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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	alexnet_training_seed_01_fov4	1.0
9	AlexNet_SIN_fov4	1.0
10	compact_resnet50_robust_V4	1.0
11	yudixie_resnet50_random_0_240908	1.0
12	densenet-121	1.0
13	convnext_small_imagenet_10_seed-0	1.0
14	resnet34_ecoset_full	1.0
15	resnet-152_v2_pytorch	1.0
16	AlexNet_SIN_fov16	1.0
17	yudixie_resnet50_distance_translation_rotation_0_240908	1.0
18	alexnet_training_seed_07	1.0
19	artResNet18_1	1.0
20	resnet50_imagenet_100_seed-0	1.0
21	resnet50_imagenet_1_seed-0	1.0
22	deepeisnn_ei_cifar10_vgg19	.985
23	deit3_base_patch16_224_fb_in1k	.985
24	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.985
25	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.985
26	resnet152_ecoset_full	.985
27	yudixie_wbh_object_class_scaling_0415_run_0	.925
28	resnet50_st_wzc_2	.925
29	alexnet_training_seed_08	.925
30	alexnet_training_seed_02	.925
31	yudixie_resnet18_object_class_0_240719	.894
32	compact_cornets_IT	.839
33	vgg_19	.839
34	yudixie_resnet50_translation_reg_0_240908	.839
35	vit_large_patch14_clip_224:openai_ft_in1k	.839
36	convnext_base:clip_laiona_augreg_ft_in1k_384	.839
37	antialiased-r50	.839
38	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.811
39	ReAlnet04_cornet	.811
40	ReAlnet04	.811
41	resnet_50_v1_spiking_l4	.811
42	mobilenet_v2_1_4_224	.762
43	ReAlnet10_cornet	.762
44	resnet_152_v2	.762
45	ReAlnet10	.762
46	blt_vs	.762
47	mobilenet_v2_1-4_224_pytorch	.762
48	ReAlnet07_ALL	.762
49	resnet_50_v1_spiking_l3	.762
50	yudixie_resnet50_distance_reg_0_240908	.736
51	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.736
52	resnet152_imagenet_full	.736
53	resnet18_fair	.691
54	resnet50_st_wzc_seed4_2_323	.691
55	mobilenet_v2_0_5_192	.691
56	voneresnet-50	.691
57	resnet50-moclr8deg	.691
58	resnet50-SIN	.691
59	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.691
60	convnext_tiny:in12k_ft_in1k	.691
61	yudixie_resnet18_translation_reg_0_240719	.691
62	yudixie_resnet18_distance_translation_0_240719	.691
63	cvt_cvt-21-384-in1k_4_LucyV4	.691
64	resnet50-barlow	.667
65	yudixie_resnet18_distance_rotation_0_240719	.667
66	convnext_tiny_imagenet_full_seed-0	.667
67	deit_small_imagenet_100_seed-0	.667
68	yudixie_wbh_object_class_scaling_0415_imagenet	.627
69	convnext_base_fb_in22k_ft_in1k	.627
70	alexnet_fov16	.627
71	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.627
72	ReAlnet08_cornet	.627
73	ReAlnet03_cornet	.627
74	resnet_50_v2	.627
75	resnet_101_v1	.627
76	ReAlnet08	.627
77	ReAlnet03	.627
78	densenet-201	.627
79	vit_large_patch14_clip_224:laion2b_ft_in1k	.627
80	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.627
81	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.627
82	BiT-S-R152x2	.627
83	vonegrcnn_52e_full	.627
84	resnet50_ecoset_full	.627
85	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.627
86	resnext101_32x32d_wsl	.627
87	resnet50-SIN_IN	.606
88	deit_large_imagenet_full_seed-0	.606
89	alexnet_training_seed_01	.569
90	Res2Net50_26w_4s	.569
91	vit_relpos_base_patch16_clsgap_224:sw_in1k	.569
92	resnet50_robust_l2_eps3	.569
93	imagenet_l2_3_0	.569
94	AdvProp_efficientnet-b7	.569
95	AdvProp_efficientnet-b6	.569
