.691
55	yudixie_resnet18_translation_reg_0_240719	.691
56	yudixie_resnet18_distance_translation_0_240719	.691
57	cvt_cvt-21-384-in1k_4_LucyV4	.691
58	resnet50-barlow	.667
59	yudixie_resnet18_distance_rotation_0_240719	.667
60	convnext_tiny_imagenet_full_seed-0	.667
61	deit_small_imagenet_100_seed-0	.667
62	alexnet_fov16	.627
63	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.627
64	ReAlnet08_cornet	.627
65	ReAlnet03_cornet	.627
66	resnet_50_v2	.627
67	resnet_101_v1	.627
68	ReAlnet08	.627
69	ReAlnet03	.627
70	densenet-201	.627
71	vit_large_patch14_clip_224:laion2b_ft_in1k	.627
72	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.627
73	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.627
74	BiT-S-R152x2	.627
75	vonegrcnn_52e_full	.627
76	resnet50_ecoset_full	.627
77	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.627
78	resnext101_32x32d_wsl	.627
79	resnet50-SIN_IN	.606
80	deit_large_imagenet_full_seed-0	.606
81	alexnet_training_seed_01	.569
82	Res2Net50_26w_4s	.569
83	vit_relpos_base_patch16_clsgap_224:sw_in1k	.569
84	resnet50_robust_l2_eps3	.569
85	imagenet_l2_3_0	.569
86	AdvProp_efficientnet-b7	.569
87	AdvProp_efficientnet-b6	.569
88	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.569
89	mobilenet_v2_1_3_224	.549
90	alexnet_training_seed_03	.549
91	resnet50_imagenet_full	.549
92	yudixie_resnet50_object_class_0_240908	.516
93	mobilenet_v2_1_0_160	.516
94	nasnet_mobile	.516
95	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.516
96	vit_base_patch16_clip_224:openai_ft_in1k	.516
97	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.516
98	convnext_small_imagenet_1_seed-0	.516
99	resnet-50-robust	.516
100	effnetb1_272x240	.516
101	compact_resnet50_IT	.468
102	ReAlnet01_cornet	.468
103	grcnn	.468
104	ReAlnet01	.468
105	vit_large_patch14_clip_336:laion2b_ft_in1k	.468
106	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.468
107	AdvProp_efficientnet-b8	.468
108	deit_base_imagenet_full_seed-0	.452
109	alexnet_fov12	.425
110	yudixie_resnet50_imagenet1kpret_0_240908	.425
111	alexnet_training_seed_06	.425
112	alexnet_training_seed_05	.425
113	mobilenet_v2_0_75_224	.425
114	grcnn_109	.425
115	deit_small_imagenet_1_seed-0	.425
116	yudixie_resnet18_distance_reg_0_240719	.425
117	resnet50_tutorial	.425
118	resnet50_primary_visual_cortex	.425
119	ReAlnet01_cornet_fov12	.410
120	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.385
121	vit_base_patch14_dinov2:lvd142m	.385
122	ReAlnet07_cornet	.385
123	ReAlnet05_cornet	.385
124	mobilenet_v2_1_0_128	.385
125	resnet_101_v2	.385
126	ReAlnet07	.385
127	ReAlnet05	.385
128	convnext_xlarge:fb_in22k_ft_in1k	.385
129	convnext_large:fb_in22k_ft_in1k	.385
130	BiT-S-R50x1	.385
131	AdvProp_efficientnet-b4	.385
132	convnext_small_imagenet_full_seed-0	.385
133	deit_small_imagenet_10_seed-0	.385
134	ReAlnet01_cornet_fov4	.349
135	yudixie_resnet50_category_class_0_240908	.349
136	yudixie_resnet18_translation_rotation_0_240719	.349
137	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.349
138	ReAlnet02_ALL	.349
139	custom_model_cv_18_dagger_408	.349
140	alexnet_training_seed_10	.317
141	ReAlnet06_cornet	.317
142	mobilenet_v2_0_75_192	.317
143	vonegrcnn_62e_nobn	.317
144	ReAlnet06	.317
145	resnet50-vicreg	.317
146	resnet50_robust_l2_eps1	.317
147	yudixie_resnet18_imagenet1kpret_0_240719	.317
