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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	.331
26	densenet_201_pytorch	.331
27	resnet50_robust_l2_eps1	.320
28	convnext_small_imagenet_full_seed-0	.310
29	mobilenet_v2_0_5_192	.310
30	mobilenet_v2_0_75_192	.310
31	grcnn_109	.300
32	AdvProp_efficientnet-b4	.289
33	AdvProp_efficientnet-b2	.289
34	AT_efficientnet-b2	.289
35	mobilenet_v2_1_0_128	.279
36	regnet_y_400mf	.279
37	shufflenet_v2_x1_0	.279
38	mobilenet_v2_1_0_224	.279
39	convnext_tiny:in12k_ft_in1k	.269
40	resnet-50-robust	.269
41	nasnet_large	.269
42	resnet_101_v2	.269
43	imagenet_l2_3_0	.269
44	resnet50_robust_l2_eps3	.269
45	convnext_tiny_imagenet_full_seed-0	.258
46	inception_v3_pytorch	.258
47	convnext_base_imagenet_full_seed-0	.258
48	cvt_cvt-21-224-in1k_4_LucyV4	.248
49	mobilenet_v2_0_75_160	.248
50	antialias-resnet152	.248
51	deit_base_imagenet_full_seed-0	.248
52	cvt_cvt-13-224-in1k_4_LucyV4	.248
53	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.238
54	mobilenet_v2_1_0_192	.238
55	effnetb1_272x240	.238
56	resnext101_32x32d_wsl	.238
57	cvt_cvt-21-384-in1k_4_LucyV4	.238
58	resnet18_imagenet_full	.238
59	inception_v4	.238
60	Res2Net50_26w_4s	.238
61	grcnn	.238
62	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.227
63	alexnet_fov4	.227
64	resnet50_imagenet_100_seed-0	.227
65	mobilenet_v2_0_5_224	.227
66	efficientnet_b0_imagenet_full	.227
67	resnet152_imagenet_full	.227
68	antialiased-r50	.227
69	inception_v3	.217
70	mobilenet_v2_0_75_224	.217
71	mobilenet_v2_1-4_224_pytorch	.217
72	resnet50-VITO-8deg-cc	.217
73	resnet50-vitoimagevidnet8	.217
74	voneresnet-50	.217
75	mobilenet_v2_1_4_224	.217
76	ReAlnet04	.217
77	resnet_101_v1	.217
78	ReAlnet09	.207
79	tv_efficientnet-b1	.207
80	AlexNet_SIN	.207
81	deit_large_imagenet_full_seed-0	.207
82	resnet34_imagenet_full	.207
83	AlexNet_SIN_fov4	.207
84	vonegrcnn_62e_nobn	.207
85	BiT-S-R101x3	.207
86	BiT-S-R50x1	.207
87	resnet_50_v2	.196
88	resnet_50_v1_spiking	.196
89	ReAlnet07	.196
90	ReAlnet08	.196
91	ReAlnet10	.196
92	vit_relpos_base_patch16_clsgap_224:sw_in1k	.196
93	nasnet_mobile	.196
94	vonegrcnn_47e	.196
95	ReAlnet02	.196
96	resnet_152_v1	.186
97	alexnet	.186
98	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.186
99	alexnet_ks_torevert	.186
100	efficientnet_b2_imagenet_full	.186
101	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.186
102	voneresnet-50-robust	.186
103	ReAlnet01	.186
104	vonegrcnn_52e_full	.186
105	resnet50_tutorial	.176
106	cv_18_dagger_408_pretrained	.176
107	custom_model_cv_18_dagger_408	.176
108	focalnet_tiny_lrf_in1k	.176
109	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.176
110	efficientnet_b1_imagenet_full	.176
111	deit_small_imagenet_full_seed-0	.176
112	resnet50-SIN_IN	.176
113	vgg_16	.176
114	resnet_50_v1	.176
115	resnet50-sup	.176
116	ReAlnet03	.176
117	resnet50_ewconplus_wzc	.165
118	convnext_large_imagenet_full_seed-0	.165
119	voneresnet-50-non_stochastic	.165
120	inception_v1	.165
121	densenet-121	.165
122	ReAlnet06	.155
123	bp_resnet50_julios	.155
124	resnet50-SIN	.155
125	ReAlnet05	.145
126	resnet101_imagenet_full	.145
127	cvt_cvt-13-384-in1k_4_LucyV4	.145
128	resnet50-SIN_IN_IN	.145
129	resnet_SIN_IN_FT_IN	.145
130	convnext_tiny_sup	.145
131	densenet-169	.145
132	resnet50_imagenet_1_seed-0	.134
133	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.134
134	resnet50_eMMCR_Vanilla	.134
135	resnet-152_v2_pytorch	.134
136	efficientnet_b0	.134
137	resnet_50_v1_spiking_l4	.124
138	resnet50_imagenet_full	.124
139	ViT_L_32_imagenet1k	.124
140	resnet50-moclr8deg	.124
141	mobilenet_v2_1_3_224	.124
142	BiT-S-R50x3	.124
143	BiT-S-R101x1	.124
144	convnext_femto_ols:d1_in1k	.124
