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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024round_v-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	yudixie_wbh_object_class_scaling_0415_run_0	1.0
2	resnet50_ewconplus_noseed_2_323	1.0
3	ReAlnet01_cornet	1.0
4	mobilenet_v2_0_75_192	1.0
5	grcnn	1.0
6	ReAlnet01	1.0
7	voneresnet-50-robust	1.0
8	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
9	resnet50_ecoset_full	1.0
10	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
11	yudixie_resnet18_object_class_0_240719	1.0
12	yudixie_resnet18_distance_translation_0_240719	1.0
13	resnet152_ecoset_full	1.0
14	alexnet_training_seed_01_fov4	1.0
15	ReAlnet08_cornet	1.0
16	resnet_152_v2	1.0
17	nasnet_large	1.0
18	ReAlnet08	1.0
19	resnet50-SIN	1.0
20	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
21	convnext_femto_ols:d1_in1k	1.0
22	ReAlnet01_cornet_fov4	1.0
23	yudixie_resnet50_category_class_0_240908	1.0
24	alexnet_training_seed_04	1.0
25	ReAlnet06_cornet	1.0
26	ReAlnet04_cornet	1.0
27	inception_v4	1.0
28	ReAlnet06	1.0
29	ReAlnet04	1.0
30	Res2Net50_26w_4s	1.0
31	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
32	convnext_small_imagenet_10_seed-0	1.0
33	resnet34_ecoset_full	1.0
34	ReAlnet01_ALL	.924
35	mobilenet_v2_1_4_224	.924
36	mobilenet_v2_0_5_224	.924
37	omnivore_swinB	.924
38	convnext_xlarge:fb_in22k_ft_in1k	.924
39	convnext_base_imagenet_full_seed-0	.924
40	resnet101_imagenet_full	.924
41	mobilenet_v2_1-4_224_pytorch	.924
42	deepeisnn_ei_imagenet_resnet18	.905
43	vit_base_patch16_dinov3-lvd1689m	.905
44	compact_vgg19_IT	.905
45	voneresnet-50	.905
46	efficientnet-b7	.905
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.905
48	convnext_tiny_imagenet_full_seed-0	.905
49	AlexNet_SIN_fov12	.836
50	ReAlnet09_cornet	.836
51	nasnet_mobile	.836
52	inception_v1	.836
53	ReAlnet09	.836
54	deit_small_imagenet_100_seed-0	.836
55	deit_large_imagenet_full_seed-0	.836
56	resnet101_ecoset_full	.836
57	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.820
58	resnet50_ewconplus_wzc_seed7_2_323	.820
59	resnet50-vicreg	.820
60	vit_large_patch14_clip_224:openai_ft_in1k	.820
61	blt_vs	.820
62	yudixie_resnet18_distance_reg_0_240719	.820
63	resnet152_imagenet_full	.820
64	resnet18_imagenet_full	.820
65	focalnet_tiny_lrf_in1k	.820
66	resnext101_32x32d_wsl	.820
67	yudixie_resnet50_distance_reg_0_240908	.757
68	alexnet_training_seed_10	.757
69	vgg_16	.757
70	vonegrcnn_62e_nobn	.757
71	resnet34_imagenet_full	.757
72	ViT_L_32_imagenet1k	.757
73	resnet18_fair	.742
74	ReAlnet01_cornet_fov12	.742
75	alexnet_training_seed_01	.742
76	ReAlnet05_cornet	.742
77	ReAlnet05	.742
78	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.742
79	deit3_base_patch16_224_fb_in22k_ft_in1k	.686
80	ReAlnet10_ALL	.686
81	ReAlnet05_ALL	.686
82	ReAlnet02_ALL	.686
83	shufflenet_v2_x1_0	.686
84	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.686
85	yudixie_wbh_object_class_scaling_0415_run_3	.672
86	resnet50_st_wzc_seed5_2_323	.672
87	resnet50_ewconplus_wzc_seed4_2_323	.672
88	resnet50_st_wzc_seed7_2_323	.672
89	AlexNet_SIN_fov4	.672
90	alexnet_fov4	.672
91	ReAlnet07_ALL	.672
92	resnet_50_v1_spiking_l3	.672
93	resnet_50_v2	.672
94	vgg_19	.672
95	efficientnet_b0	.672
96	AdvProp_efficientnet-b7	.672
97	efficientnet_b2_imagenet_full	.672
