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("Ferguson2024tilted_line-value_delta")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	yudixie_wbh_object_class_scaling_0415_run_1	1.0
2	yudixie_wbh_object_class_scaling_0415_imagenet	1.0
3	resnet50_st_wzc_noseed_2_323	1.0
4	resnet50_ewconplus_noseed_2_323	1.0
5	ReAlnet01_cornet_fov16	1.0
6	compact_resnet50_robust_IT	1.0
7	alexnet_training_seed_01	1.0
8	alexnet_training_seed_02	1.0
9	resnet50-vitoimagevidnet8	1.0
10	resnet-18_test_m	1.0
11	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
12	resnet50-VITO-8deg-cc	1.0
13	omnivore_swinS	1.0
14	convnext_tiny_imagenet_full_seed-0	1.0
15	efficientnet_b1_imagenet_full	1.0
16	resnet50_ecoset_full	1.0
17	pnasnet_large_halfPrecision	1.0
18	resnet50_st_wzc_2	1.0
19	compact_cornets_V4	1.0
20	resnet_50_v1_spiking_l3	1.0
21	yudixie_resnet50_random_0_240908	1.0
22	pnasnet_large	1.0
23	ReAlnet08_cornet	1.0
24	mobilenet_v2_0_75_224	1.0
25	ReAlnet08	1.0
26	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
27	vonegrcnn_52e_full	1.0
28	resnet50_tutorial	1.0
29	resnet-50-robust	1.0
30	yudixie_wbh_object_class_scaling_0415_run_3	.975
31	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.975
32	resnet_50_v1_spiking	.975
33	resnet_152_v1	.975
34	resnet_101_v2	.975
35	mobilenet_v2_0_5_224	.975
36	resnet152_ecoset_full	.975
37	resnet152_imagenet_full	.975
38	resnet50_ewconplus_wzc_seed5_2__323	.917
39	alexnet_fov4	.917
40	compact_vgg19_IT	.917
41	ReAlnet06_ALL	.917
42	alexnet_training_seed_05	.917
43	ReAlnet05_cornet	.917
44	ReAlnet05	.917
45	resnet50-SIN_IN_IN	.917
46	convnext_small_imagenet_10_seed-0	.917
47	yudixie_resnet18_category_class_0_240719	.917
48	resnet50_imagenet_10_seed-0	.917
49	alexnet_training_seed_01_fov16	.883
50	AlexNet_SIN_fov4	.883
51	alexnet_fov16	.883
52	compact_resnet50_V4	.883
53	yudixie_resnet50_object_class_0_240908	.883
54	mobilenet_v2_0_75_160	.883
55	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.883
56	densenet-169	.883
57	resnet50-vicregl0p75	.883
58	cvt_cvt-21-224-in1k_4_LucyV4	.883
59	deepeisnn_ei_imagenet_resnet18	.831
60	resnet50_ewconplus_wzc_seed6_2_323	.831
61	alexnet_fov12	.831
62	AlexNet_SIN	.831
63	briaai_rmbg_1_4	.831
64	mobilenet_v2_1_4_224	.831
65	mobilenet_v2_1_0_128	.831
66	grcnn_109	.831
67	voneresnet-50-robust	.831
68	resnet50-barlow	.831
69	BiT-S-R101x3	.831
70	convnext_tiny_sup	.831
71	cvt_cvt-13-224-in1k_4_LucyV4	.831
72	mobilenet_v2_1-4_224_pytorch	.831
73	resnext101_32x32d_wsl	.831
74	convnext_base_fb_in1k_gram_aligned_dinov3	.800
75	convnext_base_fb_in1k	.800
76	resnet50_st_wzc_seed3_2_323	.800
77	ReAlnet01_cornet	.800
78	mobilenet_v2_1_0_192	.800
79	vgg_16	.800
80	ReAlnet01	.800
81	convnext_xlarge:fb_in22k_ft_in1k	.800
82	convnext_large:fb_in22k_ft_in1k	.800
83	resnet_SIN_IN_FT_IN	.800
84	convnext_base_imagenet_full_seed-0	.800
85	yudixie_resnet18_distance_reg_0_240719	.800
86	deit_large_imagenet_full_seed-0	.800
87	deepeisnn_ei_cifar10_vgg19	.753
88	ReAlnet01_ALL	.753
89	ReAlnet10_cornet	.753
90	vgg_19	.753
91	vonegrcnn_62e_nobn	.753
92	ReAlnet10	.753
93	efficientnet_b0	.753
94	BiT-S-R152x2	.753
95	convnext_small_imagenet_100_seed-0	.753
96	alexnet_training_seed_04	.725
97	compact_resnet50_IT	.682
98	ReAlnet08_ALL	.682
99	ReAlnet09_cornet	.682
100	resnet_101_v1	.682
101	inception_v3	.682
