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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	convnext_base_fb_in1k	.507
16	convnext_base_fb_in22k_ft_in1k	.496
17	AdvProp_efficientnet-b8	.455
18	AdvProp_efficientnet-b7	.445
19	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.434
20	convnext_xlarge:fb_in22k_ft_in1k	.424
21	convnext_large:fb_in22k_ft_in1k	.413
22	vit_base_patch16_clip_224:openai_ft_in1k	.382
23	mobilenet_v2_1_0_160	.372
24	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.362
25	AdvProp_efficientnet-b6	.351
26	blt_vs	.341
27	densenet-201	.331
28	densenet_201_pytorch	.331
29	resnet50_robust_l2_eps1	.320
30	convnext_small_imagenet_full_seed-0	.310
31	mobilenet_v2_0_5_192	.310
32	mobilenet_v2_0_75_192	.310
33	grcnn_109	.300
34	AdvProp_efficientnet-b4	.289
35	AdvProp_efficientnet-b2	.289
36	AT_efficientnet-b2	.289
37	mobilenet_v2_1_0_128	.279
38	regnet_y_400mf	.279
39	shufflenet_v2_x1_0	.279
40	mobilenet_v2_1_0_224	.279
41	convnext_tiny:in12k_ft_in1k	.269
42	resnet-50-robust	.269
43	nasnet_large	.269
44	resnet_101_v2	.269
45	imagenet_l2_3_0	.269
46	resnet50_robust_l2_eps3	.269
47	resnet50_ewconplus_wzc_seed7_2_323	.269
48	deit3_base_patch16_224_fb_in1k	.269
49	convnext_tiny_imagenet_full_seed-0	.258
50	inception_v3_pytorch	.258
51	convnext_base_imagenet_full_seed-0	.258
52	convnext_base_fb_in1k_gram_aligned_dinov3	.258
53	cvt_cvt-21-224-in1k_4_LucyV4	.248
54	mobilenet_v2_0_75_160	.248
55	antialias-resnet152	.248
56	deit_base_imagenet_full_seed-0	.248
57	cvt_cvt-13-224-in1k_4_LucyV4	.248
58	resnet50_st_wzc_seed3_2_323	.248
59	deit3_base_patch16_224_fb_in22k_ft_in1k	.248
60	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.238
61	mobilenet_v2_1_0_192	.238
62	effnetb1_272x240	.238
63	resnext101_32x32d_wsl	.238
64	cvt_cvt-21-384-in1k_4_LucyV4	.238
65	resnet18_imagenet_full	.238
66	inception_v4	.238
67	Res2Net50_26w_4s	.238
68	grcnn	.238
69	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.227
70	alexnet_fov4	.227
71	resnet50_imagenet_100_seed-0	.227
72	mobilenet_v2_0_5_224	.227
73	efficientnet_b0_imagenet_full	.227
74	resnet152_imagenet_full	.227
75	antialiased-r50	.227
76	resnet50_ewconplus_wzc_seed2_2__323	.227
77	resnet50_st_wzc_seed7_2_323	.227
78	resnet50_st_wzc_noseed_2_323	.227
79	inception_v3	.217
80	mobilenet_v2_0_75_224	.217
81	mobilenet_v2_1-4_224_pytorch	.217
82	resnet50-VITO-8deg-cc	.217
83	resnet50-vitoimagevidnet8	.217
84	voneresnet-50	.217
85	mobilenet_v2_1_4_224	.217
86	ReAlnet04	.217
87	resnet_101_v1	.217
88	resnet50_st_wzc_2	.207
89	ReAlnet09	.207
90	tv_efficientnet-b1	.207
91	AlexNet_SIN	.207
92	deit_large_imagenet_full_seed-0	.207
93	resnet34_imagenet_full	.207
94	AlexNet_SIN_fov4	.207
95	vonegrcnn_62e_nobn	.207
96	BiT-S-R101x3	.207
97	BiT-S-R50x1	.207
98	resnet50_ewconplus_wzc_seed3_2_323	.207
99	resnet_50_v2	.196
100	resnet_50_v1_spiking	.196
101	ReAlnet07	.196
102	ReAlnet08	.196
103	ReAlnet10	.196
104	vit_relpos_base_patch16_clsgap_224:sw_in1k	.196
105	nasnet_mobile	.196
106	vonegrcnn_47e	.196
107	ReAlnet02	.196
108	resnet_152_v1	.186
109	resnet50_st_wzc_seed5_2_323	.186
