Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("BMD2024.texture_1Behavioral-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	.998
2	vit_large_patch14_clip_224:laion2b_ft_in1k	.991
3	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.951
4	vit_large_patch14_clip_336:laion2b_ft_in1k	.941
5	vit_large_patch14_clip_224:openai_ft_in1k	.941
6	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.930
7	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.858
8	resnext101_32x48d_wsl	.817
9	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.775
10	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.765
11	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.713
12	convnext_base:clip_laiona_augreg_ft_in1k_384	.600
13	resnext101_32x8d_wsl	.579
14	resnext101_32x16d_wsl	.558
15	AdvProp_efficientnet-b8	.455
16	AdvProp_efficientnet-b7	.445
17	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.434
18	convnext_xlarge:fb_in22k_ft_in1k	.424
19	convnext_large:fb_in22k_ft_in1k	.413
20	vit_base_patch16_clip_224:openai_ft_in1k	.382
21	mobilenet_v2_1_0_160	.372
22	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.362
23	AdvProp_efficientnet-b6	.351
24	blt_vs	.341
25	densenet_201_pytorch	.331
26	densenet-201	.331
27	resnet50_robust_l2_eps1	.320
28	mobilenet_v2_0_5_192	.310
29	convnext_small_imagenet_full_seed-0	.310
30	mobilenet_v2_0_75_192	.310
31	grcnn_109	.300
32	AT_efficientnet-b2	.289
33	AdvProp_efficientnet-b2	.289
34	AdvProp_efficientnet-b4	.289
35	regnet_y_400mf	.279
36	mobilenet_v2_1_0_128	.279
37	shufflenet_v2_x1_0	.279
38	mobilenet_v2_1_0_224	.279
39	resnet_101_v2	.269
40	imagenet_l2_3_0	.269
41	nasnet_large	.269
42	convnext_tiny:in12k_ft_in1k	.269
43	resnet-50-robust	.269
44	resnet50_robust_l2_eps3	.269
45	convnext_tiny_imagenet_full_seed-0	.258
46	convnext_base_imagenet_full_seed-0	.258
47	inception_v3_pytorch	.258
48	cvt_cvt-21-224-in1k_4_LucyV4	.248
49	mobilenet_v2_0_75_160	.248
50	cvt_cvt-13-224-in1k_4_LucyV4	.248
51	deit_base_imagenet_full_seed-0	.248
52	antialias-resnet152	.248
53	effnetb1_272x240	.238
54	resnet18_imagenet_full	.238
55	cvt_cvt-21-384-in1k_4_LucyV4	.238
56	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.238
57	resnext101_32x32d_wsl	.238
58	mobilenet_v2_1_0_192	.238
59	grcnn	.238
60	Res2Net50_26w_4s	.238
61	inception_v4	.238
62	resnet50_imagenet_100_seed-0	.227
63	mobilenet_v2_0_5_224	.227
64	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.227
65	antialiased-r50	.227
66	resnet152_imagenet_full	.227
67	efficientnet_b0_imagenet_full	.227
68	ReAlnet04	.217
69	mobilenet_v2_0_75_224	.217
70	resnet_101_v1	.217
71	mobilenet_v2_1_4_224	.217
72	inception_v3	.217
73	resnet50-VITO-8deg-cc	.217
74	voneresnet-50	.217
75	resnet50-vitoimagevidnet8	.217
76	mobilenet_v2_1-4_224_pytorch	.217
77	deit_large_imagenet_full_seed-0	.207
78	AlexNet_SIN	.207
79	BiT-S-R50x1	.207
80	ReAlnet09	.207
81	tv_efficientnet-b1	.207
82	resnet34_imagenet_full	.207
83	vonegrcnn_62e_nobn	.207
84	BiT-S-R101x3	.207
85	ReAlnet07	.196
86	nasnet_mobile	.196
87	ReAlnet08	.196
88	ReAlnet10	.196
89	resnet_50_v2	.196
90	ReAlnet02	.196
91	vonegrcnn_47e	.196
92	vit_relpos_base_patch16_clsgap_224:sw_in1k	.196
93	voneresnet-50-robust	.186
94	ReAlnet01	.186
95	alexnet_ks_torevert	.186
96	resnet_152_v1	.186
97	ReAlnet_incorrect	.186
98	vonegrcnn_52e_full	.186
99	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.186
100	efficientnet_b2_imagenet_full	.186
101	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.186
102	vgg_16	.176
103	custom_model_cv_18_dagger_408	.176
104	resnet_50_v1	.176
105	ReAlnet03	.176
106	resnet50_tutorial	.176
107	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.176
108	efficientnet_b1_imagenet_full	.176
109	focalnet_tiny_lrf_in1k	.176
110	deit_small_imagenet_full_seed-0	.176
