Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("BMD2024.texture_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	1.0
2	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.971
3	vit_large_patch14_clip_224:laion2b_ft_in1k	.952
4	vit_large_patch14_clip_336:laion2b_ft_in1k	.913
5	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.892
6	vit_large_patch14_clip_224:openai_ft_in1k	.882
7	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.850
8	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.840
9	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.672
10	convnext_base:clip_laiona_augreg_ft_in1k_384	.609
11	resnext101_32x48d_wsl	.577
12	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.504
13	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.462
14	convnext_xlarge:fb_in22k_ft_in1k	.441
15	resnext101_32x32d_wsl	.430
16	AdvProp_efficientnet-b6	.430
17	AdvProp_efficientnet-b7	.430
18	convnext_large:fb_in22k_ft_in1k	.420
19	resnext101_32x16d_wsl	.409
20	AdvProp_efficientnet-b4	.409
21	AdvProp_efficientnet-b8	.399
22	resnext101_32x8d_wsl	.378
23	blt_vs	.367
24	mobilenet_v2_0_5_192	.357
25	vit_base_patch16_clip_224:openai_ft_in1k	.336
26	inception_v4	.325
27	mobilenet_v2_0_75_192	.325
28	inception_v3_pytorch	.315
29	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.315
30	resnet50_robust_l2_eps1	.304
31	convnext_large_imagenet_full_seed-0	.294
32	efficientnet_b0_imagenet_full	.294
33	imagenet_l2_3_0	.283
34	grcnn_109	.283
35	resnet-50-robust	.283
36	resnet_101_v1	.283
37	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.283
38	resnet50_robust_l2_eps3	.283
39	densenet-201	.273
40	densenet_201_pytorch	.273
41	mobilenet_v2_0_75_160	.273
42	BiT-S-R101x1	.273
43	Res2Net50_26w_4s	.273
44	resnet18_imagenet_full	.273
45	mobilenet_v2_1_0_128	.262
46	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.252
47	cvt_cvt-21-384-in1k_4_LucyV4	.252
48	vonegrcnn_62e_nobn	.252
49	ReAlnet08	.241
50	convnext_base_imagenet_full_seed-0	.241
51	voneresnet-50	.241
52	vit_relpos_base_patch16_clsgap_224:sw_in1k	.241
53	vonegrcnn_47e	.241
54	deit_large_imagenet_full_seed-0	.241
55	ReAlnet07	.241
56	AdvProp_efficientnet-b2	.241
57	AT_efficientnet-b2	.241
58	vonegrcnn_52e_full	.231
59	deit_small_imagenet_full_seed-0	.231
60	ReAlnet04	.231
61	cvt_cvt-21-224-in1k_4_LucyV4	.220
62	mobilenet_v2_0_75_224	.220
63	mobilenet_v2_1_0_224	.220
64	mobilenet_v2_0_5_224	.220
65	focalnet_tiny_lrf_in1k	.220
66	antialiased-r50	.220
67	voneresnet-50-non_stochastic	.220
68	convnext_small_imagenet_full_seed-0	.220
69	effnetb1_272x240	.210
70	convnext_tiny:in12k_ft_in1k	.210
71	nasnet_large	.210
72	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.210
73	convnext_tiny_imagenet_full_seed-0	.210
74	ReAlnet02	.210
75	ReAlnet_incorrect	.210
76	AlexNet_SIN	.210
77	shufflenet_v2_x1_0	.210
78	ReAlnet01	.210
79	voneresnet-50-robust	.210
80	resnet_101_v2	.210
81	inception_v1	.210
82	regnet_y_400mf	.199
83	resnet50-SIN_IN	.199
84	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.199
85	BiT-S-R50x3	.199
86	cvt_cvt-13-384-in1k_4_LucyV4	.199
87	inception_v3	.199
88	mobilenet_v2_1_0_160	.199
89	ReAlnet03	.189
90	ReAlnet09	.189
91	BiT-S-R152x4	.189
92	custom_model_cv_18_dagger_408	.189
93	nasnet_mobile	.189
94	ReAlnet10	.189
95	efficientnet_b2_imagenet_full	.189
96	BiT-S-R50x1	.178
97	deit_base_imagenet_full_seed-0	.178
98	densenet-121	.178
99	grcnn	.178
100	resnet50-vitoimagevidnet8	.178
101	resnet_50_v1	.178
102	antialias-resnet152	.178
103	resnet152_imagenet_full	.178
104	resnet50_tutorial	.178
105	mobilenet_v2_1_0_192	.178
106	resnet50_imagenet_100_seed-0	.178
107	resnet50-barlow	.178
108	resnet50-VITO-8deg-cc	.178
109	resnet50-sup	.178
110	convnext_femto_ols:d1_in1k	.178
111	resnet_152_v1	.168