110	alexnet	.186
111	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.186
112	alexnet_ks_torevert	.186
113	efficientnet_b2_imagenet_full	.186
114	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.186
115	voneresnet-50-robust	.186
116	ReAlnet01	.186
117	vonegrcnn_52e_full	.186
118	resnet50_ewconplus_wzc_seed6_2_323	.186
119	resnet50_tutorial	.176
120	cv_18_dagger_408_pretrained	.176
121	custom_model_cv_18_dagger_408	.176
122	focalnet_tiny_lrf_in1k	.176
123	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.176
124	efficientnet_b1_imagenet_full	.176
125	deit_small_imagenet_full_seed-0	.176
126	resnet50-SIN_IN	.176
127	vgg_16	.176
128	resnet_50_v1	.176
129	resnet50-sup	.176
130	ReAlnet03	.176
131	resnet50_ewconplus_wzc	.165
132	convnext_large_imagenet_full_seed-0	.165
133	voneresnet-50-non_stochastic	.165
134	inception_v1	.165
135	densenet-121	.165
136	resnet50_ewconplus_wzc_seed5_2__323	.165
137	resnet50_st_wzc_2_323	.165
138	ReAlnet06	.155
139	bp_resnet50_julios	.155
140	resnet50-SIN	.155
141	resnet50_st_wzc_seed6_2_323	.155
142	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.155
143	ReAlnet05	.145
144	resnet101_imagenet_full	.145
145	cvt_cvt-13-384-in1k_4_LucyV4	.145
146	resnet50-SIN_IN_IN	.145
147	resnet_SIN_IN_FT_IN	.145
148	convnext_tiny_sup	.145
149	densenet-169	.145
150	resnet50_ewconplus_wzc_2_323	.145
151	resnet50_imagenet_1_seed-0	.134
152	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.134
153	resnet50_eMMCR_Vanilla	.134
154	resnet-152_v2_pytorch	.134
155	efficientnet_b0	.134
156	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.134
157	resnet_50_v1_spiking_l4	.124
158	resnet50_imagenet_full	.124
159	ViT_L_32_imagenet1k	.124
160	resnet50-moclr8deg	.124
161	mobilenet_v2_1_3_224	.124
162	BiT-S-R50x3	.124
163	BiT-S-R101x1	.124
164	convnext_femto_ols:d1_in1k	.124
165	resnet50_ewconplus_noseed_2_323	.124
166	resnet_50_v1_spiking_l4a	.114
167	alexnet_training_seed_04	.114
168	pnasnet_large_pytorch	.114
169	convnext_small_imagenet_10_seed-0	.114
170	xception	.114
171	AlexNet_SIN_fov16	.114
172	BiT-S-R152x2	.114
173	resnet_152_v2	.114
174	alexnet_training_seed_09	.103
175	alexnet_training_seed_05	.103
176	alexnet_training_seed_06	.103
177	alexnet_training_seed_02	.103
178	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.103
179	alexnet_training_seed_08	.103
180	convnext_small_imagenet_1_seed-0	.103
181	deit_small_imagenet_10_seed-0	.103
182	alexnet_training_seed_10	.103
183	alexnet_fov16	.103
184	deit_small_imagenet_1_seed-0	.103
185	resnet_50_v1_spiking_l3	.103
186	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.103
187	alexnet_training_seed_01_fov16	.103
188	BiT-S-R152x4	.103
189	resnet50-vicregl0p75	.103
190	resnet50-vicregl0p9	.103
191	alexnet_fov12	.093
192	convnext_small_imagenet_100_seed-0	.093
193	deit_small_imagenet_100_seed-0	.093
194	resnet50_imagenet_10_seed-0	.093
195	vgg_19	.093
196	resnet50-barlow	.093
197	artResNet18_1	.093
198	alexnet_training_seed_03	.093
199	pnasnet_large_halfPrecision	.083
200	alexnet_training_seed_07	.083
201	AlexNet_SIN_fov12	.083