111	resnet50-sup	.176
112	resnet50-SIN_IN	.176
113	convnext_large_imagenet_full_seed-0	.165
114	voneresnet-50-non_stochastic	.165
115	inception_v1	.165
116	densenet-121	.165
117	bp_resnet50_julios	.155
118	resnet50-SIN	.155
119	ReAlnet06	.155
120	resnet50-SIN_IN_IN	.145
121	convnext_tiny_sup	.145
122	densenet-169	.145
123	ReAlnet05	.145
124	cvt_cvt-13-384-in1k_4_LucyV4	.145
125	resnet101_imagenet_full	.145
126	resnet_SIN_IN_FT_IN	.145
127	efficientnet_b0	.134
128	resnet50_eMMCR_Vanilla	.134
129	resnet50_imagenet_1_seed-0	.134
130	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.134
131	resnet-152_v2_pytorch	.134
132	BiT-S-R50x3	.124
133	resnet50_imagenet_full	.124
134	resnet50-moclr8deg	.124
135	ViT_L_32_imagenet1k	.124
136	BiT-S-R101x1	.124
137	mobilenet_v2_1_3_224	.124
138	convnext_femto_ols:d1_in1k	.124
139	xception	.114
140	alexnet_training_seed_04	.114
141	pnasnet_large_pytorch	.114
142	resnet_152_v2	.114
143	convnext_small_imagenet_10_seed-0	.114
144	BiT-S-R152x2	.114
145	resnet50-vicregl0p75	.103
146	convnext_small_imagenet_1_seed-0	.103
147	alexnet_training_seed_08	.103
148	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.103
149	deit_small_imagenet_10_seed-0	.103
150	alexnet_training_seed_02	.103
151	resnet50-vicregl0p9	.103
152	alexnet_training_seed_06	.103
153	alexnet_training_seed_10	.103
154	alexnet_training_seed_05	.103
155	BiT-S-R152x4	.103
156	alexnet_training_seed_09	.103
157	deit_small_imagenet_1_seed-0	.103
158	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.103
159	alexnet_training_seed_03	.093
160	convnext_small_imagenet_100_seed-0	.093
161	deit_small_imagenet_100_seed-0	.093
162	resnet50_imagenet_10_seed-0	.093
163	vgg_19	.093
164	resnet50-barlow	.093
165	artResNet18_1	.093
166	pnasnet_large	.083
167	alexnet_training_seed_07	.083
168	alexnet_training_seed_01	.072
169	yudixie_resnet50_cat_obj_class_all_latents_0_240908	X
170	yudixie_resnet50_random_0_240908	X
171	ReAlnet06_cornet	X
172	yudixie_resnet18_distance_reg_0_240719	X
173	yudixie_resnet18_translation_reg_0_240719	X
174	yudixie_resnet18_imagenet1kpret_0_240719	X
175	yudixie_resnet18_rotation_reg_0_240719	X
176	omnivore_swinS	X
177	yudixie_resnet50_distance_translation_rotation_0_240908	X
178	yudixie_resnet18_object_class_0_240719	X
179	ReAlnet09_cornet	X
180	ReAlnet05_cornet	X
181	yudixie_resnet18_distance_translation_rotation_0_240719	X
182	yudixie_resnet18_cat_obj_class_all_latents_0_240719	X
183	yudixie_resnet18_random_0_240719	X
184	resnet-18_test_m	X
185	yudixie_resnet18_category_class_0_240719	X
186	yudixie_resnet18_distance_rotation_0_240719	X
187	yudixie_resnet50_distance_translation_0_240908	X
188	yudixie_resnet18_translation_rotation_0_240719	X
189	ReAlnet04_cornet	X
190	yudixie_resnet18_distance_translation_0_240719	X
191	yudixie_resnet50_translation_reg_0_240908	X
192	resnet152_ecoset_full	X
193	resnet101_ecoset_full	X
194	resnet50_ecoset_full	X
195	VOneCORnet-S	X
196	resnet34_ecoset_full	X
197	resnet18_ecoset_full	X
198	yudixie_resnet50_distance_rotation_0_240908	X
199	yudixie_resnet50_rotation_reg_0_240908	X
200	ReAlnet03_cornet	X
201	ReAlnet02_cornet	X
202	ReAlnet10_cornet	X
203	ConvLSTM	X
204	ReAlnet01_cornet	X
205	MIM	X
206	TAU	X
207	SimVP	X
208	resnet18_imagenet21kP	X
209	PredRNN	X
210	antialiased-rnext101_32x8d	X
211	hmax	X
212	yudixie_resnet50_distance_reg_0_240908	X
213	yudixie_resnet50_category_class_0_240908	X
214	yudixie_resnet50_object_class_0_240908	X
215	yudixie_resnet50_imagenet1kpret_0_240908	X
216	ReAlnet07_cornet	X
217	yudixie_resnet50_translation_rotation_0_240908	X
218	resnet50-vicreg	X
219	omnivore_swinB	X
220	ReAlnet08_cornet	X
221	efficientnet-b7	X

Benchmark bibtex

None

Ceiling

0.98.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_1Behavioral

Metric: accuracy_distance