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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	gabor_filter_mean_abs_4x4_v2	1.0
2	convnext_large_in22k_supervised	1.0
3	yudixie_wbh_object_class_scaling_0415_run_1	1.0
4	yudixie_wbh_object_class_scaling_0415_imagenet	1.0
5	ReAlnet01_cornet_fov16	1.0
6	mehrer2020_alexnet_training_seed_01_fov4	1.0
7	compact_resnet50_robust_IT	1.0
8	alexnet_training_seed_01	1.0
9	alexnet_training_seed_02	1.0
10	resnet50-vitoimagevidnet8	1.0
11	resnet-18_test_m	1.0
12	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
13	resnet50-VITO-8deg-cc	1.0
14	omnivore_swinS	1.0
15	convnext_tiny_imagenet_full_seed-0	1.0
16	efficientnet_b1_imagenet_full	1.0
17	resnet50_ecoset_full	1.0
18	focalnet_tiny_lrf_in1k	1.0
19	pnasnet_large_halfPrecision	1.0
20	resnet50_st_wzc_2	1.0
21	compact_cornets_V4	1.0
22	resnet_50_v1_spiking_l3	1.0
23	yudixie_resnet50_random_0_240908	1.0
24	pnasnet_large	1.0
25	ReAlnet08_cornet	1.0
26	mobilenet_v2_0_75_224	1.0
27	ReAlnet08	1.0
28	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
29	vonegrcnn_52e_full	1.0
30	resnet50_tutorial	1.0
31	resnet-50-robust	1.0
32	yudixie_wbh_object_class_scaling_0415_run_3	.975
33	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.975
34	mehrer2020_alexnet_training_seed_05	.975
35	resnet_50_v1_spiking	.975
36	resnet_152_v1	.975
37	resnet_101_v2	.975
38	mobilenet_v2_0_5_224	.975
39	resnet152_ecoset_full	.975
40	resnet152_imagenet_full	.975
41	resnet50_ewconplus_wzc_seed5_2__323	.917
42	alexnet_fov4	.917
43	resnet50_simclr_linhead_01norm	.917
44	compact_vgg19_IT	.917
45	ReAlnet06_ALL	.917
46	alexnet_training_seed_05	.917
47	ReAlnet05_cornet	.917
48	ReAlnet05	.917
49	resnet50-SIN_IN_IN	.917
50	convnext_small_imagenet_10_seed-0	.917
51	yudixie_resnet18_category_class_0_240719	.917
52	resnet50_imagenet_10_seed-0	.917
53	mehrer2020_alexnet_training_seed_02	.883
54	mehrer2020_alexnet_training_seed_01	.883
55	convnext_xxlarge_clip	.883
56	alexnet_training_seed_01_fov16	.883
57	AlexNet_SIN_fov4	.883
58	alexnet_fov16	.883
59	compact_resnet50_V4	.883
60	yudixie_resnet50_object_class_0_240908	.883
61	mobilenet_v2_0_75_160	.883
62	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.883
63	densenet-169	.883
64	resnet50-vicregl0p75	.883
65	cvt_cvt-21-224-in1k_4_LucyV4	.883
66	deepeisnn_ei_imagenet_resnet18	.831
67	resnet50_ewconplus_wzc_seed6_2_323	.831
68	alexnet_fov12	.831
69	AlexNet_SIN	.831
70	resnet50_hvs_wzc	.831
71	mehrer2020_alexnet_training_seed_08	.831
72	briaai_rmbg_1_4	.831
73	mobilenet_v2_1_4_224	.831
74	mobilenet_v2_1_0_128	.831
75	grcnn_109	.831
76	voneresnet-50-robust	.831
77	resnet50-barlow	.831
78	BiT-S-R101x3	.831
79	convnext_tiny_sup	.831
80	cvt_cvt-13-224-in1k_4_LucyV4	.831
81	mobilenet_v2_1-4_224_pytorch	.831
82	resnext101_32x32d_wsl	.831
83	convnext_base_fb_in1k_gram_aligned_dinov3	.800
84	convnext_base_fb_in1k	.800
85	resnet50_st_wzc_seed3_2_323	.800
86	resnet50_vicreg_linhead	.800
87	ijepa_vith14_linhead	.800
88	ReAlnet01_cornet	.800
89	mobilenet_v2_1_0_192	.800
90	vgg_16	.800
91	ReAlnet01	.800
92	convnext_xlarge:fb_in22k_ft_in1k	.800
93	convnext_large:fb_in22k_ft_in1k	.800
94	resnet_SIN_IN_FT_IN	.800
95	convnext_base_imagenet_full_seed-0	.800
96	yudixie_resnet18_distance_reg_0_240719	.800
97	deit_large_imagenet_full_seed-0	.800
98	gabor_filter_entropy_4x4_v2_forcedCosine	.753
99	deepeisnn_ei_cifar10_vgg19	.753
100	resnet50_barlowtwins_linhead	.753
101	ReAlnet01_ALL	.753
102	ReAlnet10_cornet	.753
103	vgg_19	.753
104	vonegrcnn_62e_nobn	.753
105	ReAlnet10	.753
106	efficientnet_b0	.753
107	BiT-S-R152x2	.753
108	convnext_small_imagenet_100_seed-0	.753
109	convnext_large_clip_laion2b_finelayers	.725
110	alexnet_training_seed_04	.725
