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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024lle-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	pr1_stl10_disentangled_alpha04	1.0
2	ReAlnet10_ALL	1.0
3	alexnet_training_seed_08	1.0
4	alexnet_training_seed_03	1.0
5	ReAlnet10_cornet	1.0
6	mobilenet_v2_0_5_224	1.0
7	ReAlnet10	1.0
8	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
9	AdvProp_efficientnet-b8	1.0
10	resnet50_imagenet_1_seed-0	1.0
11	mobilenet_v2_1_0_160	1.0
12	densenet-169	1.0
13	resnet50-vicregl0p9	1.0
14	deit_small_imagenet_10_seed-0	1.0
15	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
16	resnet50_tutorial	1.0
17	resnext101_32x48d_wsl	1.0
18	gabor_filter_entropy_4x4_v2	1.0
19	ReAlnet05_ALL	1.0
20	yudixie_resnet50_random_0_240908	1.0
21	ReAlnet08_cornet	1.0
22	vgg_16	1.0
23	ReAlnet08	1.0
24	resnet50_robust_l2_eps1	1.0
25	resnet50-vicregl0p75	1.0
26	focalnet_tiny_lrf_in1k	1.0
27	gabor_filter_entropy_4x4_v2_forcedCosine	1.0
28	eva02_large_in22k	1.0
29	resnet50_hvs_wzc	1.0
30	vgg_19	1.0
31	yudixie_resnet50_distance_rotation_0_240908	1.0
32	resnet50_simsiam_linhead	1.0
33	resnet50-SIN_IN	1.0
34	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
35	vit_base_patch16_clip_224:openai_ft_in1k	1.0
36	deit_base_imagenet_full_seed-0	1.0
37	cvt_cvt-21-384-in1k_4_LucyV4	1.0
38	resnet152_imagenet_full	1.0
39	ReAlnet01_cornet_fov12	.967
40	ReAlnet07_ALL	.967
41	mobilenet_v2_1_3_224	.967
42	shufflenet_v2_x1_0	.967
43	omnivore_swinS	.967
44	yudixie_resnet50_imagenet1kpret_0_240908	.911
45	alexnet_training_seed_01	.911
46	inception_v1	.911
47	Res2Net50_26w_4s	.911
48	efficientnet_b0	.911
49	BiT-S-R152x2	.911
50	resnet152_ecoset_full	.911
51	AlexNet_SIN	.875
52	yudixie_resnet50_distance_translation_rotation_0_240908	.875
53	alexnet_training_seed_02	.875
54	yudixie_resnet50_rotation_reg_0_240908	.875
55	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.875
56	resnext101_32x32d_wsl	.875
57	convnext_base_fb_in1k_gram_aligned_dinov3	.825
58	predictive_coding_pc	.825
59	resnet50_st_wzc_2	.825
60	briaai_rmbg_1_4	.825
61	ReAlnet04_cornet	.825
62	ReAlnet04	.825
63	artResNet18_1	.825
64	convnext_tiny_imagenet_full_seed-0	.825
65	resnet-50-robust	.825
66	resnext101_32x16d_wsl	.793
67	convnext_base_fb_in1k	.793
68	convnext_xlarge:fb_in22k_ft_in1k	.793
69	AT_efficientnet-b2	.793
70	AdvProp_efficientnet-b2	.793
71	mehrer2020_alexnet_training_seed_01	.747
72	compact_resnet50_robust_IT	.747
73	inception_v3	.747
74	mehrer2020_alexnet_training_seed_07	.747
75	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
76	efficientnet_b1_imagenet_full	.747
77	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.747
78	resnet34_ecoset_full	.747
79	resnet50_st_wzc_seed3_2_323	.718
80	alexnet_fov4	.718
81	mobilenet_v2_0_75_224	.718
82	resnet50_byol_linhead	.718
83	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.718
84	BiT-S-R101x1	.718
85	yudixie_resnet18_random_0_240719	.718
86	voneresnet-50-non_stochastic	.718
87	deepeisnn_ei_imagenet_resnet18	.676
88	compact_vgg19_V4	.676
89	mobilenet_v2_1_0_192	.676
90	resnet50_simclr_linhead_01norm	.676
91	resnet50_vicreg_linhead	.676
92	cvt_cvt-21-224-in1k_4_LucyV4	.676
93	cvt_cvt-13-224-in1k_4_LucyV4	.676
94	ReAlnet08_ALL	.650
95	resnet_50_v2	.650
96	resnet_50_v1	.650
97	resnet50-sup	.650
98	AdvProp_efficientnet-b6	.650
99	vit_large_clip336_openai	.612
100	yolos_tiny	.612
101	nasnet_mobile	.612
102	mehrer2020_alexnet_training_seed_08	.612
103	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.612
104	resnet50_imagenet_full	.612
105	convnext_large_clip_laion2b_finelayers	.588
106	resnet_50_v1_spiking_l4a	.588
107	resnet_50_v1_spiking	.588
108	resnet50-vicreg	.588
109	seresnext50_32x4d	.554
