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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024llh-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	mehrer2020_alexnet_training_seed_01_fov4	1.0
2	mehrer2020_alexnet_training_seed_01_fov12	1.0
3	alexnet_training_seed_10	1.0
4	alexnet_training_seed_06	1.0
5	alexnet_training_seed_09	1.0
6	mobilenet_v2_1_0_128	1.0
7	resnet50-SIN_IN_IN	1.0
8	vit_large_patch14_clip_224:openai_ft_in1k	1.0
9	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
10	convnext_femto_ols:d1_in1k	1.0
11	deit_small_imagenet_10_seed-0	1.0
12	deit_base_imagenet_full_seed-0	1.0
13	efficientnet_b1_imagenet_full	1.0
14	resnet50_imagenet_100_seed-0	1.0
15	ViT_L_32_imagenet1k	1.0
16	mehrer2020_alexnet_training_seed_07	1.0
17	mehrer2020_alexnet_training_seed_02	1.0
18	dinov2_vitl14_reg_lc	1.0
19	alexnet_training_seed_01_fov16	1.0
20	alexnet_fov4	1.0
21	resnet_50_v1_spiking_l4a	1.0
22	eicircuit_resnet18_bn_20260919	1.0
23	xception	1.0
24	alexnet_training_seed_02	1.0
25	resnet50-moclr8deg	1.0
26	mobilenet_v2_1_0_160	1.0
27	resnet-152_v2_pytorch	1.0
28	resnext101_32x16d_wsl	1.0
29	dinov2_vitl14_lc_res336	1.0
30	yudixie_resnet50_object_class_0_240908	1.0
31	alexnet_training_seed_01	1.0
32	mobilenet_v2_1_0_192	1.0
33	efficientnet-b7	1.0
34	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
35	resnet50_tutorial	1.0
36	resnet152_imagenet_full	1.0
37	resnet34_imagenet_full	1.0
38	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
39	dinov2_vitg14_reg_lc	1.0
40	vit_base_patch14_dinov2-lvd142m	1.0
41	compact_resnet50_robust_V4	1.0
42	resnet_50_v1_spiking	1.0
43	vgg_16	1.0
44	efficientnet_b0_imagenet_full	1.0
45	cvt_cvt-13-384-in1k_4_LucyV4	1.0
46	AdvProp_efficientnet-b8	.979
47	cvt_cvt-21-224-in1k_4_LucyV4	.979
48	resnet50_st_wzc_seed7_2_323	.951
49	gabor_filter_entropy_4x4_v2	.951
50	gabor_filter_entropy_4x4	.951
51	vonegrcnn_52e_full	.951
52	AdvProp_efficientnet-b4	.951
53	antialiased-r50	.951
54	blt_vs	.951
55	yudixie_resnet18_category_class_0_240719	.951
56	resnet152_ecoset_full	.951
57	pnasnet_large_pytorch	.951
58	alexnet_training_seed_01_fov4	.888
59	mobilenet_v2_1_0_224	.888
60	mobilenet_v2_0_5_224	.888
61	BiT-S-R50x1	.888
62	BiT-S-R50x3	.888
63	AdvProp_efficientnet-b7	.888
64	yudixie_resnet18_distance_rotation_0_240719	.888
65	mehrer2020_alexnet_training_seed_05	.862
66	dinov2_vitl14_lc	.862
67	yudixie_resnet50_imagenet1kpret_0_240908	.862
68	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
69	AT_efficientnet-b2	.862
70	AdvProp_efficientnet-b2	.862
71	yudixie_resnet18_distance_translation_0_240719	.862
72	efficientnet_b2_imagenet_full	.862
73	focalnet_tiny_lrf_in1k	.862
74	yudixie_wbh_object_class_scaling_0415_run_0	.805
75	predictive_coding_pc	.805
76	resnet18_fair	.805
77	resnet50_primary_visual_cortex	.805
78	mobilenet_v2_0_75_224	.805
79	inception_v1	.805
80	yudixie_resnet18_object_class_0_240719	.805
81	deit_small_imagenet_100_seed-0	.805
82	resnet18_ecoset_full	.805
83	alexnet	.805
84	resnext101_32x32d_wsl	.805
85	resnet50_st_wzc_seed3_2_323	.782
86	resnet50_ewconplus_wzc_seed5_2__323	.782
87	ReAlnet01_cornet_fov4	.782
88	vit_huge_clip336_laion	.782
89	resnet50_robust_l2_eps1	.782
90	resnet50-vicregl0p9	.782
91	BiT-S-R152x4	.782
92	artResNet18_1	.782
93	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
94	resnet18_imagenet_full	.782
95	ReAlnet01_cornet_fov16	.730
96	mobilenet_v2_0_75_192	.730
97	inception_v3	.730
98	omnivore_swinB	.730
99	yudixie_resnet18_rotation_reg_0_240719	.730
100	resnet50_imagenet_1_seed-0	.730
101	resnet50-vitoimagevidnet8	.709
102	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.709
103	omnivore_swinS	.709
