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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	compact_resnet50_robust_V4	1.0
2	ReAlnet10_cornet	1.0
3	ReAlnet10	1.0
4	omnivore_swinB	1.0
5	BiT-S-R101x1	1.0
6	artResNet18_1	1.0
7	deit_small_imagenet_100_seed-0	1.0
8	deit_large_imagenet_full_seed-0	1.0
9	resnet101_ecoset_full	1.0
10	pnasnet_large_pytorch	1.0
11	resnet18_fair	1.0
12	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
13	convnext_tiny:in12k_ft_in1k	1.0
14	convnext_femto_ols:d1_in1k	1.0
15	yudixie_resnet18_object_class_0_240719	1.0
16	resnext101_32x16d_wsl	1.0
17	ReAlnet01_ALL	1.0
18	vgg_16	1.0
19	inception_v4	1.0
20	deepeisnn_ei_cifar10_vgg19	.971
21	yudixie_wbh_object_class_scaling_0415_run_1	.971
22	yudixie_wbh_object_class_scaling_0415_run_3	.971
23	compact_resnet50_robust_IT	.971
24	ReAlnet02_ALL	.971
25	voneresnet-50-robust	.971
26	BiT-S-R152x2	.971
27	deit_small_imagenet_1_seed-0	.971
28	vit_huge_clip336_laion	.942
29	vit_large_clip336_openai	.942
30	dinov2_vitl14_reg_lc_featread	.942
31	dinov2_vitl14_lc_res336	.942
32	dinov2_vitl14_reg_lc	.942
33	eva02_large_in22k	.942
34	dinov2_vitg14_reg_lc	.942
35	dinov2_vitg14_lc	.942
36	yudixie_wbh_object_class_scaling_0415_run_2	.942
37	deit3_base_patch16_224_fb_in1k	.942
38	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.942
39	vit_base_patch16_dinov3-lvd1689m	.942
40	vit_base_patch14_reg4_dinov2-lvd142m	.942
41	vit_base_patch14_dinov2-lvd142m	.942
42	cv_18_dagger_408_pretrained	.942
43	resnet_50_v1_spiking_l4	.942
44	nasnet_mobile	.942
45	resnet50-vitoimagevidnet8	.942
46	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.942
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.942
48	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.942
49	vit_large_patch14_clip_224:openai_ft_in1k	.942
50	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.942
51	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.942
52	resnet50-VITO-8deg-cc	.942
53	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.942
54	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.942
55	vit_large_patch14_clip_224:laion2b_ft_in1k	.942
56	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.942
57	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.942
58	convnext_xxlarge_clip	.883
59	pnasnet_large_halfPrecision	.883
60	yudixie_resnet50_imagenet1kpret_0_240312	.883
61	yudixie_resnet50_imagenet1kpret_0_240908	.883
62	nasnet_large	.883
63	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.883
64	convnext_large:fb_in22k_ft_in1k	.883
65	deit_small_imagenet_10_seed-0	.883
66	compact_resnet50_IT	.855
67	alexnet_training_seed_06	.855
68	ReAlnet05_cornet	.855
69	ReAlnet05	.855
70	custom_model_cv_18_dagger_408	.855
71	alexnet_fov12	.802
72	resnet50-vicregl0p9	.802
73	resnet_SIN_IN_FT_IN	.802
74	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.777
75	deit3_base_patch16_224_fb_in22k_ft_in1k	.777
76	briaai_rmbg_1_4	.777
77	yudixie_resnet50_distance_translation_rotation_0_240908	.777
78	alexnet_training_seed_08	.777
79	ReAlnet07_cornet	.777
80	grcnn	.777
81	ReAlnet07	.777
82	resnet50_imagenet_full	.777
83	convnext_large_in22k_supervised	.728
84	ReAlnet07_ALL	.728
85	yudixie_resnet50_object_class_0_240908	.728
86	yudixie_resnet50_rotation_reg_0_240908	.728
87	convnext_xlarge:fb_in22k_ft_in1k	.728
88	resnet50-vicregl0p75	.728
89	yudixie_resnet18_distance_translation_rotation_0_240719	.728
90	cvt_cvt-21-224-in1k_4_LucyV4	.728
91	focalnet_tiny_lrf_in1k	.728