112	alexnet_ks_torevert	.168
113	densenet-169	.168
114	ReAlnet06	.168
115	BiT-S-R101x3	.168
116	deit_small_imagenet_100_seed-0	.168
117	resnet50-SIN	.168
118	resnet50_eMMCR_Vanilla	.157
119	vgg_16	.157
120	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.147
121	efficientnet_b1_imagenet_full	.147
122	resnet50_imagenet_1_seed-0	.147
123	resnet50_imagenet_full	.147
124	ReAlnet05	.147
125	cvt_cvt-13-224-in1k_4_LucyV4	.147
126	tv_efficientnet-b1	.147
127	bp_resnet50_julios	.136
128	convnext_small_imagenet_100_seed-0	.136
129	alexnet_training_seed_03	.126
130	mobilenet_v2_1_3_224	.126
131	convnext_tiny_sup	.126
132	resnet101_imagenet_full	.126
133	artResNet18_1	.126
134	pnasnet_large	.126
135	alexnet_training_seed_04	.115
136	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.115
137	resnet34_imagenet_full	.115
138	resnet_50_v2	.115
139	resnet50-SIN_IN_IN	.115
140	xception	.115
141	BiT-S-R152x2	.115
142	efficientnet_b0	.115
143	resnet_SIN_IN_FT_IN	.115
144	alexnet_training_seed_05	.105
145	alexnet_training_seed_10	.105
146	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.105
147	resnet50-moclr8deg	.105
148	deit_small_imagenet_1_seed-0	.105
149	alexnet_training_seed_02	.105
150	ViT_L_32_imagenet1k	.105
151	alexnet_training_seed_06	.105
152	deit_small_imagenet_10_seed-0	.105
153	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
154	convnext_small_imagenet_10_seed-0	.105
155	pnasnet_large_pytorch	.105
156	resnet-152_v2_pytorch	.105
157	resnet50-vicregl0p75	.105
158	resnet50-vicregl0p9	.105
159	alexnet_training_seed_08	.105
160	alexnet_training_seed_09	.105
161	convnext_small_imagenet_1_seed-0	.105
162	resnet_152_v2	.105
163	vgg_19	.084
164	alexnet_training_seed_07	.073
165	alexnet_training_seed_01	.073
166	mobilenet_v2_1-4_224_pytorch	.073
167	mobilenet_v2_1_4_224	.073
168	resnet50_imagenet_10_seed-0	.073
169	hmax	X
170	ReAlnet03_cornet	X
171	yudixie_resnet50_cat_obj_class_all_latents_0_240908	X
172	ReAlnet01_cornet	X
173	yudixie_resnet18_distance_translation_rotation_0_240719	X
174	antialiased-rnext101_32x8d	X
175	SimVP	X
176	yudixie_resnet50_object_class_0_240908	X
177	MIM	X
178	TAU	X
179	PredRNN	X
180	ConvLSTM	X
181	yudixie_resnet18_distance_rotation_0_240719	X
182	resnet18_imagenet21kP	X
183	yudixie_resnet50_distance_translation_0_240908	X
184	yudixie_resnet18_category_class_0_240719	X
185	yudixie_resnet18_translation_rotation_0_240719	X
186	resnet-18_test_m	X
187	yudixie_resnet18_random_0_240719	X
188	yudixie_resnet18_cat_obj_class_all_latents_0_240719	X
189	yudixie_resnet50_rotation_reg_0_240908	X
190	ReAlnet06_cornet	X
191	yudixie_resnet18_object_class_0_240719	X
192	yudixie_resnet50_distance_reg_0_240908	X
193	yudixie_resnet18_rotation_reg_0_240719	X
194	yudixie_resnet18_imagenet1kpret_0_240719	X
195	yudixie_resnet18_translation_reg_0_240719	X
196	ReAlnet05_cornet	X
197	yudixie_resnet18_distance_reg_0_240719	X
198	efficientnet-b7	X
199	ReAlnet07_cornet	X
200	omnivore_swinB	X
201	yudixie_resnet50_translation_rotation_0_240908	X
202	ReAlnet08_cornet	X
203	yudixie_resnet18_distance_translation_0_240719	X
204	VOneCORnet-S	X
205	resnet50-vicreg	X
206	resnet152_ecoset_full	X
207	yudixie_resnet50_translation_reg_0_240908	X
208	ReAlnet09_cornet	X
209	resnet101_ecoset_full	X
210	yudixie_resnet50_category_class_0_240908	X
211	resnet50_ecoset_full	X
212	omnivore_swinS	X
213	ReAlnet04_cornet	X
214	ReAlnet10_cornet	X
215	resnet34_ecoset_full	X
216	resnet18_ecoset_full	X
217	yudixie_resnet50_imagenet1kpret_0_240908	X
218	yudixie_resnet50_distance_rotation_0_240908	X
219	yudixie_resnet50_random_0_240908	X
220	yudixie_resnet50_distance_translation_rotation_0_240908	X
221	ReAlnet02_cornet	X

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_2Behavioral

Metric: accuracy_distance