110	resnet50_st_wzc_seed6_2_323	.554
111	vit_base_patch16_dinov3-lvd1689m	.554
112	compact_cornets_IT	.554
113	ReAlnet03_ALL	.554
114	ReAlnet02_ALL	.554
115	resnet50-SIN_IN_IN	.554
116	vit_relpos_base_patch16_clsgap_224:sw_in1k	.554
117	vit_large_patch14_clip_336:laion2b_ft_in1k	.554
118	yudixie_resnet18_translation_reg_0_240719	.554
119	resnet34_imagenet_full	.554
120	convnext_xxlarge_clip	.532
121	alexnet_training_seed_06	.532
122	ReAlnet06_cornet	.532
123	vonegrcnn_62e_nobn	.532
124	ReAlnet06	.532
125	mehrer2020_alexnet_training_seed_10	.532
126	efficientnet-b7	.532
127	resnet-18_test_m	.532
128	convnext_tiny:in12k_ft_in1k	.532
129	BiT-S-R50x1	.532
130	cv_18_dagger_408_pretrained	.502
131	ReAlnet04_ALL	.502
132	ReAlnet01_ALL	.502
133	resnet_50_v1_spiking_l4	.502
134	alexnet_training_seed_09	.502
135	mobilenet_v2_0_75_192	.502
136	VOneCORnet-S	.502
137	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.502
138	antialiased-r50	.502
139	blt_vs	.502
140	yudixie_resnet18_distance_translation_0_240719	.502
141	custom_model_cv_18_dagger_408	.502
142	ReAlnet07_cornet	.482
143	ReAlnet07	.482
144	yudixie_wbh_object_class_scaling_0415_run_2	.454
145	compact_vgg19_IT	.454
146	compact_resnet50_IT	.454
147	ReAlnet09_ALL	.454
148	ijepa_vith14_linhead	.454
149	voneresnet-50	.454
150	resnet50-barlow	.454
151	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.454
152	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.454
153	resnext101_32x8d_wsl	.454
154	compact_resnet50_V4	.436
155	resnet50_primary_visual_cortex	.436
156	efficientnet_b2_imagenet_full	.436
157	vit_huge_clip336_laion	.411
158	deit3_base_patch16_224_fb_in1k	.411
159	ReAlnet06_ALL	.411
160	alexnet_training_seed_10	.411
161	alexnet_training_seed_05	.411
162	ReAlnet01_cornet	.411
163	resnet50_barlowtwins_linhead	.411
164	mehrer2020_alexnet_training_seed_02	.411
165	ReAlnet01	.411
166	convnext_base:clip_laiona_augreg_ft_in1k_384	.411
167	resnet_SIN_IN_FT_IN	.411
168	yudixie_resnet18_category_class_0_240719	.411
169	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.411
170	voneresnet-50-robust	.395
171	dinov2_vitl14_reg_lc_featread	.372
172	alexnet_fov16	.372
173	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.372
174	resnet_152_v2	.372
175	mehrer2020_alexnet_training_seed_03	.372
176	yudixie_resnet18_distance_translation_rotation_0_240719	.372
177	resnet101_ecoset_full	.372
178	resnet-152_v2_pytorch	.372
179	ReAlnet03_cornet	.358
180	inception_v4	.358
181	yudixie_resnet50_translation_rotation_0_240908	.358
182	ReAlnet03	.358
183	yudixie_wbh_object_class_scaling_0415_run_3	.337
184	resnet50_st_wzc_seed7_2_323	.337
185	vit_base_patch14_dinov2-lvd142m	.337
186	ReAlnet05_cornet	.337
187	mobilenet_v2_1_0_128	.337
188	ReAlnet05	.337
189	resnet50-moclr8deg	.337
190	convnext_large:fb_in22k_ft_in1k	.337
191	BiT-S-R50x3	.337
192	deit_small_imagenet_1_seed-0	.337
193	yudixie_resnet18_distance_reg_0_240719	.337
194	yudixie_resnet18_translation_rotation_0_240719	.337
195	BiT-S-R152x4	.324
196	vonegrcnn_47e	.324
197	dinov2_vitg14_reg_lc	.305
198	yudixie_wbh_object_class_scaling_0415_imagenet	.305
199	deit3_base_patch16_224_fb_in22k_ft_in1k	.305
200	resnet50_ewconplus_wzc_seed5_2__323	.305
201	AlexNet_SIN_fov12	.305
202	pnasnet_large	.305
203	BiT-S-R101x3	.305
204	vonegrcnn_52e_full	.305
205	resnet18_ecoset_full	.305
206	omnivore_swinB	.293
207	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.276
208	AlexNet_SIN_fov4	.276
209	resnet_50_v1_spiking_l3	.276
210	alexnet_training_seed_04	.276
211	nasnet_large	.276
212	mobilenet_v2_0_5_192	.276
213	vit_large_patch14_clip_224:openai_ft_in1k	.276
214	resnet50_imagenet_100_seed-0	.276
215	cvt_cvt-13-384-in1k_4_LucyV4	.276
216	compact_cornets_V4	.265