96	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.569
97	mobilenet_v2_1_3_224	.549
98	alexnet_training_seed_03	.549
99	resnet50_imagenet_full	.549
100	yudixie_resnet50_object_class_0_240908	.516
101	mobilenet_v2_1_0_160	.516
102	nasnet_mobile	.516
103	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.516
104	vit_base_patch16_clip_224:openai_ft_in1k	.516
105	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.516
106	convnext_small_imagenet_1_seed-0	.516
107	resnet-50-robust	.516
108	effnetb1_272x240	.516
109	compact_resnet50_IT	.468
110	ReAlnet01_cornet	.468
111	grcnn	.468
112	ReAlnet01	.468
113	vit_large_patch14_clip_336:laion2b_ft_in1k	.468
114	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.468
115	AdvProp_efficientnet-b8	.468
116	deit_base_imagenet_full_seed-0	.452
117	predictive_coding_pc	.425
118	resnet50_ewconplus_wzc_seed2_2__323	.425
119	pnasnet_large_halfPrecision	.425
120	alexnet_fov12	.425
121	yudixie_resnet50_imagenet1kpret_0_240908	.425
122	alexnet_training_seed_06	.425
123	alexnet_training_seed_05	.425
124	mobilenet_v2_0_75_224	.425
125	grcnn_109	.425
126	deit_small_imagenet_1_seed-0	.425
127	yudixie_resnet18_distance_reg_0_240719	.425
128	resnet50_tutorial	.425
129	resnet50_primary_visual_cortex	.425
130	ReAlnet01_cornet_fov12	.410
131	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.385
132	deepeisnn_ei_cifar10_resnet18	.385
133	yudixie_wbh_object_class_scaling_0415_run_3	.385
134	vit_base_patch14_reg4_dinov2-lvd142m	.385
135	ReAlnet07_cornet	.385
136	ReAlnet05_cornet	.385
137	mobilenet_v2_1_0_128	.385
138	resnet_101_v2	.385
139	ReAlnet07	.385
140	ReAlnet05	.385
141	convnext_xlarge:fb_in22k_ft_in1k	.385
142	convnext_large:fb_in22k_ft_in1k	.385
143	BiT-S-R50x1	.385
144	AdvProp_efficientnet-b4	.385
145	convnext_small_imagenet_full_seed-0	.385
146	deit_small_imagenet_10_seed-0	.385
147	resnet50_ewconplus_noseed_2_323	.349
148	vit_base_patch16_dinov3-lvd1689m	.349
149	aughost_fair_resnet18	.349
150	ReAlnet01_cornet_fov4	.349
151	yudixie_resnet50_category_class_0_240908	.349
152	yudixie_resnet18_translation_rotation_0_240719	.349
153	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.349
154	ReAlnet02_ALL	.349
155	custom_model_cv_18_dagger_408	.349
156	deit3_base_patch16_224_fb_in22k_ft_in1k	.317
157	convnext_base_fb_in1k_gram_aligned_dinov3	.317
158	vit_base_patch14_dinov2-lvd142m	.317
159	alexnet_training_seed_10	.317
160	ReAlnet06_cornet	.317
161	mobilenet_v2_0_75_192	.317
162	vonegrcnn_62e_nobn	.317
163	ReAlnet06	.317
164	resnet50-vicreg	.317
165	resnet50_robust_l2_eps1	.317
166	yudixie_resnet18_imagenet1kpret_0_240719	.317
167	resnet50_imagenet_10_seed-0	.317
168	hmax	.317
169	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.317
170	resnext101_32x8d_wsl	.317
171	yudixie_resnet50_translation_rotation_0_240908	.306
172	alexnet_training_seed_01_fov16	.288
173	mobilenet_v2_0_5_224	.288
174	mobilenet_v2_0_75_160	.288
175	omnivore_swinB	.288
176	convnext_large_imagenet_full_seed-0	.288
177	convnext_base_imagenet_full_seed-0	.288
178	yudixie_resnet18_random_0_240719	.288
179	compact_cornets_V4	.261
180	nasnet_large	.261
181	efficientnet_b2_imagenet_full	.261
182	cvt_cvt-13-224-in1k_4_LucyV4	.261
183	ViT_L_32_imagenet1k	.261
