Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("BMD2024.dotted_2Behavioral-accuracy_distance")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.991
2	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.765
3	vit_large_patch14_clip_224:openai_ft_in1k	.626
4	vit_large_patch14_clip_224:laion2b_ft_in1k	.615
5	vit_large_patch14_clip_336:laion2b_ft_in1k	.583
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.561
7	convnext_base:clip_laiona_augreg_ft_in1k_384	.465
8	resnext101_32x48d_wsl	.454
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.379
10	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.369
11	resnet50-SIN	.337
12	convnext_large:fb_in22k_ft_in1k	.337
13	resnext101_32x8d_wsl	.337
14	resnext101_32x16d_wsl	.315
15	convnext_xlarge:fb_in22k_ft_in1k	.294
16	resnext101_32x32d_wsl	.294
17	AdvProp_efficientnet-b7	.272
18	antialias-resnet152	.261
19	focalnet_tiny_lrf_in1k	.250
20	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.250
21	regnet_y_400mf	.250
22	mobilenet_v2_1_0_128	.250
23	ReAlnet10	.239
24	ReAlnet05	.239
25	resnet50-SIN_IN_IN	.239
26	ReAlnet02	.239
27	resnet_SIN_IN_FT_IN	.239
28	resnet34_imagenet_full	.239
29	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.227
30	convnext_small_imagenet_100_seed-0	.227
31	effnetb1_272x240	.227
32	ReAlnet06	.227
33	mobilenet_v2_1_0_224	.216
34	ReAlnet03	.216
35	ReAlnet_incorrect	.216
36	convnext_tiny_sup	.216
37	ReAlnet07	.216
38	BiT-S-R50x3	.216
39	ReAlnet08	.216
40	antialiased-r50	.216
41	resnet50_robust_l2_eps1	.216
42	ReAlnet09	.216
43	ReAlnet04	.216
44	grcnn_109	.216
45	ReAlnet01	.216
46	voneresnet-50	.216
47	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.216
48	convnext_large_imagenet_full_seed-0	.216
49	vit_relpos_base_patch16_clsgap_224:sw_in1k	.205
50	AdvProp_efficientnet-b2	.205
51	resnet50-SIN_IN	.205
52	cvt_cvt-13-224-in1k_4_LucyV4	.205
53	pnasnet_large	.205
54	BiT-S-R152x4	.205
55	AT_efficientnet-b2	.205
56	vgg_19	.205
57	convnext_base_imagenet_full_seed-0	.205
58	convnext_tiny_imagenet_full_seed-0	.194
59	AlexNet_SIN	.194
60	mobilenet_v2_1_0_192	.194
61	resnet50-moclr8deg	.182
62	resnet50_tutorial	.182
63	resnet50_imagenet_full	.182
64	convnext_small_imagenet_full_seed-0	.182
65	deit_small_imagenet_full_seed-0	.182
66	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.182
67	grcnn	.182
68	voneresnet-50-robust	.182
69	resnet_50_v1	.182
70	resnet50-sup	.182
71	resnet_101_v1	.182
72	densenet_201_pytorch	.171
73	BiT-S-R152x2	.171
74	densenet-201	.171
75	resnet152_imagenet_full	.171
76	nasnet_mobile	.171
77	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.171
78	AdvProp_efficientnet-b4	.171
79	shufflenet_v2_x1_0	.171
80	BiT-S-R101x1	.160
81	voneresnet-50-non_stochastic	.160
82	alexnet_ks_torevert	.160
83	BiT-S-R101x3	.160
84	blt_vs	.160
85	efficientnet_b1_imagenet_full	.160
86	resnet-50-robust	.149
87	pnasnet_large_pytorch	.149
88	resnet18_imagenet_full	.149
89	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.149
90	mobilenet_v2_0_75_160	.149
91	resnet50_robust_l2_eps3	.149
92	imagenet_l2_3_0	.149
93	AdvProp_efficientnet-b8	.149
94	efficientnet_b2_imagenet_full	.137
95	inception_v3_pytorch	.137
96	cvt_cvt-13-384-in1k_4_LucyV4	.137
97	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.137
98	vgg_16	.137
99	resnet_50_v2	.137
100	deit_base_imagenet_full_seed-0	.137
101	convnext_tiny:in12k_ft_in1k	.137
102	inception_v4	.137
103	inception_v1	.137
104	convnext_femto_ols:d1_in1k	.137
105	deit_large_imagenet_full_seed-0	.137
106	efficientnet_b0_imagenet_full	.137
107	bp_resnet50_julios	.126
108	resnet50_eMMCR_Vanilla	.126
109	mobilenet_v2_0_75_192	.126
110	resnet-152_v2_pytorch	.126
111	convnext_small_imagenet_10_seed-0	.126
112	custom_model_cv_18_dagger_408	.126
113	resnet50_imagenet_1_seed-0	.126
114	resnet50_imagenet_100_seed-0	.126
