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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024tilted_line-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_tiny_imagenet_full_seed-0	1.0
2	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
3	alexnet_training_seed_02	1.0
4	resnet50_ecoset_full	1.0
5	efficientnet_b1_imagenet_full	1.0
6	alexnet_training_seed_01	1.0
7	resnet-18_test_m	1.0
8	ReAlnet01_cornet_fov16	1.0
9	resnet50-vitoimagevidnet8	1.0
10	omnivore_swinS	1.0
11	resnet50-VITO-8deg-cc	1.0
12	compact_resnet50_robust_IT	1.0
13	yudixie_wbh_object_class_scaling_0415_imagenet	1.0
14	yudixie_wbh_object_class_scaling_0415_run_1	1.0
15	convnext_large_in22k_supervised	1.0
16	mobilenet_v2_0_75_224	1.0
17	resnet50_tutorial	1.0
18	ReAlnet08	1.0
19	resnet50_st_wzc_2	1.0
20	pnasnet_large_halfPrecision	1.0
21	resnet-50-robust	1.0
22	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
23	pnasnet_large	1.0
24	resnet_50_v1_spiking_l3	1.0
25	ReAlnet08_cornet	1.0
26	compact_cornets_V4	1.0
27	vonegrcnn_52e_full	1.0
28	yudixie_resnet50_random_0_240908	1.0
29	resnet_50_v1_spiking	.975
30	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.975
31	mobilenet_v2_0_5_224	.975
32	resnet152_ecoset_full	.975
33	resnet152_imagenet_full	.975
34	resnet_101_v2	.975
35	resnet_152_v1	.975
36	yudixie_wbh_object_class_scaling_0415_run_3	.975
37	alexnet_training_seed_05	.917
38	resnet50_imagenet_10_seed-0	.917
39	ReAlnet05	.917
40	alexnet_fov4	.917
41	convnext_small_imagenet_10_seed-0	.917
42	resnet50-SIN_IN_IN	.917
43	ReAlnet05_cornet	.917
44	yudixie_resnet18_category_class_0_240719	.917
45	compact_vgg19_IT	.917
46	ReAlnet06_ALL	.917
47	resnet50_ewconplus_wzc_seed5_2__323	.917
48	cvt_cvt-21-224-in1k_4_LucyV4	.883
49	mobilenet_v2_0_75_160	.883
50	compact_resnet50_V4	.883
51	alexnet_fov16	.883
52	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.883
53	AlexNet_SIN_fov4	.883
54	alexnet_training_seed_01_fov16	.883
55	yudixie_resnet50_object_class_0_240908	.883
56	resnet50-vicregl0p75	.883
57	densenet-169	.883
58	convnext_xxlarge_clip	.883
59	mobilenet_v2_1_0_128	.831
60	AlexNet_SIN	.831
61	briaai_rmbg_1_4	.831
62	alexnet_fov12	.831
63	cvt_cvt-13-224-in1k_4_LucyV4	.831
64	resnext101_32x32d_wsl	.831
65	mobilenet_v2_1-4_224_pytorch	.831
66	resnet50-barlow	.831
67	mobilenet_v2_1_4_224	.831
68	voneresnet-50-robust	.831
69	grcnn_109	.831
70	convnext_tiny_sup	.831
71	BiT-S-R101x3	.831
72	resnet50_hvs_wzc	.831
73	resnet50_ewconplus_wzc_seed6_2_323	.831
74	deepeisnn_ei_imagenet_resnet18	.831
75	deit_large_imagenet_full_seed-0	.800
76	convnext_xlarge:fb_in22k_ft_in1k	.800
77	mobilenet_v2_1_0_192	.800
78	resnet50_st_wzc_seed3_2_323	.800
79	ReAlnet01_cornet	.800
80	convnext_base_imagenet_full_seed-0	.800
81	yudixie_resnet18_distance_reg_0_240719	.800
82	vgg_16	.800
83	ReAlnet01	.800
84	resnet_SIN_IN_FT_IN	.800
85	convnext_large:fb_in22k_ft_in1k	.800
86	convnext_base_fb_in1k	.800
87	convnext_base_fb_in1k_gram_aligned_dinov3	.800
88	convnext_small_imagenet_100_seed-0	.753
89	ReAlnet10	.753
90	efficientnet_b0	.753
91	ReAlnet01_ALL	.753
92	vgg_19	.753
93	vonegrcnn_62e_nobn	.753
94	ReAlnet10_cornet	.753
95	BiT-S-R152x2	.753
96	deepeisnn_ei_cifar10_vgg19	.753
97	alexnet_training_seed_04	.725
98	convnext_large_clip_laion2b_finelayers	.725
99	deit_small_imagenet_full_seed-0	.682
100	inception_v3	.682
101	ReAlnet09	.682
102	convnext_small_imagenet_full_seed-0	.682
