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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	alexnet_training_seed_09	1.0
2	deit_base_imagenet_full_seed-0	1.0
3	alexnet_training_seed_06	1.0
4	vit_large_patch14_clip_224:openai_ft_in1k	1.0
5	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
6	mobilenet_v2_1_0_128	1.0
7	deit_small_imagenet_10_seed-0	1.0
8	resnet50_imagenet_100_seed-0	1.0
9	ViT_L_32_imagenet1k	1.0
10	alexnet_training_seed_10	1.0
11	efficientnet_b1_imagenet_full	1.0
12	resnet50-SIN_IN_IN	1.0
13	convnext_femto_ols:d1_in1k	1.0
14	alexnet_training_seed_02	1.0
15	resnet_50_v1_spiking_l4a	1.0
16	mobilenet_v2_1_0_160	1.0
17	xception	1.0
18	resnet50-moclr8deg	1.0
19	resnet-152_v2_pytorch	1.0
20	resnet152_imagenet_full	1.0
21	resnet34_imagenet_full	1.0
22	yudixie_resnet50_object_class_0_240908	1.0
23	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
24	resnet50_tutorial	1.0
25	mobilenet_v2_1_0_192	1.0
26	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
27	alexnet_training_seed_01	1.0
28	efficientnet-b7	1.0
29	resnet_50_v1_spiking	1.0
30	cvt_cvt-13-384-in1k_4_LucyV4	1.0
31	compact_resnet50_robust_V4	1.0
32	efficientnet_b0_imagenet_full	1.0
33	vgg_16	1.0
34	cvt_cvt-21-224-in1k_4_LucyV4	.979
35	AdvProp_efficientnet-b8	.979
36	blt_vs	.951
37	resnet152_ecoset_full	.951
38	pnasnet_large_pytorch	.951
39	yudixie_resnet18_category_class_0_240719	.951
40	antialiased-r50	.951
41	AdvProp_efficientnet-b4	.951
42	vonegrcnn_52e_full	.951
43	mobilenet_v2_0_5_224	.888
44	yudixie_resnet18_distance_rotation_0_240719	.888
45	mobilenet_v2_1_0_224	.888
46	AdvProp_efficientnet-b7	.888
47	BiT-S-R50x3	.888
48	BiT-S-R50x1	.888
49	yudixie_resnet50_imagenet1kpret_0_240908	.862
50	efficientnet_b2_imagenet_full	.862
51	focalnet_tiny_lrf_in1k	.862
52	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.862
53	yudixie_resnet18_distance_translation_0_240719	.862
54	AdvProp_efficientnet-b2	.862
55	AT_efficientnet-b2	.862
56	deit_small_imagenet_100_seed-0	.805
57	mobilenet_v2_0_75_224	.805
58	resnext101_32x32d_wsl	.805
59	resnet18_ecoset_full	.805
60	yudixie_resnet18_object_class_0_240719	.805
61	inception_v1	.805
62	resnet50_primary_visual_cortex	.805
63	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.782
64	resnet18_imagenet_full	.782
65	resnet50_robust_l2_eps1	.782
66	artResNet18_1	.782
67	BiT-S-R152x4	.782
68	resnet50-vicregl0p9	.782
69	inception_v3	.730
70	mobilenet_v2_0_75_192	.730
71	resnet50_imagenet_1_seed-0	.730
72	yudixie_resnet18_rotation_reg_0_240719	.730
73	omnivore_swinB	.730
74	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.709
75	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.709
76	resnext101_32x48d_wsl	.709
77	yudixie_resnet18_translation_rotation_0_240719	.709
78	resnet50-VITO-8deg-cc	.709
79	efficientnet_b0	.709
80	resnet50-vitoimagevidnet8	.709
81	omnivore_swinS	.709
82	convnext_tiny_sup	.709
83	BiT-S-R101x1	.709
84	mobilenet_v2_1_3_224	.662
85	resnet_SIN_IN_FT_IN	.662
86	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.643
87	convnext_xlarge:fb_in22k_ft_in1k	.643
88	mobilenet_v2_0_5_192	.643
89	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.643
90	yudixie_resnet18_random_0_240719	.643
91	ReAlnet01_ALL	.643
92	resnet_101_v1	.643
93	alexnet_training_seed_05	.601
94	compact_vgg19_IT	.601
95	BiT-S-R152x2	.601
96	resnet_152_v1	.583
97	alexnet_training_seed_08	.583
98	inception_v4	.583
99	yudixie_resnet50_translation_reg_0_240908	.583
100	shufflenet_v2_x1_0	.583
101	VOneCORnet-S	.583
102	BiT-S-R101x3	.583
103	densenet-169	.583
104	AdvProp_efficientnet-b6	.545
105	yudixie_resnet50_distance_reg_0_240908	.529
106	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.529
107	mobilenet_v2_0_75_160	.529
108	mobilenet_v2_1-4_224_pytorch	.529
109	resnet-18_test_m	.529
110	yudixie_resnet18_distance_translation_rotation_0_240719	.529
111	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.529