104	efficientnet_b0	.709
105	resnet50-VITO-8deg-cc	.709
106	BiT-S-R101x1	.709
107	convnext_tiny_sup	.709
108	yudixie_resnet18_translation_rotation_0_240719	.709
109	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.709
110	resnext101_32x48d_wsl	.709
111	hmax	.709
112	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.662
113	mobilenet_v2_1_3_224	.662
114	resnet_SIN_IN_FT_IN	.662
115	mehrer2020_alexnet_training_seed_06	.643
116	yudixie_wbh_object_class_scaling_0415_imagenet	.643
117	alexnet_training_seed_01_fov12	.643
118	alexnet_fov16	.643
119	ReAlnet01_ALL	.643
120	resnet_101_v1	.643
121	mobilenet_v2_0_5_192	.643
122	convnext_xlarge:fb_in22k_ft_in1k	.643
123	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.643
124	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.643
125	yudixie_resnet18_random_0_240719	.643
126	convnext_large_in22k_supervised	.601
127	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.601
128	AlexNet_SIN_fov12	.601
129	compact_vgg19_IT	.601
130	alexnet_training_seed_05	.601
131	BiT-S-R152x2	.601
132	yudixie_wbh_object_class_scaling_0415_run_2	.583
133	deit3_base_patch16_224_fb_in1k	.583
134	vit_base_patch16_dinov3-lvd1689m	.583
135	AlexNet_SIN_fov4	.583
136	gabor_filter_entropy_4x4_v2_forcedCosine	.583
137	alexnet_training_seed_08	.583
138	resnet_152_v1	.583
139	inception_v4	.583
140	yudixie_resnet50_translation_reg_0_240908	.583
141	shufflenet_v2_x1_0	.583
142	VOneCORnet-S	.583
143	densenet-169	.583
144	BiT-S-R101x3	.583
145	yudixie_wbh_object_class_scaling_0415_run_1	.545
146	convnext_base_fb_in22k_ft_in1k	.545
147	AdvProp_efficientnet-b6	.545
148	mehrer2020_alexnet_training_seed_08	.529
149	ReAlnet01_cornet_fov12	.529
150	AlexNet_SIN	.529
151	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.529
152	yudixie_resnet50_distance_reg_0_240908	.529
153	mobilenet_v2_1_4_224	.529
154	mobilenet_v2_0_75_160	.529
155	vonegrcnn_62e_nobn	.529
156	resnet50-vicreg	.529
157	resnet-18_test_m	.529
158	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
159	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
160	resnet50-vicregl0p75	.529
161	vonegrcnn_47e	.529
162	yudixie_resnet18_distance_translation_rotation_0_240719	.529
163	mobilenet_v2_1-4_224_pytorch	.529
164	yudixie_wbh_object_class_scaling_0415_run_3	.494
165	alexnet_training_seed_04	.494
166	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
167	mehrer2020_alexnet_training_seed_10	.480
168	dinov2_vitl14_reg_lc_featread	.480
169	deit3_base_patch16_224_fb_in22k_ft_in1k	.480
170	resnet_50_v1	.480
171	densenet-201	.480
172	resnet50-sup	.480
173	yudixie_resnet50_translation_rotation_0_240908	.448
174	yudixie_resnet18_distance_reg_0_240719	.448
175	resnet50_ewconplus_wzc	.435
176	compact_resnet50_IT	.435
177	ReAlnet02_ALL	.435
178	yudixie_resnet50_category_class_0_240908	.435
179	nasnet_mobile	.435
180	grcnn	.435
181	cvt_cvt-21-384-in1k_4_LucyV4	.435
182	resnet50_ecoset_full	.435
183	resnet_152_v2	.406
184	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
185	convnext_small_imagenet_10_seed-0	.406
186	alexnet_fov12	.395
187	compact_cornets_V4	.395
188	compact_resnet50_V4	.395
189	ReAlnet04_ALL	.395
190	convnext_xxlarge_clip	.395
191	yudixie_resnet50_distance_rotation_0_240908	.395
192	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
193	resnet_50_v1_spiking_l4	.369
194	alexnet_training_seed_07	.369
195	resnet50_imagenet_10_seed-0	.369
196	custom_model_cv_18_dagger_408	.369
197	eva02_large_in22k	.358
198	vit_base_patch14_reg4_dinov2-lvd142m	.358
199	yudixie_resnet50_random_0_240908	.358
200	yudixie_resnet50_rotation_reg_0_240908	.358
201	resnet50-SIN	.358
202	effnetb1_272x240	.358