217	convnext_tiny_sup	.265
218	dinov2_vitg14_lc	.250
219	yudixie_wbh_object_class_scaling_0415_run_0	.250
220	AlexNet_SIN_fov16	.250
221	ReAlnet01_cornet_fov16	.250
222	resnet50_ewconplus_wzc	.250
223	yudixie_resnet50_category_class_0_240908	.250
224	yudixie_resnet50_object_class_0_240908	.250
225	mehrer2020_alexnet_training_seed_04	.250
226	deit_small_imagenet_100_seed-0	.250
227	alexnet	.250
228	deepeisnn_ei_cifar10_vgg19	.240
229	vit_base_patch14_reg4_dinov2-lvd142m	.226
230	pnasnet_large_halfPrecision	.226
231	mobilenet_v2_0_75_160	.226
232	vit_large_patch14_clip_224:laion2b_ft_in1k	.226
233	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.226
234	convnext_small_imagenet_full_seed-0	.226
235	hmax	.226
236	convnext_large_in22k_supervised	.205
237	deepeisnn_ei_cifar10_resnet18	.205
238	alexnet_training_seed_01_fov12	.205
239	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.205
240	mobilenet_v2_1_4_224	.205
241	grcnn	.205
242	yudixie_resnet50_distance_translation_0_240908	.205
243	yudixie_resnet18_imagenet1kpret_0_240719	.205
244	yudixie_resnet18_object_class_0_240719	.205
245	mobilenet_v2_1-4_224_pytorch	.205
246	compact_resnet50_robust_V4	.197
247	eicircuit_resnet18_bn_20260919	.186
248	resnet_101_v1	.186
249	resnet_101_v2	.178
250	gabor_filter_mean_abs_4x4_v2	.168
251	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.168
252	AdvProp_efficientnet-b7	.168
253	convnext_small_imagenet_100_seed-0	.168
254	effnetb1_272x240	.168
255	resnet_152_v1	.161
256	convnext_base_fb_in22k_ft_in1k	.152
257	xception	.152
258	mehrer2020_alexnet_training_seed_09	.152
259	mehrer2020_alexnet_training_seed_01_fov4	.152
260	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.152
261	resnet50_robust_l2_eps3	.152
262	imagenet_l2_3_0	.152
263	yudixie_resnet18_rotation_reg_0_240719	.146
264	dinov2_vitl14_reg_lc	.138
265	alexnet_fov12	.138
266	ReAlnet09_cornet	.138
267	ReAlnet09	.138
268	yudixie_resnet18_distance_rotation_0_240719	.138
269	gabor_filter_entropy_4x4	.125
270	regnety_032	.125
271	dinov2_vitl14_lc_res336	.125
272	yudixie_resnet50_distance_reg_0_240908	.125
273	resnet50-vitoimagevidnet8	.125
274	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.125
275	resnet50-VITO-8deg-cc	.125
276	resnet50_imagenet_10_seed-0	.125
277	convnext_femto_ols:d1_in1k	.113
278	convnext_large_imagenet_full_seed-0	.113
279	convnext_base_imagenet_full_seed-0	.113
280	resnet18_imagenet_full	.113
281	densenet-201	.108
282	ViT_L_32_imagenet1k	.108
283	mehrer2020_alexnet_training_seed_01_fov12	.102
284	resnet18_fair	.102
285	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.092
286	alexnet_training_seed_01_fov16	.092
287	ReAlnet01_cornet_fov4	.092
288	mehrer2020_alexnet_training_seed_06	.092
289	pnasnet_large_pytorch	.092
290	dinov2_vitl14_lc	.076
291	ReAlnet02_cornet	.069
292	yudixie_resnet50_translation_reg_0_240908	.069
293	ReAlnet02	.069
294	mehrer2020_alexnet_training_seed_05	.069
295	convnext_small_imagenet_10_seed-0	.069
296	efficientnet_b0_imagenet_full	.069
297	resnet50_ecoset_full	.069
298	grcnn_109	.062
299	resnet50-SIN	.062
300	convnext_small_imagenet_1_seed-0	.062
301	AdvProp_efficientnet-b4	.056
302	alexnet_training_seed_07	.051
303	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.051
304	alexnet_training_seed_01_fov4	.049
305	densenet-121	.046
306	deit_small_imagenet_full_seed-0	.046
307	mehrer2020_alexnet_training_seed_01_fov16	.034
308	deit_large_imagenet_full_seed-0	.025
309	resnet101_imagenet_full	.023
310	yudixie_wbh_object_class_scaling_0415_run_1
311	mobilenet_v2_1_0_224

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

0.83.

Note that scores are relative to this ceiling.

Data: Ferguson2024lle

Metric: value_delta