115	deit_small_imagenet_10_seed-0	.126
116	resnet_152_v1	.126
117	alexnet_training_seed_10	.126
118	alexnet_training_seed_07	.126
119	vit_base_patch16_clip_224:openai_ft_in1k	.126
120	cvt_cvt-21-384-in1k_4_LucyV4	.126
121	convnext_small_imagenet_1_seed-0	.126
122	mobilenet_v2_0_5_224	.126
123	efficientnet_b0	.126
124	Res2Net50_26w_4s	.126
125	resnet50-VITO-8deg-cc	.126
126	deit_small_imagenet_1_seed-0	.126
127	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.126
128	alexnet_training_seed_08	.126
129	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.126
130	resnet_101_v2	.126
131	alexnet_training_seed_04	.126
132	resnet50-vitoimagevidnet8	.126
133	vonegrcnn_62e_nobn	.126
134	resnet50_imagenet_10_seed-0	.126
135	artResNet18_1	.126
136	mobilenet_v2_0_5_192	.126
137	resnet_152_v2	.126
138	mobilenet_v2_1_0_160	.126
139	alexnet_training_seed_02	.126
140	cvt_cvt-21-224-in1k_4_LucyV4	.126
141	vonegrcnn_47e	.126
142	inception_v3	.126
143	vonegrcnn_52e_full	.126
144	alexnet_training_seed_06	.126
145	alexnet_training_seed_05	.126
146	alexnet_training_seed_09	.126
147	resnet50-vicregl0p75	.126
148	resnet50-vicregl0p9	.126
149	densenet-169	.126
150	densenet-121	.126
151	AdvProp_efficientnet-b6	.126
152	tv_efficientnet-b1	.126
153	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.115
154	ViT_L_32_imagenet1k	.115
155	BiT-S-R50x1	.115
156	resnet101_imagenet_full	.115
157	deit_small_imagenet_100_seed-0	.104
158	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.093
159	alexnet_training_seed_01	.093
160	nasnet_large	.093
161	mobilenet_v2_1_3_224	.093
162	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.081
163	alexnet_training_seed_03	.081
164	xception	.081
165	mobilenet_v2_1_4_224	.036
166	mobilenet_v2_1-4_224_pytorch	.036
167	resnet50-barlow	.036
168	mobilenet_v2_0_75_224	.014
169	omnivore_swinS	X
170	SimVP	X
171	PredRNN	X
172	resnet18_ecoset_full	X
173	yudixie_resnet50_category_class_0_240908	X
174	ReAlnet10_cornet	X
175	yudixie_resnet50_distance_translation_rotation_0_240908	X
176	ConvLSTM	X
177	yudixie_resnet50_cat_obj_class_all_latents_0_240908	X
178	antialiased-rnext101_32x8d	X
179	yudixie_resnet50_distance_rotation_0_240908	X
180	resnet152_ecoset_full	X
181	yudixie_resnet50_translation_reg_0_240908	X
182	yudixie_resnet18_distance_translation_0_240719	X
183	yudixie_resnet18_translation_rotation_0_240719	X
184	yudixie_resnet18_distance_rotation_0_240719	X
185	yudixie_resnet50_random_0_240908	X
186	yudixie_resnet50_distance_translation_0_240908	X
187	yudixie_resnet50_rotation_reg_0_240908	X
188	yudixie_resnet18_category_class_0_240719	X
189	resnet-18_test_m	X
190	ReAlnet05_cornet	X
191	yudixie_resnet18_random_0_240719	X
192	yudixie_resnet18_cat_obj_class_all_latents_0_240719	X
193	ReAlnet04_cornet	X
194	yudixie_resnet18_distance_translation_rotation_0_240719	X
195	yudixie_resnet50_object_class_0_240908	X
196	yudixie_resnet18_object_class_0_240719	X
197	yudixie_resnet18_rotation_reg_0_240719	X
198	yudixie_resnet18_imagenet1kpret_0_240719	X
199	yudixie_resnet18_translation_reg_0_240719	X
200	yudixie_resnet18_distance_reg_0_240719	X
201	efficientnet-b7	X
202	yudixie_resnet50_distance_reg_0_240908	X
203	ReAlnet02_cornet	X
204	ReAlnet06_cornet	X
205	resnet101_ecoset_full	X
206	ReAlnet01_cornet	X
207	yudixie_resnet50_translation_rotation_0_240908	X
208	ReAlnet07_cornet	X
209	ReAlnet03_cornet	X
210	resnet50-vicreg	X
211	ReAlnet08_cornet	X
212	VOneCORnet-S	X
213	resnet50_ecoset_full	X
214	omnivore_swinB	X
215	resnet34_ecoset_full	X
216	resnet18_imagenet21kP	X
217	hmax	X
218	MIM	X
219	TAU	X
220	ReAlnet09_cornet	X
221	yudixie_resnet50_imagenet1kpret_0_240908	X

Benchmark bibtex

None

Ceiling

0.93.

Note that scores are relative to this ceiling.

Data: BMD2024.dotted_2Behavioral

Metric: accuracy_distance