Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

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

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