112	resnet50-vicreg	.529
113	vonegrcnn_62e_nobn	.529
114	mobilenet_v2_1_4_224	.529
115	vonegrcnn_47e	.529
116	resnet50-vicregl0p75	.529
117	alexnet_training_seed_04	.494
118	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.494
119	densenet-201	.480
120	resnet_50_v1	.480
121	resnet50-sup	.480
122	yudixie_resnet18_distance_reg_0_240719	.448
123	yudixie_resnet50_translation_rotation_0_240908	.448
124	cvt_cvt-21-384-in1k_4_LucyV4	.435
125	resnet50_ewconplus_wzc	.435
126	yudixie_resnet50_category_class_0_240908	.435
127	resnet50_ecoset_full	.435
128	compact_resnet50_IT	.435
129	ReAlnet02_ALL	.435
130	nasnet_mobile	.435
131	grcnn	.435
132	convnext_small_imagenet_10_seed-0	.406
133	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.406
134	resnet_152_v2	.406
135	compact_resnet50_V4	.395
136	yudixie_resnet50_distance_rotation_0_240908	.395
137	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.395
138	compact_cornets_V4	.395
139	ReAlnet04_ALL	.395
140	resnet50_imagenet_10_seed-0	.369
141	resnet_50_v1_spiking_l4	.369
142	custom_model_cv_18_dagger_408	.369
143	alexnet_training_seed_07	.369
144	yudixie_resnet50_random_0_240908	.358
145	resnet50-SIN	.358
146	yudixie_resnet50_rotation_reg_0_240908	.358
147	effnetb1_272x240	.358
148	briaai_rmbg_1_4	.334
149	compact_resnet50_robust_IT	.334
150	deit_small_imagenet_full_seed-0	.325
151	vit_base_patch16_clip_224:openai_ft_in1k	.325
152	grcnn_109	.325
153	resnet50_robust_l2_eps3	.325
154	imagenet_l2_3_0	.325
155	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.303
156	convnext_small_imagenet_full_seed-0	.294
157	Res2Net50_26w_4s	.294
158	yudixie_resnet18_translation_reg_0_240719	.294
159	densenet-121	.294
160	deit_large_imagenet_full_seed-0	.275
161	convnext_tiny:in12k_ft_in1k	.267
162	convnext_base_imagenet_full_seed-0	.267
163	yolos_tiny	.267
164	resnet_50_v2	.267
165	ReAlnet06	.242
166	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.242
167	ReAlnet02_cornet	.242
168	resnet50_imagenet_full	.242
169	deit_small_imagenet_1_seed-0	.242
170	yudixie_resnet50_distance_translation_0_240908	.242
171	ReAlnet06_cornet	.242
172	resnet50-barlow	.242
173	pnasnet_large	.242
174	resnet_101_v2	.242
175	ReAlnet02	.242
176	ReAlnet10_ALL	.242
177	alexnet_training_seed_03	.226
178	ReAlnet06_ALL	.220
179	resnet_50_v1_spiking_l3	.205
180	resnet101_imagenet_full	.199
181	voneresnet-50-non_stochastic	.199
182	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.199
183	convnext_large_imagenet_full_seed-0	.181
184	ReAlnet07_ALL	.181
185	ReAlnet09_ALL	.181
186	yudixie_resnet50_distance_translation_rotation_0_240908	.164
187	ReAlnet09	.164
188	resnet-50-robust	.164
189	cvt_cvt-13-224-in1k_4_LucyV4	.164
190	resnet50-SIN_IN	.164
191	nasnet_large	.164
192	voneresnet-50	.164
193	ReAlnet09_cornet	.164
194	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
195	resnet101_ecoset_full	.149
196	ReAlnet05	.135
197	vit_large_patch14_clip_336:laion2b_ft_in1k	.135
198	ReAlnet05_cornet	.135
199	compact_cornets_IT	.135
200	convnext_small_imagenet_1_seed-0	.126
201	vit_large_patch14_clip_224:laion2b_ft_in1k	.122
202	vgg_19	.122
203	convnext_small_imagenet_100_seed-0	.111
204	yudixie_resnet18_imagenet1kpret_0_240719	.111
205	voneresnet-50-robust	.111
206	compact_vgg19_V4	.101
207	ReAlnet05_ALL	.101
208	ReAlnet08_ALL	.101
209	ReAlnet01_cornet	.083
210	ReAlnet01	.083
211	ReAlnet03_ALL	.075
212	convnext_base:clip_laiona_augreg_ft_in1k_384	.068
213	resnext101_32x8d_wsl	.068
214	convnext_large:fb_in22k_ft_in1k	.068
215	ReAlnet03	.062
216	ReAlnet03_cornet	.062
217	ReAlnet10	.051
218	ReAlnet10_cornet	.051
219	ReAlnet08	.046
220	resnet34_ecoset_full	.046
221	ReAlnet08_cornet	.046
222	ReAlnet07	.042
223	ReAlnet07_cornet	.042
224	convnext_tiny_imagenet_full_seed-0	.034
225	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.031
226	ReAlnet04_cornet	.016
227	ReAlnet04	.016
228	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