184	efficientnet_b0_imagenet_full	.252
185	ReAlnet01_cornet_fov16	.237
186	mobilenet_v2_1_0_224	.237
187	alexnet_training_seed_04	.237
188	alexnet_training_seed_09	.237
189	vgg_16	.237
190	yudixie_resnet50_distance_translation_0_240908	.237
191	ReAlnet01_ALL	.237
192	voneresnet-50-non_stochastic	.237
193	yudixie_wbh_object_class_scaling_0415_run_2	.215
194	convnext_base_fb_in1k	.215
195	resnet50_st_wzc_noseed_2_323	.215
196	ReAlnet02_cornet	.215
197	resnet_50_v1	.215
198	ReAlnet02	.215
199	voneresnet-50-robust	.215
200	resnet50-sup	.215
201	yudixie_resnet18_category_class_0_240719	.215
202	efficientnet_b1_imagenet_full	.215
203	resnet50_ewconplus_wzc	.195
204	compact_vgg19_IT	.195
205	yudixie_resnet50_rotation_reg_0_240908	.195
206	shufflenet_v2_x1_0	.195
207	resnet50-SIN_IN_IN	.195
208	omnivore_swinS	.195
209	AT_efficientnet-b2	.195
210	convnext_tiny_sup	.195
211	AdvProp_efficientnet-b2	.195
212	cvt_cvt-21-224-in1k_4_LucyV4	.195
213	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.195
214	compact_resnet50_V4	.188
215	resnet_152_v1	.177
216	efficientnet-b7	.177
217	VOneCORnet-S	.177
218	efficientnet_b0	.177
219	resnet50-vicregl0p9	.177
220	yudixie_resnet18_distance_translation_rotation_0_240719	.177
221	ReAlnet06_ALL	.177
222	ReAlnet03_ALL	.177
223	resnet_50_v1_spiking	.177
224	resnet18_imagenet_full	.171
225	resnet50_st_wzc_seed5_2_323	.160
226	cv_18_dagger_408_pretrained	.160
227	AlexNet_SIN	.160
228	compact_vgg19_V4	.160
229	BiT-S-R101x3	.160
230	ReAlnet09_ALL	.160
231	resnet34_imagenet_full	.155
232	convnext_femto_ols:d1_in1k	.145
233	convnext_small_imagenet_100_seed-0	.145
234	ReAlnet05_ALL	.145
235	deit_small_imagenet_full_seed-0	.141
236	pr1_stl10_disentangled_alpha04	.132
237	resnet50_st_wzc_seed3_2_323	.132
238	resnet50_ewconplus_wzc_2_323	.132
239	mobilenet_v2_1_0_192	.132
240	resnet50-vitoimagevidnet8	.132
241	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.132
242	resnet50-VITO-8deg-cc	.132
243	resnext101_32x48d_wsl	.132
244	cvt_cvt-13-384-in1k_4_LucyV4	.120
245	ReAlnet04_ALL	.120
246	resnet-18_test_m	.109
247	resnet_50_v1_spiking_l4a	.109
248	focalnet_tiny_lrf_in1k	.109
249	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.099
250	BiT-S-R152x4	.099
251	inception_v3	.089
252	yudixie_wbh_object_class_scaling_0415_run_1	.081
253	resnet50_ewconplus_wzc_seed7_2_323	.081
254	resnet50_ewconplus_wzc_seed4_2_323	.081
255	resnet50-vicregl0p75	.081
256	ReAlnet10_ALL	.081
257	yolos_tiny	.074
258	yudixie_resnet50_distance_rotation_0_240908	.074
259	resnet101_ecoset_full	.071
260	resnet50_ewconplus_wzc_seed5_2__323	.067
261	AlexNet_SIN_fov12	.067
262	compact_resnet50_robust_IT	.067
263	densenet-169	.067
264	resnet50_st_wzc_2_323	.061
265	briaai_rmbg_1_4	.061
266	xception	.055
267	alexnet_fov4	.050
268	resnet_SIN_IN_FT_IN	.050
269	vonegrcnn_47e	.050
270	alexnet_training_seed_01_fov12	.044
271	inception_v1	.041
272	BiT-S-R50x3	.037
273	yudixie_resnet18_rotation_reg_0_240719	.037
274	resnet50_ewconplus_wzc_seed3_2_323	.034
275	ReAlnet08_ALL	.034
276	inception_v4	.028
277	alexnet	.028
278	BiT-S-R101x1	.013
279	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
280	resnet50_st_wzc_seed7_2_323
281	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