103	compact_resnet50_IT	.682
104	resnet101_ecoset_full	.682
105	yudixie_resnet50_translation_reg_0_240908	.682
106	omnivore_swinB	.682
107	ReAlnet09_cornet	.682
108	resnet_101_v1	.682
109	antialiased-r50	.682
110	ReAlnet08_ALL	.682
111	deit_base_imagenet_full_seed-0	.657
112	convnext_large_imagenet_full_seed-0	.657
113	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.657
114	cvt_cvt-21-384-in1k_4_LucyV4	.657
115	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.657
116	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.657
117	vit_large_patch14_clip_224:openai_ft_in1k	.657
118	vit_large_patch14_clip_336:laion2b_ft_in1k	.657
119	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.657
120	cv_18_dagger_408_pretrained	.657
121	vit_relpos_base_patch16_clsgap_224:sw_in1k	.657
122	resnet_50_v1_spiking_l4a	.657
123	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.657
124	mobilenet_v2_0_75_192	.657
125	vit_base_patch16_dinov3-lvd1689m	.657
126	AdvProp_efficientnet-b6	.657
127	custom_model_cv_18_dagger_408	.657
128	ViT_L_32_imagenet1k	.657
129	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.657
130	cvt_cvt-13-384-in1k_4_LucyV4	.657
131	vit_base_patch14_dinov2-lvd142m	.657
132	vit_base_patch16_clip_224:openai_ft_in1k	.657
133	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.657
134	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.657
135	resnet50-SIN_IN	.657
136	vit_base_patch14_reg4_dinov2-lvd142m	.657
137	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.657
138	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.657
139	yudixie_resnet18_distance_translation_rotation_0_240719	.657
140	efficientnet-b7	.657
141	AlexNet_SIN_fov12	.657
142	AdvProp_efficientnet-b7	.657
143	AdvProp_efficientnet-b4	.657
144	AdvProp_efficientnet-b2	.657
145	AdvProp_efficientnet-b8	.657
146	BiT-S-R152x4	.657
147	resnet50-vicregl0p9	.657
148	AT_efficientnet-b2	.657
149	convnext_base:clip_laiona_augreg_ft_in1k_384	.657
150	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.657
151	convnext_base_fb_in22k_ft_in1k	.657
152	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
153	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
154	deit3_base_patch16_224_fb_in1k	.657
155	dinov2_vitg14_lc	.657
156	eva02_large_in22k	.657
157	dinov2_vitg14_reg_lc	.657
158	dinov2_vitl14_reg_lc	.657
159	dinov2_vitl14_lc_res336	.657
160	vit_large_clip336_openai	.657
161	dinov2_vitl14_reg_lc_featread	.657
162	vit_huge_clip336_laion	.657
163	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.618
164	yolos_tiny	.618
165	deit_small_imagenet_100_seed-0	.618
166	ReAlnet04_cornet	.618
167	ReAlnet04_ALL	.618
168	BiT-S-R101x1	.618
169	ReAlnet04	.618
170	resnet50_st_wzc_seed6_2_323	.618
171	yudixie_resnet50_distance_reg_0_240908	.595
172	resnet50_imagenet_100_seed-0	.595
173	yudixie_resnet18_rotation_reg_0_240719	.595
174	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.595
175	resnet34_imagenet_full	.560
176	resnext101_32x48d_wsl	.560
177	ReAlnet02_ALL	.560
178	resnet50_ewconplus_wzc_seed2_2__323	.560
179	deit_small_imagenet_10_seed-0	.539
180	deit_small_imagenet_1_seed-0	.539
181	VOneCORnet-S	.539
182	compact_vgg19_V4	.539
183	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.539
184	mobilenet_v2_1_0_224	.539
185	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.507
186	resnet50_imagenet_1_seed-0	.507
187	ReAlnet03_ALL	.507