92	yudixie_wbh_object_class_scaling_0415_run_0	.706
93	predictive_coding_pc	.706
94	alexnet_ks_torevert	.706
95	ReAlnet01_cornet_fov4	.706
96	ReAlnet09_ALL	.706
97	mobilenet_v2_1_0_224	.706
98	resnet_152_v2	.706
99	resnet50-vicreg	.706
100	VOneCORnet-S	.706
101	cvt_cvt-13-224-in1k_4_LucyV4	.706
102	ViT_L_32_imagenet1k	.706
103	alexnet	.706
104	ReAlnet06_ALL	.662
105	ReAlnet04_ALL	.662
106	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.662
107	resnet50_tutorial	.662
108	fixres_resnext101_32x48d_wsl	.641
109	resnet18_imagenet21kP	.641
110	resnet50_st_wzc_2	.641
111	ReAlnet05_ALL	.641
112	yolos_tiny	.641
113	mobilenet_v2_1_3_224	.641
114	ReAlnet03_cornet	.641
115	inception_v1	.641
116	ReAlnet03	.641
117	Res2Net50_26w_4s	.641
118	resnet-18_test_m	.641
119	omnivore_swinS	.641
120	vit_base_patch16_clip_224:openai_ft_in1k	.641
121	resnet18_imagenet_full	.641
122	alexnet_training_seed_05	.601
123	yudixie_resnet18_distance_rotation_0_240719	.601
124	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.601
125	alexnet_training_seed_01_fov4	.583
126	resnet50_ewconplus_wzc	.583
127	mobilenet_v2_1_0_128	.583
128	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.583
129	AdvProp_efficientnet-b7	.583
130	yudixie_resnet18_random_0_240719	.583
131	resnet50_imagenet_1_seed-0	.583
132	cvt_cvt-13-384-in1k_4_LucyV4	.583
133	resnet18_ecoset_full	.583
134	AlexNet_SIN	.546
135	ReAlnet03_ALL	.546
136	pnasnet_large	.546
137	resnet_101_v2	.546
138	antialiased-rnext101_32x8d	.529
139	compact_vgg19_IT	.529
140	resnet_50_v1_spiking_l4a	.529
141	BiT-S-R101x3	.529
142	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.529
143	yudixie_resnet50_distance_reg_0_240908	.496
144	alexnet_training_seed_07	.496
145	compact_resnet50_V4	.481
146	ReAlnet09_cornet	.481
147	ReAlnet09	.481
148	vonegrcnn_47e	.481
149	blt_vs	.481
150	yudixie_resnet18_translation_reg_0_240719	.481
151	deit_base_imagenet_full_seed-0	.481
152	ReAlnet08_ALL	.451
153	alexnet_training_seed_01	.451
154	deepeisnn_ei_imagenet_resnet18	.437
155	yudixie_wbh_object_class_scaling_0415_imagenet	.437
156	AlexNet_SIN_fov4	.437
157	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.437
158	mobilenet_v2_1_4_224	.437
159	alexnet_training_seed_03	.437
160	ReAlnet01_cornet	.437
161	resnet_101_v1	.437
162	vgg_19	.437
163	ReAlnet01	.437
164	densenet-201	.437
165	convnext_base:clip_laiona_augreg_ft_in1k_384	.437
166	convnext_tiny_imagenet_full_seed-0	.437
167	mobilenet_v2_1-4_224_pytorch	.437
168	hmax	.437
169	resnext101_32x8d_wsl	.437
170	xception	.410
171	mobilenet_v2_1_0_192	.410
172	resnet50-SIN_IN_IN	.410
173	convnext_large_clip_laion2b_finelayers	.397
174	compact_vgg19_V4	.397
175	resnet50_primary_visual_cortex	.397
176	yudixie_resnet50_random_0_240908	.397
177	alexnet_training_seed_10	.397
178	alexnet_training_seed_04	.397
179	ReAlnet08_cornet	.397
180	ReAlnet04_cornet	.397
181	ReAlnet08	.397
182	ReAlnet04	.397
183	resnet50-moclr8deg	.397
184	resnet50-barlow	.397
185	resnet50-SIN	.397
186	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.397
187	convnext_small_imagenet_100_seed-0	.397
188	resnet50_imagenet_10_seed-0	.372
189	resnext101_32x32d_wsl	.372
190	densenet-169	.361
191	antialiased-r50	.361
192	AdvProp_efficientnet-b6	.361
193	deit_small_imagenet_full_seed-0	.361
194	compact_cornets_IT	.338
195	yudixie_resnet18_translation_rotation_0_240719	.338
196	convnext_base_fb_in1k_gram_aligned_dinov3	.328
197	convnext_base_fb_in22k_ft_in1k	.328
198	alexnet_training_seed_01_fov12	.328
199	vonegrcnn_62e_nobn	.328
