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("Ferguson2024quarter-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
2	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
3	mobilenet_v2_0_5_224	1.0
4	pnasnet_large_halfPrecision	1.0
5	yudixie_resnet50_translation_reg_0_240908	1.0
6	omnivore_swinB	1.0
7	cv_18_dagger_408_pretrained	1.0
8	mobilenet_v2_0_75_160	1.0
9	resnet50_primary_visual_cortex	1.0
10	resnet50_ecoset_full	1.0
11	alexnet_training_seed_04	1.0
12	resnext101_32x8d_wsl	1.0
13	resnet50-sup	1.0
14	resnet_50_v1	1.0
15	resnet_152_v1	.950
16	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.950
17	resnet34_ecoset_full	.950
18	deit_large_imagenet_full_seed-0	.950
19	mobilenet_v2_0_75_192	.950
20	resnet18_imagenet_full	.950
21	effnetb1_272x240	.950
22	ViT_L_32_imagenet1k	.950
23	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.950
24	inception_v4	.950
25	convnext_large:fb_in22k_ft_in1k	.950
26	resnet18_ecoset_full	.923
27	resnet_50_v1_spiking_l4a	.923
28	resnext101_32x48d_wsl	.923
29	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.923
30	BiT-S-R152x2	.923
31	cvt_cvt-21-224-in1k_4_LucyV4	.860
32	convnext_tiny:in12k_ft_in1k	.836
33	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.836
34	resnet50_tutorial	.836
35	ReAlnet01_cornet_fov16	.836
36	mobilenet_v2_1_0_224	.836
37	antialiased-r50	.836
38	resnet_SIN_IN_FT_IN	.836
39	vit_large_patch14_clip_336:laion2b_ft_in1k	.779
40	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.779
41	yudixie_resnet50_category_class_0_240908	.757
42	ReAlnet01_cornet_fov4	.757
43	efficientnet_b0	.757
44	deit_small_imagenet_1_seed-0	.757
45	grcnn	.757
46	cvt_cvt-21-384-in1k_4_LucyV4	.706
47	alexnet_training_seed_05	.706
48	yudixie_resnet18_imagenet1kpret_0_240719	.706
49	yudixie_resnet18_distance_reg_0_240719	.706
50	BiT-S-R152x4	.706
51	resnet_50_v2	.686
52	yudixie_resnet50_distance_translation_rotation_0_240908	.686
53	resnet_50_v1_spiking	.686
54	convnext_base_imagenet_full_seed-0	.686
55	voneresnet-50-non_stochastic	.686
56	convnext_large_imagenet_full_seed-0	.686
57	AdvProp_efficientnet-b2	.686
58	AT_efficientnet-b2	.686
59	convnext_xlarge:fb_in22k_ft_in1k	.639
60	convnext_small_imagenet_full_seed-0	.621
61	efficientnet-b7	.621
62	convnext_tiny_sup	.621
63	artResNet18_1	.579
64	alexnet_training_seed_06	.563
65	alexnet_training_seed_10	.563
66	resnet50_imagenet_1_seed-0	.563
67	efficientnet_b2_imagenet_full	.563
68	vonegrcnn_62e_nobn	.563
69	AdvProp_efficientnet-b7	.563
70	imagenet_l2_3_0	.563
71	resnet50_robust_l2_eps3	.563
72	cvt_cvt-13-224-in1k_4_LucyV4	.524
73	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.524
74	vit_base_patch14_dinov2-lvd142m	.524
75	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.510
76	yudixie_resnet50_imagenet1kpret_0_240908	.510
77	deit_base_imagenet_full_seed-0	.510
78	mobilenet_v2_1_0_128	.510
79	densenet-201	.510
80	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.510
81	resnet50_imagenet_100_seed-0	.510
82	resnet101_imagenet_full	.510
83	vit_base_patch16_dinov3-lvd1689m	.510
84	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.510
85	resnet50-SIN_IN_IN	.510
86	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.510
87	ReAlnet01_cornet_fov12	.510
88	resnet50_robust_l2_eps1	.510
89	vgg_16	.510
90	BiT-S-R50x3	.510
91	resnet50-vicregl0p75	.510
92	densenet-121	.510
93	deit_small_imagenet_full_seed-0	.475
94	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.475
95	resnext101_32x32d_wsl	.475
96	custom_model_cv_18_dagger_408	.475
97	resnet_50_v1_spiking_l3	.475
98	resnet50-vicreg	.475
99	BiT-S-R50x1	.475
100	inception_v3	.461
101	AlexNet_SIN	.461
102	resnet-152_v2_pytorch	.461
103	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.461
104	vonegrcnn_47e	.461
105	densenet-169	.461
106	vit_relpos_base_patch16_clsgap_224:sw_in1k	.430
107	mobilenet_v2_1_0_160	.430
108	yudixie_resnet18_random_0_240719	.430
109	yudixie_resnet50_rotation_reg_0_240908	.430
110	mobilenet_v2_0_5_192	.418
111	yudixie_resnet18_distance_rotation_0_240719	.418
112	Res2Net50_26w_4s	.418
113	grcnn_109	.418
114	vit_base_patch16_clip_224:openai_ft_in1k	.390
115	yudixie_resnet18_distance_translation_0_240719	.390
116	vit_large_patch14_clip_224:openai_ft_in1k	.379
117	resnet50_imagenet_10_seed-0	.379