203	compact_resnet50_robust_IT	.334
204	briaai_rmbg_1_4	.334
205	mehrer2020_alexnet_training_seed_04	.325
206	resnet50_st_wzc_2	.325
207	grcnn_109	.325
208	vit_base_patch16_clip_224:openai_ft_in1k	.325
209	imagenet_l2_3_0	.325
210	resnet50_robust_l2_eps3	.325
211	deit_small_imagenet_full_seed-0	.325
212	gabor_filter_mean_abs_4x4_v2	.303
213	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
214	convnext_large_clip_laion2b_finelayers	.294
215	resnet50_ewconplus_wzc_seed6_2_323	.294
216	seresnext50_32x4d	.294
217	Res2Net50_26w_4s	.294
218	densenet-121	.294
219	yudixie_resnet18_translation_reg_0_240719	.294
220	convnext_small_imagenet_full_seed-0	.294
221	deit_large_imagenet_full_seed-0	.275
222	AlexNet_SIN_fov16	.267
223	yolos_tiny	.267
224	resnet_50_v2	.267
225	convnext_tiny:in12k_ft_in1k	.267
226	convnext_base_imagenet_full_seed-0	.267
227	dinov2_vitg14_lc	.242
228	pnasnet_large_halfPrecision	.242
229	ReAlnet10_ALL	.242
230	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
231	pnasnet_large	.242
232	ReAlnet06_cornet	.242
233	ReAlnet02_cornet	.242
234	resnet_101_v2	.242
235	yudixie_resnet50_distance_translation_0_240908	.242
236	ReAlnet06	.242
237	ReAlnet02	.242
238	resnet50-barlow	.242
239	deit_small_imagenet_1_seed-0	.242
240	resnet50_imagenet_full	.242
241	mehrer2020_alexnet_training_seed_01_fov16	.226
242	alexnet_training_seed_03	.226
243	mehrer2020_alexnet_training_seed_01	.220
244	deepeisnn_ei_cifar10_vgg19	.220
245	ReAlnet06_ALL	.220
246	regnety_032	.220
247	resnet_50_v1_spiking_l3	.205
248	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
249	resnet101_imagenet_full	.199
250	voneresnet-50-non_stochastic	.199
251	deepeisnn_ei_imagenet_resnet18	.181
252	deepeisnn_ei_cifar10_resnet18	.181
253	ReAlnet09_ALL	.181
254	ReAlnet07_ALL	.181
255	convnext_large_imagenet_full_seed-0	.181
256	yudixie_resnet50_distance_translation_rotation_0_240908	.164
257	ReAlnet09_cornet	.164
258	nasnet_large	.164
259	ReAlnet09	.164
260	voneresnet-50	.164
261	resnet50-SIN_IN	.164
262	cvt_cvt-13-224-in1k_4_LucyV4	.164
263	resnet-50-robust	.164
264	convnext_base_fb_in1k_gram_aligned_dinov3	.149
265	resnet101_ecoset_full	.149
266	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
267	mehrer2020_alexnet_training_seed_03	.135
268	compact_cornets_IT	.135
269	ReAlnet05_cornet	.135
270	ReAlnet05	.135
271	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
272	convnext_small_imagenet_1_seed-0	.126
273	vgg_19	.122
274	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
275	voneresnet-50-robust	.111
276	convnext_small_imagenet_100_seed-0	.111
277	yudixie_resnet18_imagenet1kpret_0_240719	.111
278	compact_vgg19_V4	.101
279	ReAlnet08_ALL	.101
280	ReAlnet05_ALL	.101
281	convnext_base_fb_in1k	.091
282	mehrer2020_alexnet_training_seed_09	.083
283	ReAlnet01_cornet	.083
284	ReAlnet01	.083
285	ReAlnet03_ALL	.075
286	cv_18_dagger_408_pretrained	.068
287	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
288	convnext_large:fb_in22k_ft_in1k	.068
289	resnext101_32x8d_wsl	.068
290	ReAlnet03_cornet	.062
291	ReAlnet03	.062
292	ReAlnet10_cornet	.051
293	ReAlnet10	.051
294	ReAlnet08_cornet	.046
295	ReAlnet08	.046
296	resnet34_ecoset_full	.046
297	ReAlnet07_cornet	.042
298	ReAlnet07	.042
299	convnext_tiny_imagenet_full_seed-0	.034
300	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
301	resnet50_hvs_wzc	.023
302	ReAlnet04_cornet	.016
303	ReAlnet04	.016
304	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
305	vit_large_clip336_openai

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

0.81.

Note that scores are relative to this ceiling.

Data: Ferguson2024llh

Metric: value_delta