148	resnet50_imagenet_10_seed-0	.317
149	hmax	.317
150	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.317
151	resnext101_32x8d_wsl	.317
152	yudixie_resnet50_translation_rotation_0_240908	.306
153	alexnet_training_seed_01_fov16	.288
154	mobilenet_v2_0_5_224	.288
155	mobilenet_v2_0_75_160	.288
156	omnivore_swinB	.288
157	convnext_large_imagenet_full_seed-0	.288
158	convnext_base_imagenet_full_seed-0	.288
159	yudixie_resnet18_random_0_240719	.288
160	compact_cornets_V4	.261
161	nasnet_large	.261
162	efficientnet_b2_imagenet_full	.261
163	cvt_cvt-13-224-in1k_4_LucyV4	.261
164	ViT_L_32_imagenet1k	.261
165	efficientnet_b0_imagenet_full	.252
166	ReAlnet01_cornet_fov16	.237
167	mobilenet_v2_1_0_224	.237
168	alexnet_training_seed_04	.237
169	alexnet_training_seed_09	.237
170	vgg_16	.237
171	yudixie_resnet50_distance_translation_0_240908	.237
172	ReAlnet01_ALL	.237
173	voneresnet-50-non_stochastic	.237
174	ReAlnet02_cornet	.215
175	resnet_50_v1	.215
176	ReAlnet02	.215
177	voneresnet-50-robust	.215
178	resnet50-sup	.215
179	yudixie_resnet18_category_class_0_240719	.215
180	efficientnet_b1_imagenet_full	.215
181	resnet50_ewconplus_wzc	.195
182	compact_vgg19_IT	.195
183	yudixie_resnet50_rotation_reg_0_240908	.195
184	shufflenet_v2_x1_0	.195
185	resnet50-SIN_IN_IN	.195
186	omnivore_swinS	.195
187	AT_efficientnet-b2	.195
188	convnext_tiny_sup	.195
189	AdvProp_efficientnet-b2	.195
190	cvt_cvt-21-224-in1k_4_LucyV4	.195
191	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.195
192	compact_resnet50_V4	.188
193	resnet_152_v1	.177
194	efficientnet-b7	.177
195	VOneCORnet-S	.177
196	efficientnet_b0	.177
197	resnet50-vicregl0p9	.177
198	yudixie_resnet18_distance_translation_rotation_0_240719	.177
199	ReAlnet06_ALL	.177
200	ReAlnet03_ALL	.177
201	resnet_50_v1_spiking	.177
202	resnet18_imagenet_full	.171
203	cv_18_dagger_408_pretrained	.160
204	AlexNet_SIN	.160
205	compact_vgg19_V4	.160
206	BiT-S-R101x3	.160
207	ReAlnet09_ALL	.160
208	resnet34_imagenet_full	.155
209	convnext_femto_ols:d1_in1k	.145
210	convnext_small_imagenet_100_seed-0	.145
211	ReAlnet05_ALL	.145
212	deit_small_imagenet_full_seed-0	.141
213	mobilenet_v2_1_0_192	.132
214	resnet50-vitoimagevidnet8	.132
215	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.132
216	resnet50-VITO-8deg-cc	.132
217	resnext101_32x48d_wsl	.132
218	vit_base_patch14_reg4_dinov2:lvd142m	.120
219	cvt_cvt-13-384-in1k_4_LucyV4	.120
220	ReAlnet04_ALL	.120
221	resnet-18_test_m	.109
222	resnet_50_v1_spiking_l4a	.109
223	focalnet_tiny_lrf_in1k	.109
224	BiT-S-R152x4	.099
225	inception_v3	.089
226	resnet50-vicregl0p75	.081
227	ReAlnet10_ALL	.081
228	yolos_tiny	.074
229	yudixie_resnet50_distance_rotation_0_240908	.074
230	resnet101_ecoset_full	.071
231	AlexNet_SIN_fov12	.067
232	compact_resnet50_robust_IT	.067
233	densenet-169	.067
234	briaai_rmbg_1_4	.061
235	xception	.055
236	alexnet_fov4	.050
237	resnet_SIN_IN_FT_IN	.050
238	vonegrcnn_47e	.050
239	alexnet_training_seed_01_fov12	.044
240	inception_v1	.041
241	BiT-S-R50x3	.037
242	yudixie_resnet18_rotation_reg_0_240719	.037
243	ReAlnet08_ALL	.034
244	inception_v4	.028
245	alexnet_workflow_trigger	.028
246	alexnet	.028
247	BiT-S-R101x1	.013
248	pnasnet_large

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

0.86.

Note that scores are relative to this ceiling.

Data: Ferguson2024convergence

Metric: value_delta