118	blt_vs	.379
119	focalnet_tiny_lrf_in1k	.379
120	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.379
121	alexnet_training_seed_01_fov4	.379
122	convnext_base:clip_laiona_augreg_ft_in1k_384	.379
123	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.353
124	yudixie_resnet18_distance_translation_rotation_0_240719	.343
125	xception	.343
126	resnet-18_test_m	.320
127	ReAlnet05	.311
128	alexnet_training_seed_02	.311
129	briaai_rmbg_1_4	.311
130	compact_resnet50_IT	.311
131	yudixie_resnet50_distance_rotation_0_240908	.311
132	ReAlnet05_cornet	.311
133	resnet152_ecoset_full	.289
134	nasnet_mobile	.289
135	alexnet_fov12	.281
136	deit_small_imagenet_10_seed-0	.281
137	deit_small_imagenet_100_seed-0	.281
138	alexnet_fov16	.281
139	efficientnet_b1_imagenet_full	.281
140	yudixie_resnet50_distance_translation_0_240908	.281
141	cvt_cvt-13-384-in1k_4_LucyV4	.262
142	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.262
143	ReAlnet07	.255
144	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.255
145	alexnet	.255
146	resnet152_imagenet_full	.255
147	resnet50-SIN	.255
148	ReAlnet07_cornet	.255
149	vgg_19	.255
150	compact_cornets_V4	.255
151	compact_cornets_IT	.255
152	alexnet_training_seed_01_fov12	.255
153	resnet34_imagenet_full	.231
154	resnet-50-robust	.231
155	mobilenet_v2_1-4_224_pytorch	.231
156	yudixie_resnet18_translation_rotation_0_240719	.231
157	AlexNet_SIN_fov12	.231
158	resnet50-barlow	.231
159	mobilenet_v2_1_4_224	.231
160	BiT-S-R101x3	.231
161	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.215
162	vit_base_patch14_reg4_dinov2-lvd142m	.215
163	ReAlnet10	.209
164	yudixie_resnet50_distance_reg_0_240908	.209
165	efficientnet_b0_imagenet_full	.209
166	ReAlnet01_cornet	.209
167	VOneCORnet-S	.209
168	ReAlnet01	.209
169	alexnet_training_seed_01_fov16	.209
170	ReAlnet10_cornet	.209
171	alexnet_fov4	.189
172	convnext_small_imagenet_1_seed-0	.189
173	resnet50_imagenet_full	.189
174	BiT-S-R101x1	.189
175	resnet50_ewconplus_wzc	.171
176	ReAlnet03	.171
177	ReAlnet09	.171
178	resnet101_ecoset_full	.171
179	ReAlnet03_cornet	.171
180	alexnet_training_seed_07	.171
181	omnivore_swinS	.171
182	shufflenet_v2_x1_0	.171
183	yudixie_resnet50_translation_rotation_0_240908	.171
184	inception_v1	.171
185	ReAlnet09_cornet	.171
186	resnet_101_v1	.171
187	convnext_small_imagenet_10_seed-0	.155
188	ReAlnet02_cornet	.155
189	ReAlnet04_cornet	.155
190	voneresnet-50	.155
191	ReAlnet04	.155
192	ReAlnet02	.155
193	resnet50-vicregl0p9	.155
194	resnet_152_v2	.155
195	ReAlnet06	.141
196	yudixie_resnet50_object_class_0_240908	.141
197	convnext_small_imagenet_100_seed-0	.141
198	mobilenet_v2_1_0_192	.141
199	alexnet_training_seed_01	.141
200	aughost_fair_resnet18	.141
201	resnet50-VITO-8deg-cc	.141
202	ReAlnet06_cornet	.141
203	AlexNet_SIN_fov16	.141
204	resnet50-vitoimagevidnet8	.141
205	AdvProp_efficientnet-b8	.141
206	convnext_femto_ols:d1_in1k	.141
207	yudixie_resnet50_random_0_240908	.127
208	resnet_50_v1_spiking_l4	.127
209	ReAlnet08	.127
210	pnasnet_large_pytorch	.127
211	compact_resnet50_robust_V4	.127
212	ReAlnet08_cornet	.127
213	ReAlnet09_ALL	.127
214	resnet_101_v2	.119
215	alexnet_training_seed_08	.115
216	yolos_tiny	.115
217	compact_vgg19_IT	.115
218	mobilenet_v2_1_3_224	.115
219	AdvProp_efficientnet-b4	.115
220	yudixie_resnet18_object_class_0_240719	.104
221	ReAlnet07_ALL	.104
222	alexnet_training_seed_03	.095
223	yudixie_resnet18_translation_reg_0_240719	.095
224	compact_resnet50_robust_IT	.095
225	vonegrcnn_52e_full	.095
226	ReAlnet08_ALL	.095
227	yudixie_resnet18_rotation_reg_0_240719	.086
228	alexnet_training_seed_09	.078
229	compact_resnet50_V4	.078
230	resnet50-SIN_IN	.078
231	ReAlnet03_ALL	.078
232	voneresnet-50-robust	.078
233	convnext_tiny_imagenet_full_seed-0	.070
234	ReAlnet04_ALL	.070
235	yudixie_resnet18_category_class_0_240719	.064
236	ReAlnet01_ALL	.064
237	resnet50-moclr8deg	.064
238	ReAlnet05_ALL	.064
239	ReAlnet10_ALL	.058
240	ReAlnet06_ALL	.052
241	nasnet_large	.047
242	AdvProp_efficientnet-b6	.043
243	compact_vgg19_V4	.043
244	AlexNet_SIN_fov4	.021
245	ReAlnet02_ALL	.019
246	mobilenet_v2_0_75_224
247	hmax
248	pnasnet_large

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

0.88.

Note that scores are relative to this ceiling.

Data: Ferguson2024quarter

Metric: value_delta