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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024gray_hard-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	deit_small_imagenet_100_seed-0	1.0
2	deit_large_imagenet_full_seed-0	1.0
3	ReAlnet10	1.0
4	pnasnet_large_pytorch	1.0
5	compact_resnet50_robust_V4	1.0
6	resnet101_ecoset_full	1.0
7	omnivore_swinB	1.0
8	artResNet18_1	1.0
9	ReAlnet10_cornet	1.0
10	BiT-S-R101x1	1.0
11	convnext_tiny:in12k_ft_in1k	1.0
12	yudixie_resnet18_object_class_0_240719	1.0
13	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
14	convnext_femto_ols:d1_in1k	1.0
15	resnext101_32x16d_wsl	1.0
16	inception_v4	1.0
17	ReAlnet01_ALL	1.0
18	vgg_16	1.0
19	deit_small_imagenet_1_seed-0	.971
20	ReAlnet02_ALL	.971
21	voneresnet-50-robust	.971
22	compact_resnet50_robust_IT	.971
23	BiT-S-R152x2	.971
24	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.942
25	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.942
26	resnet_50_v1_spiking_l4	.942
27	vit_large_patch14_clip_224:openai_ft_in1k	.942
28	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.942
29	vit_large_patch14_clip_336:laion2b_ft_in1k	.942
30	cv_18_dagger_408_pretrained	.942
31	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.942
32	vit_base_patch16_dinov3-lvd1689m	.942
33	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.942
34	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.942
35	vit_base_patch14_dinov2-lvd142m	.942
36	vit_base_patch14_reg4_dinov2-lvd142m	.942
37	vit_large_patch14_clip_224:laion2b_ft_in1k	.942
38	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.942
39	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.942
40	resnet50-VITO-8deg-cc	.942
41	nasnet_mobile	.942
42	resnet50-vitoimagevidnet8	.942
43	yudixie_resnet50_imagenet1kpret_0_240908	.883
44	yudixie_resnet50_imagenet1kpret_0_240312	.883
45	deit_small_imagenet_10_seed-0	.883
46	pnasnet_large_halfPrecision	.883
47	nasnet_large	.883
48	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.883
49	convnext_large:fb_in22k_ft_in1k	.883
50	ReAlnet05	.855
51	alexnet_training_seed_06	.855
52	compact_resnet50_IT	.855
53	ReAlnet05_cornet	.855
54	custom_model_cv_18_dagger_408	.855
55	alexnet_fov12	.802
56	resnet_SIN_IN_FT_IN	.802
57	resnet50-vicregl0p9	.802
58	ReAlnet07	.777
59	alexnet_training_seed_08	.777
60	briaai_rmbg_1_4	.777
61	resnet50_imagenet_full	.777
62	ReAlnet07_cornet	.777
63	grcnn	.777
64	yudixie_resnet50_distance_translation_rotation_0_240908	.777
65	yudixie_resnet50_object_class_0_240908	.728
66	convnext_xlarge:fb_in22k_ft_in1k	.728
67	cvt_cvt-21-224-in1k_4_LucyV4	.728
68	yudixie_resnet18_distance_translation_rotation_0_240719	.728
69	yudixie_resnet50_rotation_reg_0_240908	.728
70	ReAlnet07_ALL	.728
71	resnet50-vicregl0p75	.728
72	focalnet_tiny_lrf_in1k	.728
73	alexnet_ks_torevert	.706
74	cvt_cvt-13-224-in1k_4_LucyV4	.706
75	alexnet	.706
76	ViT_L_32_imagenet1k	.706
77	ReAlnet01_cornet_fov4	.706
78	resnet50-vicreg	.706
79	VOneCORnet-S	.706
80	mobilenet_v2_1_0_224	.706
81	resnet_152_v2	.706
82	ReAlnet09_ALL	.706