111	resnet50_simsiam_linhead	.682
112	compact_resnet50_IT	.682
113	ReAlnet08_ALL	.682
114	ReAlnet09_cornet	.682
115	resnet_101_v1	.682
116	inception_v3	.682
117	yudixie_resnet50_translation_reg_0_240908	.682
118	ReAlnet09	.682
119	omnivore_swinB	.682
120	antialiased-r50	.682
121	convnext_small_imagenet_full_seed-0	.682
122	deit_small_imagenet_full_seed-0	.682
123	resnet101_ecoset_full	.682
124	resnext101_32x16d_wsl	.657
125	seresnext50_32x4d	.657
126	regnety_032	.657
127	vit_huge_clip336_laion	.657
128	vit_large_clip336_openai	.657
129	dinov2_vitl14_reg_lc_featread	.657
130	dinov2_vitl14_lc_res336	.657
131	dinov2_vitl14_reg_lc	.657
132	eva02_large_in22k	.657
133	dinov2_vitg14_reg_lc	.657
134	dinov2_vitg14_lc	.657
135	dinov2_vitl14_lc	.657
136	deit3_base_patch16_224_fb_in1k	.657
137	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
138	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
139	convnext_base_fb_in22k_ft_in1k	.657
140	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.657
141	vit_base_patch16_dinov3-lvd1689m	.657
142	vit_base_patch14_reg4_dinov2-lvd142m	.657
143	vit_base_patch14_dinov2-lvd142m	.657
144	AlexNet_SIN_fov12	.657
145	cv_18_dagger_408_pretrained	.657
146	mehrer2020_alexnet_training_seed_07	.657
147	resnet_50_v1_spiking_l4a	.657
148	mobilenet_v2_0_75_192	.657
149	efficientnet-b7	.657
150	resnet50-SIN_IN	.657
151	vit_relpos_base_patch16_clsgap_224:sw_in1k	.657
152	vit_large_patch14_clip_336:laion2b_ft_in1k	.657
153	vit_large_patch14_clip_224:openai_ft_in1k	.657
154	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.657
155	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.657
156	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.657
157	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.657
158	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.657
159	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.657
160	vit_base_patch16_clip_224:openai_ft_in1k	.657
161	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.657
162	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.657
163	convnext_base:clip_laiona_augreg_ft_in1k_384	.657
164	AT_efficientnet-b2	.657
165	resnet50-vicregl0p9	.657
166	BiT-S-R152x4	.657
167	AdvProp_efficientnet-b8	.657
168	AdvProp_efficientnet-b2	.657
169	AdvProp_efficientnet-b4	.657
170	AdvProp_efficientnet-b7	.657
171	AdvProp_efficientnet-b6	.657
172	convnext_large_imagenet_full_seed-0	.657
173	yudixie_resnet18_distance_translation_rotation_0_240719	.657
174	deit_base_imagenet_full_seed-0	.657
175	cvt_cvt-21-384-in1k_4_LucyV4	.657
176	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.657
177	cvt_cvt-13-384-in1k_4_LucyV4	.657
178	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.657
179	ViT_L_32_imagenet1k	.657
180	custom_model_cv_18_dagger_408	.657
181	resnet50_st_wzc_seed6_2_323	.618
182	ReAlnet04_ALL	.618
183	yolos_tiny	.618
184	ReAlnet04_cornet	.618
185	ReAlnet04	.618
186	BiT-S-R101x1	.618
187	deit_small_imagenet_100_seed-0	.618
188	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.618
189	yudixie_resnet50_distance_reg_0_240908	.595
190	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.595
191	yudixie_resnet18_rotation_reg_0_240719	.595
192	resnet50_imagenet_100_seed-0	.595
193	resnet50_ewconplus_wzc_seed2_2__323	.560
194	mehrer2020_alexnet_training_seed_10	.560
195	ReAlnet02_ALL	.560
196	resnet34_imagenet_full	.560
197	resnext101_32x48d_wsl	.560
198	mehrer2020_alexnet_training_seed_04	.539
199	mehrer2020_alexnet_training_seed_03	.539
200	compact_vgg19_V4	.539
201	mobilenet_v2_1_0_224	.539
202	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.539
203	VOneCORnet-S	.539
204	deit_small_imagenet_1_seed-0	.539