98	custom_model_cv_18_dagger_408	.672
99	ReAlnet08_ALL	.621
100	ReAlnet03_ALL	.621
101	inception_v3	.621
102	omnivore_swinS	.621
103	densenet-169	.621
104	AdvProp_efficientnet-b4	.621
105	convnext_small_imagenet_full_seed-0	.621
106	deit_small_imagenet_10_seed-0	.621
107	deit_base_imagenet_full_seed-0	.621
108	resnet18_ecoset_full	.621
109	resnext101_32x48d_wsl	.621
110	yudixie_wbh_object_class_scaling_0415_run_1	.609
111	compact_cornets_IT	.609
112	compact_cornets_V4	.609
113	yudixie_resnet50_distance_translation_rotation_0_240908	.609
114	ReAlnet07_cornet	.609
115	ReAlnet03_cornet	.609
116	grcnn_109	.609
117	ReAlnet07	.609
118	ReAlnet03	.609
119	vonegrcnn_47e	.609
120	voneresnet-50-non_stochastic	.609
121	alexnet_fov12	.562
122	convnext_tiny_sup	.562
123	AdvProp_efficientnet-b8	.562
124	yudixie_resnet18_imagenet1kpret_0_240719	.562
125	alexnet_training_seed_05	.551
126	ReAlnet02_cornet	.551
127	ReAlnet02	.551
128	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.551
129	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.551
130	resnet_SIN_IN_FT_IN	.551
131	yudixie_resnet18_translation_reg_0_240719	.551
132	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.551
133	resnet-50-robust	.551
134	aughost_fair_resnet18	.509
135	alexnet_training_seed_03	.509
136	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.509
137	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.509
138	cvt_cvt-21-384-in1k_4_LucyV4	.509
139	hmax	.509
140	resnet50_st_wzc_seed3_2_323	.499
141	compact_resnet50_robust_IT	.499
142	resnet_50_v1_spiking_l4a	.499
143	mobilenet_v2_0_75_224	.499
144	BiT-S-R50x1	.499
145	convnext_small_imagenet_1_seed-0	.499
146	resnet50_ewconplus_wzc_2_323	.461
147	cv_18_dagger_408_pretrained	.461
148	ReAlnet06_ALL	.461
149	vit_base_patch16_clip_224:openai_ft_in1k	.461
150	convnext_large_imagenet_full_seed-0	.461
151	resnet50_imagenet_100_seed-0	.461
152	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.461
153	pr1_stl10_disentangled_alpha04	.417
154	resnet50_primary_visual_cortex	.417
155	resnet-18_test_m	.417
156	resnet50-SIN_IN	.417
157	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.417
158	convnext_base:clip_laiona_augreg_ft_in1k_384	.417
159	cvt_cvt-13-224-in1k_4_LucyV4	.417
160	vit_base_patch14_dinov2-lvd142m	.409
161	mobilenet_v2_1_3_224	.409
162	resnet_152_v1	.409
163	resnet_101_v2	.409
164	resnet_50_v1	.409
165	mobilenet_v2_0_75_160	.409
166	resnet50-vitoimagevidnet8	.409
167	resnet50-VITO-8deg-cc	.409
168	vit_relpos_base_patch16_clsgap_224:sw_in1k	.409
169	resnet50-sup	.409
170	yudixie_resnet18_distance_rotation_0_240719	.409
171	yudixie_wbh_object_class_scaling_0415_imagenet	.378
172	ReAlnet09_ALL	.378
173	VOneCORnet-S	.378
174	BiT-S-R50x3	.378
175	resnet50_robust_l2_eps3	.378
176	imagenet_l2_3_0	.378
177	effnetb1_272x240	.378
178	AlexNet_SIN_fov16	.370
179	briaai_rmbg_1_4	.370
180	xception	.370
181	ReAlnet10_cornet	.370
182	ReAlnet10	.370
183	resnet50-SIN_IN_IN	.370
184	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.370
185	convnext_large:fb_in22k_ft_in1k	.370
186	resnet50_imagenet_full	.370
187	resnet50-vicregl0p9	.342
188	artResNet18_1	.342
189	cvt_cvt-13-384-in1k_4_LucyV4	.342
190	deit3_base_patch16_224_fb_in1k	.335
191	AlexNet_SIN	.335
192	resnet50_ewconplus_wzc	.335