188	BiT-S-R50x3	.507
189	hmax	.507
190	ReAlnet06	.489
191	alexnet	.489
192	yudixie_resnet50_rotation_reg_0_240908	.489
193	ReAlnet06_cornet	.489
194	resnet_152_v2	.489
195	efficientnet_b2_imagenet_full	.460
196	resnext101_32x8d_wsl	.460
197	ReAlnet01_cornet_fov4	.460
198	artResNet18_1	.460
199	ReAlnet07_ALL	.460
200	yudixie_resnet50_distance_translation_rotation_0_240908	.460
201	deepeisnn_ei_cifar10_resnet18	.460
202	resnet50_ewconplus_wzc	.443
203	mobilenet_v2_0_5_192	.443
204	resnet101_imagenet_full	.443
205	voneresnet-50-non_stochastic	.443
206	yudixie_resnet50_distance_rotation_0_240908	.443
207	Res2Net50_26w_4s	.443
208	yudixie_resnet18_translation_reg_0_240719	.443
209	resnet50-vicreg	.443
210	resnet50-moclr8deg	.443
211	resnet18_fair	.443
212	yudixie_wbh_object_class_scaling_0415_run_2	.443
213	resnet50_imagenet_full	.417
214	nasnet_large	.417
215	BiT-S-R50x1	.417
216	convnext_tiny:in12k_ft_in1k	.401
217	ReAlnet03	.401
218	convnext_small_imagenet_1_seed-0	.401
219	ReAlnet03_cornet	.401
220	alexnet_training_seed_03	.401
221	alexnet_training_seed_08	.377
222	efficientnet_b0_imagenet_full	.377
223	resnet50_robust_l2_eps1	.377
224	yudixie_resnet50_distance_translation_0_240908	.377
225	ReAlnet05_ALL	.377
226	imagenet_l2_3_0	.377
227	resnet50_robust_l2_eps3	.377
228	densenet-121	.377
229	ReAlnet10_ALL	.377
230	yudixie_resnet50_category_class_0_240908	.363
231	ReAlnet02_cornet	.363
232	AlexNet_SIN_fov16	.363
233	yudixie_resnet50_imagenet1kpret_0_240908	.363
234	ReAlnet02	.363
235	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.342
236	compact_resnet50_robust_V4	.342
237	resnet_50_v1_spiking_l4	.329
238	yudixie_resnet18_random_0_240719	.329
239	resnet_50_v1	.329
240	resnet50-sup	.329
241	pr1_stl10_disentangled_alpha04	.329
242	predictive_coding_pc	.329
243	effnetb1_272x240	.310
244	resnet18_imagenet_full	.310
245	inception_v4	.310
246	resnet34_ecoset_full	.310
247	shufflenet_v2_x1_0	.310
248	mobilenet_v2_1_3_224	.310
249	compact_cornets_IT	.310
250	ReAlnet09_ALL	.310
251	densenet-201	.298
252	alexnet_training_seed_01_fov12	.298
253	resnet-152_v2_pytorch	.281
254	nasnet_mobile	.281
255	vonegrcnn_47e	.281
256	yudixie_resnet18_translation_rotation_0_240719	.270
257	alexnet_training_seed_01_fov4	.270
258	yudixie_wbh_object_class_scaling_0415_run_0	.270
259	mobilenet_v2_1_0_160	.254
260	alexnet_training_seed_10	.254
261	ReAlnet07	.245
262	blt_vs	.245
263	ReAlnet07_cornet	.245
264	resnet18_ecoset_full	.230
265	yudixie_resnet18_imagenet1kpret_0_240719	.230
266	yudixie_resnet18_distance_translation_0_240719	.222
267	resnet50-SIN	.222
268	ReAlnet01_cornet_fov12	.222
269	yudixie_resnet50_translation_rotation_0_240908	.222
270	voneresnet-50	.222
271	yudixie_resnet18_distance_rotation_0_240719	.209
272	aughost_fair_resnet18	.201
273	grcnn	.189
274	alexnet_training_seed_06	.182
275	pnasnet_large_pytorch	.171
276	alexnet_training_seed_09	.165
277	convnext_femto_ols:d1_in1k	.155
278	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.141
279	inception_v1	.141
280	alexnet_training_seed_07	.135
281	xception	.135
282	yudixie_resnet18_object_class_0_240719	.135
283	resnet_50_v2	.116
284	resnet50_primary_visual_cortex	.111
285	focalnet_tiny_lrf_in1k
286	dinov2_vitl14_lc

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

0.91.

Note that scores are relative to this ceiling.

Data: Ferguson2024tilted_line

Metric: value_delta