205	deit_small_imagenet_10_seed-0	.539
206	ReAlnet03_ALL	.507
207	BiT-S-R50x3	.507
208	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.507
209	resnet50_imagenet_1_seed-0	.507
210	hmax	.507
211	ReAlnet06_cornet	.489
212	resnet_152_v2	.489
213	yudixie_resnet50_rotation_reg_0_240908	.489
214	ReAlnet06	.489
215	alexnet	.489
216	gabor_filter_entropy_4x4_v2	.460
217	deepeisnn_ei_cifar10_resnet18	.460
218	ReAlnet01_cornet_fov4	.460
219	ReAlnet07_ALL	.460
220	yudixie_resnet50_distance_translation_rotation_0_240908	.460
221	artResNet18_1	.460
222	efficientnet_b2_imagenet_full	.460
223	resnext101_32x8d_wsl	.460
224	yudixie_wbh_object_class_scaling_0415_run_2	.443
225	resnet18_fair	.443
226	resnet50_ewconplus_wzc	.443
227	resnet50_byol_linhead	.443
228	mobilenet_v2_0_5_192	.443
229	yudixie_resnet50_distance_rotation_0_240908	.443
230	resnet50-moclr8deg	.443
231	resnet50-vicreg	.443
232	Res2Net50_26w_4s	.443
233	yudixie_resnet18_translation_reg_0_240719	.443
234	resnet101_imagenet_full	.443
235	voneresnet-50-non_stochastic	.443
236	nasnet_large	.417
237	BiT-S-R50x1	.417
238	resnet50_imagenet_full	.417
239	alexnet_training_seed_03	.401
240	ReAlnet03_cornet	.401
241	ReAlnet03	.401
242	convnext_tiny:in12k_ft_in1k	.401
243	convnext_small_imagenet_1_seed-0	.401
244	mehrer2020_alexnet_training_seed_01_fov16	.377
245	ReAlnet10_ALL	.377
246	ReAlnet05_ALL	.377
247	alexnet_training_seed_08	.377
248	yudixie_resnet50_distance_translation_0_240908	.377
249	resnet50_robust_l2_eps1	.377
250	densenet-121	.377
251	resnet50_robust_l2_eps3	.377
252	imagenet_l2_3_0	.377
253	efficientnet_b0_imagenet_full	.377
254	AlexNet_SIN_fov16	.363
255	mehrer2020_alexnet_training_seed_06	.363
256	yudixie_resnet50_category_class_0_240908	.363
257	yudixie_resnet50_imagenet1kpret_0_240908	.363
258	ReAlnet02_cornet	.363
259	ReAlnet02	.363
260	compact_resnet50_robust_V4	.342
261	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.342
262	predictive_coding_pc	.329
263	pr1_stl10_disentangled_alpha04	.329
264	mehrer2020_alexnet_training_seed_09	.329
265	resnet_50_v1_spiking_l4	.329
266	resnet_50_v1	.329
267	resnet50-sup	.329
268	yudixie_resnet18_random_0_240719	.329
269	mehrer2020_alexnet_training_seed_01_fov12	.310
270	compact_cornets_IT	.310
271	ReAlnet09_ALL	.310
272	mobilenet_v2_1_3_224	.310
273	inception_v4	.310
274	shufflenet_v2_x1_0	.310
275	resnet34_ecoset_full	.310
276	resnet18_imagenet_full	.310
277	effnetb1_272x240	.310
278	alexnet_training_seed_01_fov12	.298
279	densenet-201	.298
280	nasnet_mobile	.281
281	vonegrcnn_47e	.281
282	resnet-152_v2_pytorch	.281
283	gabor_filter_entropy_4x4	.270
284	yudixie_wbh_object_class_scaling_0415_run_0	.270
285	alexnet_training_seed_01_fov4	.270
286	yudixie_resnet18_translation_rotation_0_240719	.270
287	alexnet_training_seed_10	.254
288	mobilenet_v2_1_0_160	.254
289	ReAlnet07_cornet	.245
290	ReAlnet07	.245
291	blt_vs	.245
292	yudixie_resnet18_imagenet1kpret_0_240719	.230
293	resnet18_ecoset_full	.230
294	ReAlnet01_cornet_fov12	.222
295	yudixie_resnet50_translation_rotation_0_240908	.222
296	voneresnet-50	.222
297	resnet50-SIN	.222
298	yudixie_resnet18_distance_translation_0_240719	.222
299	yudixie_resnet18_distance_rotation_0_240719	.209
300	grcnn	.189
301	alexnet_training_seed_06	.182
302	pnasnet_large_pytorch	.171
303	alexnet_training_seed_09	.165
304	convnext_femto_ols:d1_in1k	.155
305	inception_v1	.141
306	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.141
307	xception	.135
308	alexnet_training_seed_07	.135
309	yudixie_resnet18_object_class_0_240719	.135
310	resnet_50_v2	.116
311	resnet50_primary_visual_cortex	.111
312	eicircuit_resnet18_bn_20260919	.058

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