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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	deepeisnn_ei_imagenet_resnet18	1.0
2	ReAlnet09_cornet	1.0
3	ReAlnet09	1.0
4	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
5	resnet18_ecoset_full	1.0
6	resnet101_imagenet_full	1.0
7	pnasnet_large_pytorch	1.0
8	dinov2_vitl14_reg_lc	1.0
9	alexnet_training_seed_01_fov4	1.0
10	AlexNet_SIN_fov4	1.0
11	compact_resnet50_robust_V4	1.0
12	yudixie_resnet50_random_0_240908	1.0
13	densenet-121	1.0
14	convnext_small_imagenet_10_seed-0	1.0
15	resnet34_ecoset_full	1.0
16	resnet-152_v2_pytorch	1.0
17	AlexNet_SIN_fov16	1.0
18	yudixie_resnet50_distance_translation_rotation_0_240908	1.0
19	alexnet_training_seed_07	1.0
20	artResNet18_1	1.0
21	resnet50_imagenet_100_seed-0	1.0
22	resnet50_imagenet_1_seed-0	1.0
23	deepeisnn_ei_cifar10_vgg19	.985
24	deit3_base_patch16_224_fb_in1k	.985
25	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.985
26	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.985
27	resnet152_ecoset_full	.985
28	dinov2_vitl14_reg_lc_featread	.925
29	yudixie_wbh_object_class_scaling_0415_run_0	.925
30	resnet50_st_wzc_2	.925
31	alexnet_training_seed_08	.925
32	alexnet_training_seed_02	.925
33	yudixie_resnet18_object_class_0_240719	.894
34	dinov2_vitg14_lc	.839
35	compact_cornets_IT	.839
36	vgg_19	.839
37	yudixie_resnet50_translation_reg_0_240908	.839
38	vit_large_patch14_clip_224:openai_ft_in1k	.839
39	convnext_base:clip_laiona_augreg_ft_in1k_384	.839
40	antialiased-r50	.839
41	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.811
42	ReAlnet04_cornet	.811
43	ReAlnet04	.811
44	resnet_50_v1_spiking_l4	.811
45	mobilenet_v2_1_4_224	.762
46	ReAlnet10_cornet	.762
47	resnet_152_v2	.762
48	ReAlnet10	.762
49	blt_vs	.762
50	mobilenet_v2_1-4_224_pytorch	.762
51	ReAlnet07_ALL	.762
52	resnet_50_v1_spiking_l3	.762
53	yudixie_resnet50_distance_reg_0_240908	.736
54	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.736
55	resnet152_imagenet_full	.736
56	resnet18_fair	.691
57	resnet50_hvs_wzc	.691
58	mobilenet_v2_0_5_192	.691
59	voneresnet-50	.691
60	resnet50-moclr8deg	.691
61	resnet50-SIN	.691
62	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.691
63	convnext_tiny:in12k_ft_in1k	.691
64	yudixie_resnet18_translation_reg_0_240719	.691
65	yudixie_resnet18_distance_translation_0_240719	.691
66	cvt_cvt-21-384-in1k_4_LucyV4	.691
67	resnet50-barlow	.667
68	yudixie_resnet18_distance_rotation_0_240719	.667
69	convnext_tiny_imagenet_full_seed-0	.667
70	deit_small_imagenet_100_seed-0	.667
71	yudixie_wbh_object_class_scaling_0415_imagenet	.627
72	convnext_base_fb_in22k_ft_in1k	.627
73	alexnet_fov16	.627
74	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.627
75	ReAlnet08_cornet	.627
76	ReAlnet03_cornet	.627
77	resnet_50_v2	.627
78	resnet_101_v1	.627
79	ReAlnet08	.627
80	ReAlnet03	.627
81	densenet-201	.627
82	vit_large_patch14_clip_224:laion2b_ft_in1k	.627
83	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.627
84	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.627
85	BiT-S-R152x2	.627
86	vonegrcnn_52e_full	.627
87	resnet50_ecoset_full	.627
88	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.627
89	resnext101_32x32d_wsl	.627
90	resnet50-SIN_IN	.606
91	deit_large_imagenet_full_seed-0	.606
92	alexnet_training_seed_01	.569