193	yudixie_resnet50_object_class_0_240908	.335
194	yudixie_resnet50_random_0_240908	.335
195	convnext_base_fb_in1k	.310
196	yudixie_resnet50_distance_translation_0_240908	.310
197	alexnet_training_seed_01_fov16	.304
198	compact_resnet50_IT	.304
199	yudixie_resnet50_distance_rotation_0_240908	.304
200	resnet50-moclr8deg	.304
201	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.281
202	efficientnet_b0_imagenet_full	.281
203	ReAlnet01_cornet_fov16	.275
204	yudixie_resnet50_imagenet1kpret_0_240908	.275
205	mobilenet_v2_1_0_224	.275
206	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.275
207	densenet-121	.275
208	resnet50_imagenet_10_seed-0	.275
209	vit_base_patch14_reg4_dinov2-lvd142m	.254
210	densenet-201	.254
211	AdvProp_efficientnet-b6	.254
212	deit_small_imagenet_full_seed-0	.254
213	predictive_coding_pc	.249
214	alexnet_training_seed_01_fov12	.249
215	resnet50_robust_l2_eps1	.249
216	BiT-S-R152x2	.249
217	deit_small_imagenet_1_seed-0	.249
218	alexnet	.249
219	yudixie_wbh_object_class_scaling_0415_run_2	.230
220	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.230
221	ReAlnet04_ALL	.230
222	resnet50-barlow	.230
223	AT_efficientnet-b2	.230
224	BiT-S-R152x4	.230
225	AdvProp_efficientnet-b2	.230
226	vonegrcnn_52e_full	.230
227	resnet50_st_wzc_seed4_2_323	.225
228	resnet_50_v1_spiking_l4	.225
229	alexnet_training_seed_08	.225
230	alexnet_training_seed_02	.225
231	alexnet_training_seed_09	.225
232	resnet_101_v1	.225
233	yudixie_resnet50_translation_rotation_0_240908	.225
234	yudixie_resnet18_distance_translation_rotation_0_240719	.225
235	yudixie_resnet18_translation_rotation_0_240719	.225
236	convnext_base_fb_in1k_gram_aligned_dinov3	.208
237	convnext_base_fb_in22k_ft_in1k	.208
238	mobilenet_v2_1_0_128	.208
239	resnet-152_v2_pytorch	.208
240	compact_vgg19_V4	.204
241	mobilenet_v2_1_0_192	.204
242	mobilenet_v2_1_0_160	.204
243	antialiased-r50	.204
244	mobilenet_v2_0_5_192	.189
245	alexnet_training_seed_06	.185
246	yudixie_resnet50_rotation_reg_0_240908	.185
247	convnext_tiny:in12k_ft_in1k	.185
248	cvt_cvt-21-224-in1k_4_LucyV4	.171
249	alexnet_fov16	.167
250	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.155
251	resnet50-vicregl0p75	.155
252	resnet50_st_wzc_noseed_2_323	.152
253	resnet50_st_wzc_2	.140
254	efficientnet_b1_imagenet_full	.140
255	alexnet_training_seed_07	.137
256	resnet50_tutorial	.137
257	deepeisnn_ei_cifar10_vgg19	.124
258	pnasnet_large_pytorch	.124
259	resnext101_32x8d_wsl	.102
260	deepeisnn_ei_cifar10_resnet18	.102
261	pnasnet_large_halfPrecision	.083
262	BiT-S-R101x3	.083
263	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.076
264	convnext_small_imagenet_100_seed-0	.070
265	yudixie_resnet18_rotation_reg_0_240719	.068
266	yudixie_resnet18_category_class_0_240719	.068
267	resnet50_imagenet_1_seed-0	.068
268	pnasnet_large	.062
269	compact_resnet50_robust_V4	.051
270	compact_resnet50_V4	.051
271	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.035
272	yudixie_resnet50_translation_reg_0_240908	.034
273	resnet_50_v1_spiking	.025
274	yolos_tiny	.025
275	BiT-S-R101x1	.025
276	yudixie_resnet18_random_0_240719	.023
277	resnet50_ewconplus_wzc_seed5_2__323

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

0.85.

Note that scores are relative to this ceiling.

Data: Ferguson2024round_v

Metric: value_delta