145	resnet_50_v1_spiking_l4a	.114
146	alexnet_training_seed_04	.114
147	pnasnet_large_pytorch	.114
148	convnext_small_imagenet_10_seed-0	.114
149	xception	.114
150	AlexNet_SIN_fov16	.114
151	BiT-S-R152x2	.114
152	resnet_152_v2	.114
153	alexnet_training_seed_09	.103
154	alexnet_training_seed_05	.103
155	alexnet_training_seed_06	.103
156	alexnet_training_seed_02	.103
157	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.103
158	alexnet_training_seed_08	.103
159	convnext_small_imagenet_1_seed-0	.103
160	deit_small_imagenet_10_seed-0	.103
161	alexnet_training_seed_10	.103
162	alexnet_fov16	.103
163	deit_small_imagenet_1_seed-0	.103
164	resnet_50_v1_spiking_l3	.103
165	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.103
166	alexnet_training_seed_01_fov16	.103
167	BiT-S-R152x4	.103
168	resnet50-vicregl0p75	.103
169	resnet50-vicregl0p9	.103
170	alexnet_fov12	.093
171	convnext_small_imagenet_100_seed-0	.093
172	deit_small_imagenet_100_seed-0	.093
173	resnet50_imagenet_10_seed-0	.093
174	vgg_19	.093
175	resnet50-barlow	.093
176	artResNet18_1	.093
177	alexnet_training_seed_03	.093
178	alexnet_training_seed_07	.083
179	AlexNet_SIN_fov12	.083
180	pnasnet_large	.083
181	alexnet_training_seed_01_fov12	.083
182	alexnet_training_seed_01	.072
183	alexnet_training_seed_01_fov4	.072
184	yudixie_resnet50_distance_translation_rotation_0_240908
185	yudixie_resnet50_random_0_240908
186	yudixie_resnet50_cat_obj_class_all_latents_0_240908
187	yudixie_resnet50_imagenet1kpret_0_240908
188	yudixie_resnet50_object_class_0_240908
189	ReAlnet06_ALL
190	ReAlnet08_ALL
191	yudixie_resnet50_category_class_0_240908
192	yudixie_resnet50_distance_reg_0_240908
193	hmax
194	antialiased-rnext101_32x8d
195	PredRNN
196	resnet18_imagenet21kP
197	SimVP
198	TAU
199	MIM
200	ReAlnet01_cornet
201	ConvLSTM
202	compact_resnet50_V4
203	briaai_rmbg_1_4
204	yolos_tiny
205	ReAlnet02_cornet
206	ReAlnet03_cornet
207	yudixie_resnet50_rotation_reg_0_240908
208	yudixie_resnet50_distance_rotation_0_240908
209	resnet18_ecoset_full
210	compact_resnet50_IT
211	ReAlnet01_cornet_fov4
212	resnet34_ecoset_full
213	VOneCORnet-S
214	resnet50_ecoset_full
215	resnet101_ecoset_full
216	resnet152_ecoset_full
217	yudixie_resnet50_translation_reg_0_240908
218	ReAlnet01_cornet_fov12
219	yudixie_resnet18_distance_translation_0_240719
220	compact_vgg19_V4
221	ReAlnet04_cornet
222	yudixie_resnet18_translation_rotation_0_240719
223	yudixie_resnet50_distance_translation_0_240908
224	yudixie_resnet18_distance_rotation_0_240719
225	yudixie_resnet18_category_class_0_240719
226	resnet-18_test_m
227	yudixie_resnet18_random_0_240719
228	yudixie_resnet18_cat_obj_class_all_latents_0_240719
229	yudixie_resnet18_distance_translation_rotation_0_240719
230	ReAlnet05_cornet
231	yudixie_resnet18_object_class_0_240719
232	compact_vgg19_IT
233	yudixie_resnet18_rotation_reg_0_240719
234	yudixie_resnet18_imagenet1kpret_0_240719
235	yudixie_resnet18_translation_reg_0_240719
236	yudixie_resnet18_distance_reg_0_240719
237	compact_resnet50_robust_V4
238	ReAlnet01_cornet_fov16
239	ReAlnet06_cornet
240	efficientnet-b7
241	ReAlnet01_ALL
242	yudixie_resnet50_translation_rotation_0_240908
243	ReAlnet07_cornet
244	ReAlnet02_ALL
245	omnivore_swinB
246	resnet50-vicreg
247	ReAlnet03_ALL
248	ReAlnet08_cornet
249	compact_cornets_V4
250	ReAlnet04_ALL
251	compact_cornets_IT
252	omnivore_swinS
253	ReAlnet05_ALL
254	ReAlnet09_cornet
255	compact_resnet50_robust_IT
256	ReAlnet07_ALL
257	ReAlnet10_cornet
258	ReAlnet09_ALL
259	resnet50_primary_visual_cortex
260	ReAlnet10_ALL

Benchmark bibtex

None

Ceiling

0.98.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_1Behavioral

Metric: accuracy_distance