200	efficientnet_b1_imagenet_full	.328
201	convnext_small_imagenet_1_seed-0	.307
202	alexnet_training_seed_01_fov16	.298
203	ReAlnet01_cornet_fov16	.298
204	yudixie_resnet50_distance_translation_0_240908	.298
205	resnet50_ecoset_full	.298
206	resnet34_ecoset_full	.298
207	resnext101_32x48d_wsl	.298
208	ReAlnet10_ALL	.279
209	convnext_small_imagenet_10_seed-0	.279
210	deepeisnn_ei_cifar10_resnet18	.270
211	aughost_fair_resnet18	.270
212	resnet50_eMMCR_Vanilla	.270
213	ReAlnet01_cornet_fov12	.270
214	alexnet_training_seed_02	.270
215	ReAlnet06_cornet	.270
216	mobilenet_v2_0_5_224	.270
217	mobilenet_v2_0_75_160	.270
218	yudixie_resnet50_translation_reg_0_240908	.270
219	ReAlnet06	.270
220	voneresnet-50	.270
221	convnext_tiny_sup	.270
222	resnet50_imagenet_100_seed-0	.270
223	resnet34_imagenet_full	.270
224	AlexNet_SIN_fov16	.253
225	yudixie_resnet18_rotation_reg_0_240719	.253
226	alexnet_fov16	.246
227	ReAlnet02_cornet	.246
228	ReAlnet02	.246
229	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.246
230	resnet152_ecoset_full	.246
231	voneresnet-50-non_stochastic	.246
232	yudixie_resnet50_category_class_0_240908	.230
233	resnet50_st_wzc_seed7_2_323	.223
234	resnet_50_v1_spiking_l3	.223
235	densenet-121	.223
236	BiT-S-R50x1	.223
237	AdvProp_efficientnet-b8	.223
238	convnext_small_imagenet_full_seed-0	.223
239	resnet101_imagenet_full	.223
240	resnet_50_v1	.203
241	AdvProp_efficientnet-b4	.203
242	resnet50-sup	.203
243	BiT-S-R152x4	.190
244	alexnet_fov4	.184
245	inception_v3	.184
246	yudixie_resnet18_category_class_0_240719	.184
247	efficientnet_b0_imagenet_full	.184
248	resnet152_imagenet_full	.184
249	antialias-resnet152	.173
250	AlexNet_SIN_fov12	.173
251	resnet50_hvs_wzc	.167
252	alexnet_training_seed_09	.167
253	grcnn_109	.167
254	yudixie_resnet50_translation_rotation_0_240908	.167
255	BiT-S-R50x3	.167
256	vonegrcnn_52e_full	.167
257	cvt_cvt-21-384-in1k_4_LucyV4	.157
258	resnet50_ewconplus_wzc_seed5_2__323	.152
259	tv_efficientnet-b1	.152
260	resnet_50_v2	.152
261	shufflenet_v2_x1_0	.152
262	yudixie_resnet18_distance_translation_0_240719	.152
263	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.152
264	effnetb1_272x240	.152
265	mobilenet_v2_1_0_160	.138
266	resnet_152_v1	.138
267	yudixie_resnet50_distance_rotation_0_240908	.126
268	convnext_large_imagenet_full_seed-0	.126
269	yudixie_resnet18_imagenet1kpret_0_240719	.126
270	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.126
271	mobilenet_v2_0_75_224	.114
272	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.114
273	efficientnet-b7	.104
274	yudixie_resnet18_distance_reg_0_240719	.104
275	pr1_stl10_disentangled_alpha04	.094
276	efficientnet_b0	.086
277	convnext_base_imagenet_full_seed-0	.078
278	resnet-152_v2_pytorch	.078
279	resnet50_robust_l2_eps1	.073
280	resnet50_ewconplus_wzc_seed2_2__323	.071
281	regnet_y_400mf	.071
282	resnet50-SIN_IN	.071
283	resnet50_robust_l2_eps3	.064
284	imagenet_l2_3_0	.064
285	resnet-50-robust	.064
286	compact_cornets_V4	.053
287	mobilenet_v2_0_75_192	.048
288	mobilenet_v2_0_5_192	.048
289	resnet_50_v1_spiking	.044
290	AT_efficientnet-b2	.033
291	AdvProp_efficientnet-b2	.033
292	efficientnet_b2_imagenet_full	.020
293	dinov2_vitl14_lc
294	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3
295	convnext_base_fb_in1k
296	r2plus1d_18
297	SeLaVi-VGG-Sound
298	SeLaVi-Kinetics-Sound
299	mvit_v1_b
300	mvit_v2_s
301	s3d
302	mc3_18
303	r3d_18
304	SeLaVi-Kinetics400
305	SeLaVi-AVE

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