102	yudixie_resnet50_translation_reg_0_240908	.682
103	ReAlnet09	.682
104	omnivore_swinB	.682
105	antialiased-r50	.682
106	convnext_small_imagenet_full_seed-0	.682
107	deit_small_imagenet_full_seed-0	.682
108	resnet101_ecoset_full	.682
109	deit3_base_patch16_224_fb_in1k	.657
110	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
111	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.657
112	convnext_base_fb_in22k_ft_in1k	.657
113	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.657
114	vit_base_patch16_dinov3-lvd1689m	.657
115	vit_base_patch14_reg4_dinov2-lvd142m	.657
116	vit_base_patch14_dinov2-lvd142m	.657
117	AlexNet_SIN_fov12	.657
118	cv_18_dagger_408_pretrained	.657
119	resnet_50_v1_spiking_l4a	.657
120	mobilenet_v2_0_75_192	.657
121	efficientnet-b7	.657
122	resnet50-SIN_IN	.657
123	vit_relpos_base_patch16_clsgap_224:sw_in1k	.657
124	vit_large_patch14_clip_336:laion2b_ft_in1k	.657
125	vit_large_patch14_clip_224:openai_ft_in1k	.657
126	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.657
127	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.657
128	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.657
129	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.657
130	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.657
131	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.657
132	vit_base_patch16_clip_224:openai_ft_in1k	.657
133	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.657
134	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.657
135	convnext_base:clip_laiona_augreg_ft_in1k_384	.657
136	AT_efficientnet-b2	.657
137	resnet50-vicregl0p9	.657
138	BiT-S-R152x4	.657
139	AdvProp_efficientnet-b8	.657
140	AdvProp_efficientnet-b2	.657
141	AdvProp_efficientnet-b4	.657
142	AdvProp_efficientnet-b7	.657
143	AdvProp_efficientnet-b6	.657
144	convnext_large_imagenet_full_seed-0	.657
145	yudixie_resnet18_distance_translation_rotation_0_240719	.657
146	deit_base_imagenet_full_seed-0	.657
147	cvt_cvt-21-384-in1k_4_LucyV4	.657
148	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.657
149	cvt_cvt-13-384-in1k_4_LucyV4	.657
150	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.657
151	ViT_L_32_imagenet1k	.657
152	custom_model_cv_18_dagger_408	.657
153	resnet50_st_wzc_seed6_2_323	.618
154	ReAlnet04_ALL	.618
155	yolos_tiny	.618
156	ReAlnet04_cornet	.618
157	ReAlnet04	.618
158	BiT-S-R101x1	.618
159	deit_small_imagenet_100_seed-0	.618
160	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.618
161	yudixie_resnet50_distance_reg_0_240908	.595
162	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.595
163	yudixie_resnet18_rotation_reg_0_240719	.595
164	resnet50_imagenet_100_seed-0	.595
165	resnet50_ewconplus_wzc_seed2_2__323	.560
166	ReAlnet02_ALL	.560
167	resnet34_imagenet_full	.560
168	resnext101_32x48d_wsl	.560
169	compact_vgg19_V4	.539
170	mobilenet_v2_1_0_224	.539
171	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.539
172	VOneCORnet-S	.539
173	deit_small_imagenet_1_seed-0	.539
174	deit_small_imagenet_10_seed-0	.539
175	resnet50_st_wzc_seed5_2_323	.507
176	ReAlnet03_ALL	.507
177	BiT-S-R50x3	.507
178	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.507
179	resnet50_imagenet_1_seed-0	.507
180	hmax	.507
181	ReAlnet06_cornet	.489
182	resnet_152_v2	.489
183	yudixie_resnet50_rotation_reg_0_240908	.489
184	ReAlnet06	.489
185	alexnet	.489