83	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.662
84	resnet50_tutorial	.662
85	ReAlnet04_ALL	.662
86	ReAlnet06_ALL	.662
87	resnet18_imagenet21kP	.641
88	fixres_resnext101_32x48d_wsl	.641
89	ReAlnet03	.641
90	yolos_tiny	.641
91	resnet18_imagenet_full	.641
92	ReAlnet03_cornet	.641
93	vit_base_patch16_clip_224:openai_ft_in1k	.641
94	resnet-18_test_m	.641
95	Res2Net50_26w_4s	.641
96	mobilenet_v2_1_3_224	.641
97	ReAlnet05_ALL	.641
98	omnivore_swinS	.641
99	inception_v1	.641
100	alexnet_training_seed_05	.601
101	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.601
102	yudixie_resnet18_distance_rotation_0_240719	.601
103	resnet18_ecoset_full	.583
104	resnet50_ewconplus_wzc	.583
105	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.583
106	mobilenet_v2_1_0_128	.583
107	cvt_cvt-13-384-in1k_4_LucyV4	.583
108	resnet50_imagenet_1_seed-0	.583
109	yudixie_resnet18_random_0_240719	.583
110	alexnet_training_seed_01_fov4	.583
111	AdvProp_efficientnet-b7	.583
112	AlexNet_SIN	.546
113	pnasnet_large	.546
114	ReAlnet03_ALL	.546
115	resnet_101_v2	.546
116	antialiased-rnext101_32x8d	.529
117	resnet_50_v1_spiking_l4a	.529
118	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.529
119	compact_vgg19_IT	.529
120	BiT-S-R101x3	.529
121	yudixie_resnet50_distance_reg_0_240908	.496
122	alexnet_training_seed_07	.496
123	deit_base_imagenet_full_seed-0	.481
124	blt_vs	.481
125	ReAlnet09	.481
126	compact_resnet50_V4	.481
127	yudixie_resnet18_translation_reg_0_240719	.481
128	ReAlnet09_cornet	.481
129	vonegrcnn_47e	.481
130	alexnet_training_seed_01	.451
131	ReAlnet08_ALL	.451
132	convnext_tiny_imagenet_full_seed-0	.437
133	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.437
134	densenet-201	.437
135	ReAlnet01_cornet	.437
136	resnext101_32x8d_wsl	.437
137	hmax	.437
138	mobilenet_v2_1-4_224_pytorch	.437
139	AlexNet_SIN_fov4	.437
140	vgg_19	.437
141	mobilenet_v2_1_4_224	.437
142	ReAlnet01	.437
143	resnet_101_v1	.437
144	alexnet_training_seed_03	.437
145	convnext_base:clip_laiona_augreg_ft_in1k_384	.437
146	mobilenet_v2_1_0_192	.410
147	resnet50-SIN_IN_IN	.410
148	xception	.410
149	convnext_small_imagenet_100_seed-0	.397
150	yudixie_resnet50_random_0_240908	.397
151	ReAlnet08	.397
152	alexnet_training_seed_04	.397
153	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.397
154	alexnet_training_seed_10	.397
155	resnet50-SIN	.397
156	compact_vgg19_V4	.397
157	ReAlnet04_cornet	.397
158	ReAlnet08_cornet	.397
159	resnet50-barlow	.397
160	resnet50-moclr8deg	.397
161	ReAlnet04	.397
162	resnet50_primary_visual_cortex	.397
163	resnet50_imagenet_10_seed-0	.372
164	resnext101_32x32d_wsl	.372
165	deit_small_imagenet_full_seed-0	.361
166	AdvProp_efficientnet-b6	.361
167	antialiased-r50	.361
168	densenet-169	.361
169	yudixie_resnet18_translation_rotation_0_240719	.338
170	compact_cornets_IT	.338
171	efficientnet_b1_imagenet_full	.328
172	vonegrcnn_62e_nobn	.328
173	alexnet_training_seed_01_fov12	.328
174	convnext_small_imagenet_1_seed-0	.307
175	resnext101_32x48d_wsl	.298
176	resnet34_ecoset_full	.298
177	resnet50_ecoset_full	.298