93	Res2Net50_26w_4s	.569
94	vit_relpos_base_patch16_clsgap_224:sw_in1k	.569
95	resnet50_robust_l2_eps3	.569
96	imagenet_l2_3_0	.569
97	AdvProp_efficientnet-b7	.569
98	AdvProp_efficientnet-b6	.569
99	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.569
100	mobilenet_v2_1_3_224	.549
101	alexnet_training_seed_03	.549
102	resnet50_imagenet_full	.549
103	vit_huge_clip336_laion	.516
104	yudixie_resnet50_object_class_0_240908	.516
105	mobilenet_v2_1_0_160	.516
106	nasnet_mobile	.516
107	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.516
108	vit_base_patch16_clip_224:openai_ft_in1k	.516
109	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.516
110	convnext_small_imagenet_1_seed-0	.516
111	resnet-50-robust	.516
112	effnetb1_272x240	.516
113	compact_resnet50_IT	.468
114	ReAlnet01_cornet	.468
115	grcnn	.468
116	ReAlnet01	.468
117	vit_large_patch14_clip_336:laion2b_ft_in1k	.468
118	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.468
119	AdvProp_efficientnet-b8	.468
120	deit_base_imagenet_full_seed-0	.452
121	convnext_xxlarge_clip	.425
122	predictive_coding_pc	.425
123	resnet50_ewconplus_wzc_seed2_2__323	.425
124	pnasnet_large_halfPrecision	.425
125	alexnet_fov12	.425
126	yudixie_resnet50_imagenet1kpret_0_240908	.425
127	alexnet_training_seed_06	.425
128	alexnet_training_seed_05	.425
129	mobilenet_v2_0_75_224	.425
130	grcnn_109	.425
131	deit_small_imagenet_1_seed-0	.425
132	yudixie_resnet18_distance_reg_0_240719	.425
133	resnet50_tutorial	.425
134	resnet50_primary_visual_cortex	.425
135	ReAlnet01_cornet_fov12	.410
136	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.385
137	vit_large_clip336_openai	.385
138	dinov2_vitl14_lc_res336	.385
139	deepeisnn_ei_cifar10_resnet18	.385
140	yudixie_wbh_object_class_scaling_0415_run_3	.385
141	vit_base_patch14_reg4_dinov2-lvd142m	.385
142	ReAlnet07_cornet	.385
143	ReAlnet05_cornet	.385
144	mobilenet_v2_1_0_128	.385
145	resnet_101_v2	.385
146	ReAlnet07	.385
147	ReAlnet05	.385
148	convnext_xlarge:fb_in22k_ft_in1k	.385
149	convnext_large:fb_in22k_ft_in1k	.385
150	BiT-S-R50x1	.385
151	AdvProp_efficientnet-b4	.385
152	convnext_small_imagenet_full_seed-0	.385
153	deit_small_imagenet_10_seed-0	.385
154	convnext_large_in22k_supervised	.349
155	vit_base_patch16_dinov3-lvd1689m	.349
156	aughost_fair_resnet18	.349
157	ReAlnet01_cornet_fov4	.349
158	yudixie_resnet50_category_class_0_240908	.349
159	yudixie_resnet18_translation_rotation_0_240719	.349
160	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.349
161	ReAlnet02_ALL	.349
162	custom_model_cv_18_dagger_408	.349
163	deit3_base_patch16_224_fb_in22k_ft_in1k	.317
164	convnext_base_fb_in1k_gram_aligned_dinov3	.317
165	vit_base_patch14_dinov2-lvd142m	.317
166	alexnet_training_seed_10	.317
167	ReAlnet06_cornet	.317
168	mobilenet_v2_0_75_192	.317
169	vonegrcnn_62e_nobn	.317
170	ReAlnet06	.317
171	resnet50-vicreg	.317
172	resnet50_robust_l2_eps1	.317
173	yudixie_resnet18_imagenet1kpret_0_240719	.317
174	resnet50_imagenet_10_seed-0	.317
175	hmax	.317
176	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.317
177	resnext101_32x8d_wsl	.317
178	yudixie_resnet50_translation_rotation_0_240908	.306
179	eva02_large_in22k	.288
180	dinov2_vitg14_reg_lc	.288
181	convnext_large_clip_laion2b_finelayers	.288
182	alexnet_training_seed_01_fov16	.288
183	mobilenet_v2_0_5_224	.288