186	deepeisnn_ei_cifar10_resnet18	.460
187	ReAlnet01_cornet_fov4	.460
188	ReAlnet07_ALL	.460
189	yudixie_resnet50_distance_translation_rotation_0_240908	.460
190	artResNet18_1	.460
191	efficientnet_b2_imagenet_full	.460
192	resnext101_32x8d_wsl	.460
193	yudixie_wbh_object_class_scaling_0415_run_2	.443
194	resnet18_fair	.443
195	resnet50_ewconplus_wzc	.443
196	mobilenet_v2_0_5_192	.443
197	yudixie_resnet50_distance_rotation_0_240908	.443
198	resnet50-moclr8deg	.443
199	resnet50-vicreg	.443
200	Res2Net50_26w_4s	.443
201	yudixie_resnet18_translation_reg_0_240719	.443
202	resnet101_imagenet_full	.443
203	voneresnet-50-non_stochastic	.443
204	nasnet_large	.417
205	BiT-S-R50x1	.417
206	resnet50_imagenet_full	.417
207	alexnet_training_seed_03	.401
208	ReAlnet03_cornet	.401
209	ReAlnet03	.401
210	convnext_tiny:in12k_ft_in1k	.401
211	convnext_small_imagenet_1_seed-0	.401
212	resnet50_ewconplus_wzc_2_323	.377
213	ReAlnet10_ALL	.377
214	ReAlnet05_ALL	.377
215	alexnet_training_seed_08	.377
216	yudixie_resnet50_distance_translation_0_240908	.377
217	resnet50_robust_l2_eps1	.377
218	densenet-121	.377
219	resnet50_robust_l2_eps3	.377
220	imagenet_l2_3_0	.377
221	efficientnet_b0_imagenet_full	.377
222	AlexNet_SIN_fov16	.363
223	yudixie_resnet50_category_class_0_240908	.363
224	yudixie_resnet50_imagenet1kpret_0_240908	.363
225	ReAlnet02_cornet	.363
226	ReAlnet02	.363
227	compact_resnet50_robust_V4	.342
228	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.342
229	predictive_coding_pc	.329
230	pr1_stl10_disentangled_alpha04	.329
231	resnet50_st_wzc_2_323	.329
232	resnet_50_v1_spiking_l4	.329
233	resnet_50_v1	.329
234	resnet50-sup	.329
235	yudixie_resnet18_random_0_240719	.329
236	compact_cornets_IT	.310
237	ReAlnet09_ALL	.310
238	mobilenet_v2_1_3_224	.310
239	inception_v4	.310
240	shufflenet_v2_x1_0	.310
241	resnet34_ecoset_full	.310
242	resnet18_imagenet_full	.310
243	effnetb1_272x240	.310
244	alexnet_training_seed_01_fov12	.298
245	densenet-201	.298
246	resnet50_st_wzc_seed4_2_323	.281
247	resnet50_ewconplus_wzc_seed4_2_323	.281
248	resnet50_ewconplus_wzc_seed3_2_323	.281
249	nasnet_mobile	.281
250	vonegrcnn_47e	.281
251	resnet-152_v2_pytorch	.281
252	yudixie_wbh_object_class_scaling_0415_run_0	.270
253	alexnet_training_seed_01_fov4	.270
254	yudixie_resnet18_translation_rotation_0_240719	.270
255	alexnet_training_seed_10	.254
256	mobilenet_v2_1_0_160	.254
257	ReAlnet07_cornet	.245
258	ReAlnet07	.245
259	blt_vs	.245
260	yudixie_resnet18_imagenet1kpret_0_240719	.230
261	resnet18_ecoset_full	.230
262	ReAlnet01_cornet_fov12	.222
263	yudixie_resnet50_translation_rotation_0_240908	.222
264	voneresnet-50	.222
265	resnet50-SIN	.222
266	yudixie_resnet18_distance_translation_0_240719	.222
267	yudixie_resnet18_distance_rotation_0_240719	.209
268	aughost_fair_resnet18	.201
269	grcnn	.189
270	alexnet_training_seed_06	.182
271	pnasnet_large_pytorch	.171
272	alexnet_training_seed_09	.165
273	convnext_femto_ols:d1_in1k	.155
274	resnet50_ewconplus_wzc_seed7_2_323	.141
275	inception_v1	.141
276	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.141
277	xception	.135
278	alexnet_training_seed_07	.135
279	yudixie_resnet18_object_class_0_240719	.135
280	resnet_50_v2	.116
281	resnet50_primary_visual_cortex	.111
282	focalnet_tiny_lrf_in1k

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