178	yudixie_resnet50_distance_translation_0_240908	.298
179	ReAlnet01_cornet_fov16	.298
180	alexnet_training_seed_01_fov16	.298
181	convnext_small_imagenet_10_seed-0	.279
182	ReAlnet10_ALL	.279
183	ReAlnet06	.270
184	resnet50_eMMCR_Vanilla	.270
185	alexnet_training_seed_02	.270
186	mobilenet_v2_0_75_160	.270
187	mobilenet_v2_0_5_224	.270
188	resnet50_imagenet_100_seed-0	.270
189	resnet34_imagenet_full	.270
190	ReAlnet01_cornet_fov12	.270
191	aughost_fair_resnet18	.270
192	yudixie_resnet50_translation_reg_0_240908	.270
193	ReAlnet06_cornet	.270
194	voneresnet-50	.270
195	convnext_tiny_sup	.270
196	yudixie_resnet18_rotation_reg_0_240719	.253
197	AlexNet_SIN_fov16	.253
198	resnet152_ecoset_full	.246
199	voneresnet-50-non_stochastic	.246
200	alexnet_fov16	.246
201	ReAlnet02_cornet	.246
202	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.246
203	ReAlnet02	.246
204	yudixie_resnet50_category_class_0_240908	.230
205	resnet101_imagenet_full	.223
206	convnext_small_imagenet_full_seed-0	.223
207	resnet_50_v1_spiking_l3	.223
208	AdvProp_efficientnet-b8	.223
209	BiT-S-R50x1	.223
210	densenet-121	.223
211	resnet_50_v1	.203
212	resnet50-sup	.203
213	AdvProp_efficientnet-b4	.203
214	BiT-S-R152x4	.190
215	inception_v3	.184
216	alexnet_fov4	.184
217	resnet152_imagenet_full	.184
218	efficientnet_b0_imagenet_full	.184
219	yudixie_resnet18_category_class_0_240719	.184
220	antialias-resnet152	.173
221	AlexNet_SIN_fov12	.173
222	alexnet_training_seed_09	.167
223	yudixie_resnet50_translation_rotation_0_240908	.167
224	grcnn_109	.167
225	vonegrcnn_52e_full	.167
226	BiT-S-R50x3	.167
227	cvt_cvt-21-384-in1k_4_LucyV4	.157
228	tv_efficientnet-b1	.152
229	effnetb1_272x240	.152
230	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.152
231	yudixie_resnet18_distance_translation_0_240719	.152
232	shufflenet_v2_x1_0	.152
233	resnet_50_v2	.152
234	mobilenet_v2_1_0_160	.138
235	resnet_152_v1	.138
236	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.126
237	yudixie_resnet50_distance_rotation_0_240908	.126
238	yudixie_resnet18_imagenet1kpret_0_240719	.126
239	convnext_large_imagenet_full_seed-0	.126
240	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.114
241	mobilenet_v2_0_75_224	.114
242	yudixie_resnet18_distance_reg_0_240719	.104
243	efficientnet-b7	.104
244	efficientnet_b0	.086
245	resnet-152_v2_pytorch	.078
246	convnext_base_imagenet_full_seed-0	.078
247	resnet50_robust_l2_eps1	.073
248	regnet_y_400mf	.071
249	resnet50-SIN_IN	.071
250	resnet-50-robust	.064
251	imagenet_l2_3_0	.064
252	resnet50_robust_l2_eps3	.064
253	compact_cornets_V4	.053
254	mobilenet_v2_0_5_192	.048
255	mobilenet_v2_0_75_192	.048
256	resnet_50_v1_spiking	.044
257	AdvProp_efficientnet-b2	.033
258	AT_efficientnet-b2	.033
259	efficientnet_b2_imagenet_full	.020
260	SeLaVi-AVE
261	SeLaVi-Kinetics400
262	r3d_18
263	mc3_18
264	s3d
265	mvit_v2_s
266	mvit_v1_b
267	SeLaVi-Kinetics-Sound
268	SeLaVi-VGG-Sound
269	r2plus1d_18

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

0.86.

Note that scores are relative to this ceiling.

Data: Ferguson2024gray_hard

Metric: value_delta