184	mobilenet_v2_0_75_160	.288
185	omnivore_swinB	.288
186	convnext_large_imagenet_full_seed-0	.288
187	convnext_base_imagenet_full_seed-0	.288
188	yudixie_resnet18_random_0_240719	.288
189	compact_cornets_V4	.261
190	nasnet_large	.261
191	efficientnet_b2_imagenet_full	.261
192	cvt_cvt-13-224-in1k_4_LucyV4	.261
193	ViT_L_32_imagenet1k	.261
194	efficientnet_b0_imagenet_full	.252
195	ReAlnet01_cornet_fov16	.237
196	mobilenet_v2_1_0_224	.237
197	alexnet_training_seed_04	.237
198	alexnet_training_seed_09	.237
199	vgg_16	.237
200	yudixie_resnet50_distance_translation_0_240908	.237
201	ReAlnet01_ALL	.237
202	voneresnet-50-non_stochastic	.237
203	yudixie_wbh_object_class_scaling_0415_run_2	.215
204	convnext_base_fb_in1k	.215
205	ReAlnet02_cornet	.215
206	resnet_50_v1	.215
207	ReAlnet02	.215
208	voneresnet-50-robust	.215
209	resnet50-sup	.215
210	yudixie_resnet18_category_class_0_240719	.215
211	efficientnet_b1_imagenet_full	.215
212	resnet50_ewconplus_wzc	.195
213	compact_vgg19_IT	.195
214	yudixie_resnet50_rotation_reg_0_240908	.195
215	shufflenet_v2_x1_0	.195
216	resnet50-SIN_IN_IN	.195
217	omnivore_swinS	.195
218	AT_efficientnet-b2	.195
219	convnext_tiny_sup	.195
220	AdvProp_efficientnet-b2	.195
221	cvt_cvt-21-224-in1k_4_LucyV4	.195
222	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.195
223	compact_resnet50_V4	.188
224	resnet_152_v1	.177
225	efficientnet-b7	.177
226	VOneCORnet-S	.177
227	efficientnet_b0	.177
228	resnet50-vicregl0p9	.177
229	yudixie_resnet18_distance_translation_rotation_0_240719	.177
230	ReAlnet06_ALL	.177
231	ReAlnet03_ALL	.177
232	resnet_50_v1_spiking	.177
233	resnet18_imagenet_full	.171
234	cv_18_dagger_408_pretrained	.160
235	AlexNet_SIN	.160
236	compact_vgg19_V4	.160
237	BiT-S-R101x3	.160
238	ReAlnet09_ALL	.160
239	resnet34_imagenet_full	.155
240	convnext_femto_ols:d1_in1k	.145
241	convnext_small_imagenet_100_seed-0	.145
242	ReAlnet05_ALL	.145
243	deit_small_imagenet_full_seed-0	.141
244	pr1_stl10_disentangled_alpha04	.132
245	resnet50_st_wzc_seed3_2_323	.132
246	mobilenet_v2_1_0_192	.132
247	resnet50-vitoimagevidnet8	.132
248	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.132
249	resnet50-VITO-8deg-cc	.132
250	resnext101_32x48d_wsl	.132
251	cvt_cvt-13-384-in1k_4_LucyV4	.120
252	ReAlnet04_ALL	.120
253	resnet-18_test_m	.109
254	resnet_50_v1_spiking_l4a	.109
255	focalnet_tiny_lrf_in1k	.109
256	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.099
257	BiT-S-R152x4	.099
258	inception_v3	.089
259	yudixie_wbh_object_class_scaling_0415_run_1	.081
260	resnet50-vicregl0p75	.081
261	ReAlnet10_ALL	.081
262	yolos_tiny	.074
263	yudixie_resnet50_distance_rotation_0_240908	.074
264	resnet101_ecoset_full	.071
265	resnet50_ewconplus_wzc_seed5_2__323	.067
266	AlexNet_SIN_fov12	.067
267	compact_resnet50_robust_IT	.067
268	densenet-169	.067
269	briaai_rmbg_1_4	.061
270	xception	.055
271	alexnet_fov4	.050
272	resnet_SIN_IN_FT_IN	.050
273	vonegrcnn_47e	.050
274	alexnet_training_seed_01_fov12	.044
275	inception_v1	.041
276	BiT-S-R50x3	.037
277	yudixie_resnet18_rotation_reg_0_240719	.037
278	ReAlnet08_ALL	.034
279	inception_v4	.028
280	alexnet	.028
281	BiT-S-R101x1	.013
282	dinov2_vitl14_lc
283	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
284	resnet50_st_wzc_seed7_2_323
285	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