202	pnasnet_large	.083
203	alexnet_training_seed_01_fov12	.083
204	alexnet_training_seed_01	.072
205	alexnet_training_seed_01_fov4	.072
206	yudixie_resnet50_distance_translation_rotation_0_240908
207	yudixie_resnet50_random_0_240908
208	yudixie_resnet50_cat_obj_class_all_latents_0_240908
209	yudixie_resnet50_imagenet1kpret_0_240908
210	yudixie_resnet50_object_class_0_240908
211	ReAlnet06_ALL
212	ReAlnet08_ALL
213	yudixie_resnet50_category_class_0_240908
214	yudixie_resnet50_distance_reg_0_240908
215	vit_base_patch14_reg4_dinov2-lvd142m
216	hmax
217	antialiased-rnext101_32x8d
218	PredRNN
219	resnet18_imagenet21kP
220	SimVP
221	TAU
222	MIM
223	ReAlnet01_cornet
224	ConvLSTM
225	compact_resnet50_V4
226	briaai_rmbg_1_4
227	yolos_tiny
228	vit_base_patch16_dinov3-lvd1689m
229	ReAlnet02_cornet
230	ReAlnet03_cornet
231	yudixie_resnet50_rotation_reg_0_240908
232	yudixie_resnet50_distance_rotation_0_240908
233	resnet18_ecoset_full
234	compact_resnet50_IT
235	ReAlnet01_cornet_fov4
236	resnet34_ecoset_full
237	VOneCORnet-S
238	vit_base_patch14_dinov2-lvd142m
239	resnet50_ecoset_full
240	resnet101_ecoset_full
241	resnet152_ecoset_full
242	yudixie_resnet50_translation_reg_0_240908
243	ReAlnet01_cornet_fov12
244	yudixie_resnet18_distance_translation_0_240719
245	compact_vgg19_V4
246	ReAlnet04_cornet
247	yudixie_resnet18_translation_rotation_0_240719
248	yudixie_resnet50_distance_translation_0_240908
249	aughost_fair_resnet18
250	yudixie_resnet18_distance_rotation_0_240719
251	yudixie_resnet18_category_class_0_240719
252	resnet-18_test_m
253	yudixie_resnet18_random_0_240719
254	yudixie_resnet18_cat_obj_class_all_latents_0_240719
255	yudixie_resnet18_distance_translation_rotation_0_240719
256	ReAlnet05_cornet
257	yudixie_resnet18_object_class_0_240719
258	compact_vgg19_IT
259	yudixie_resnet18_rotation_reg_0_240719
260	yudixie_resnet18_imagenet1kpret_0_240719
261	yudixie_resnet18_translation_reg_0_240719
262	yudixie_resnet18_distance_reg_0_240719
263	compact_resnet50_robust_V4
264	ReAlnet01_cornet_fov16
265	ReAlnet06_cornet
266	efficientnet-b7
267	ReAlnet01_ALL
268	yudixie_resnet50_translation_rotation_0_240908
269	ReAlnet07_cornet
270	ReAlnet02_ALL
271	omnivore_swinB
272	resnet50-vicreg
273	ReAlnet03_ALL
274	ReAlnet08_cornet
275	compact_cornets_V4
276	ReAlnet04_ALL
277	compact_cornets_IT
278	omnivore_swinS
279	ReAlnet05_ALL
280	ReAlnet09_cornet
281	compact_resnet50_robust_IT
282	ReAlnet07_ALL
283	ReAlnet10_cornet
284	ReAlnet09_ALL
285	resnet50_primary_visual_cortex
286	ReAlnet10_ALL
287	resnet18_fair
288	pr1_stl10_disentangled_alpha04
289	predictive_coding_pc
290	yudixie_wbh_object_class_scaling_0415_run_0
291	yudixie_wbh_object_class_scaling_0415_run_3
292	yudixie_wbh_object_class_scaling_0415_imagenet
293	yudixie_wbh_object_class_scaling_0415_run_2
294	yudixie_wbh_object_class_scaling_0415_run_1
295	deepeisnn_ei_cifar10_vgg19
296	deepeisnn_ei_cifar10_resnet18
297	deepeisnn_ei_imagenet_resnet18

Benchmark bibtex

None

Ceiling

0.98.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_1Behavioral

Metric: accuracy_distance