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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	convnext_base_fb_in22k_ft_in1k	.577
12	resnext101_32x48d_wsl	.577
13	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.504
14	convnext_base_fb_in1k	.472
15	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.462
16	convnext_xlarge:fb_in22k_ft_in1k	.441
17	AdvProp_efficientnet-b7	.430
18	AdvProp_efficientnet-b6	.430
19	resnext101_32x32d_wsl	.430
20	convnext_large:fb_in22k_ft_in1k	.420
21	AdvProp_efficientnet-b4	.409
22	resnext101_32x16d_wsl	.409
23	AdvProp_efficientnet-b8	.399
24	resnext101_32x8d_wsl	.378
25	blt_vs	.367
26	mobilenet_v2_0_5_192	.357
27	vit_base_patch16_clip_224:openai_ft_in1k	.336
28	inception_v4	.325
29	mobilenet_v2_0_75_192	.325
30	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.315
31	inception_v3_pytorch	.315
32	resnet50_ewconplus_wzc_seed7_2_323	.304
33	resnet50_robust_l2_eps1	.304
34	convnext_large_imagenet_full_seed-0	.294
35	efficientnet_b0_imagenet_full	.294
36	resnet_101_v1	.283
37	grcnn_109	.283
38	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.283
39	resnet50_robust_l2_eps3	.283
40	imagenet_l2_3_0	.283
41	resnet-50-robust	.283
42	mobilenet_v2_0_75_160	.273
43	Res2Net50_26w_4s	.273
44	densenet-201	.273
45	BiT-S-R101x1	.273
46	resnet18_imagenet_full	.273
47	densenet_201_pytorch	.273
48	mobilenet_v2_1_0_128	.262
49	resnet50_ewconplus_wzc_seed3_2_323	.252
50	vonegrcnn_62e_nobn	.252
51	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.252
52	cvt_cvt-21-384-in1k_4_LucyV4	.252
53	ReAlnet08	.241
54	ReAlnet07	.241
55	voneresnet-50	.241
56	vit_relpos_base_patch16_clsgap_224:sw_in1k	.241
57	AT_efficientnet-b2	.241
58	AdvProp_efficientnet-b2	.241
59	vonegrcnn_47e	.241
60	convnext_base_imagenet_full_seed-0	.241
61	deit_large_imagenet_full_seed-0	.241
62	resnet50_ewconplus_wzc_seed2_2__323	.231
63	ReAlnet04	.231
64	vonegrcnn_52e_full	.231
65	deit_small_imagenet_full_seed-0	.231
66	resnet50_st_wzc_seed4_2_323	.220
67	mobilenet_v2_1_0_224	.220
68	mobilenet_v2_0_75_224	.220
69	mobilenet_v2_0_5_224	.220
70	antialiased-r50	.220
71	convnext_small_imagenet_full_seed-0	.220
72	cvt_cvt-21-224-in1k_4_LucyV4	.220
73	AlexNet_SIN_fov4	.220
74	alexnet_fov4	.220
75	voneresnet-50-non_stochastic	.220
76	focalnet_tiny_lrf_in1k	.220
77	resnet50_st_wzc_seed3_2_323	.210
78	resnet50_st_wzc_2_323	.210
79	resnet50_ewconplus_wzc_seed6_2_323	.210
80	resnet50_st_wzc_2	.210
81	resnet_101_v2	.210
82	nasnet_large	.210
83	inception_v1	.210
84	ReAlnet02	.210
85	ReAlnet01	.210
86	voneresnet-50-robust	.210
87	shufflenet_v2_x1_0	.210
88	convnext_tiny:in12k_ft_in1k	.210
89	convnext_tiny_imagenet_full_seed-0	.210
90	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.210
91	AlexNet_SIN	.210
92	effnetb1_272x240	.210
93	convnext_base_fb_in1k_gram_aligned_dinov3	.199
94	mobilenet_v2_1_0_160	.199
95	inception_v3	.199
96	resnet50-SIN_IN	.199
97	BiT-S-R50x3	.199
98	cvt_cvt-13-384-in1k_4_LucyV4	.199
99	regnet_y_400mf	.199
100	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.199
101	resnet50_st_wzc_seed7_2_323	.189
102	resnet50_ewconplus_noseed_2_323	.189
103	resnet_50_v1_spiking	.189
104	nasnet_mobile	.189
105	ReAlnet10	.189
106	ReAlnet09	.189
107	ReAlnet03	.189
108	BiT-S-R152x4	.189
109	efficientnet_b2_imagenet_full	.189
110	custom_model_cv_18_dagger_408	.189
111	deit3_base_patch16_224_fb_in1k	.178
112	mobilenet_v2_1_0_192	.178
113	resnet_50_v1	.178
114	grcnn	.178
115	resnet50-vitoimagevidnet8	.178
116	resnet50-barlow	.178
117	resnet50-VITO-8deg-cc	.178
118	convnext_femto_ols:d1_in1k	.178
119	densenet-121	.178
120	BiT-S-R50x1	.178
121	resnet50-sup	.178
122	deit_base_imagenet_full_seed-0	.178
123	resnet50_tutorial	.178
124	resnet50_imagenet_100_seed-0	.178
125	resnet152_imagenet_full	.178
126	cv_18_dagger_408_pretrained	.178
127	antialias-resnet152	.178
128	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.168
129	resnet_152_v1	.168
130	ReAlnet06	.168
131	resnet50-SIN	.168
132	densenet-169	.168
133	BiT-S-R101x3	.168
134	deit_small_imagenet_100_seed-0	.168
135	alexnet	.168
136	alexnet_ks_torevert	.168
137	resnet50_st_wzc_seed6_2_323	.157
138	vgg_16	.157
139	AlexNet_SIN_fov16	.157
140	resnet50_eMMCR_Vanilla	.157
141	resnet50_st_wzc_seed5_2_323	.147
142	resnet50_ewconplus_wzc_2_323	.147
143	ReAlnet05	.147
144	efficientnet_b1_imagenet_full	.147
145	resnet50_imagenet_1_seed-0	.147
146	cvt_cvt-13-224-in1k_4_LucyV4	.147
147	resnet50_imagenet_full	.147
148	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.147
149	tv_efficientnet-b1	.147
150	resnet50_st_wzc_noseed_2_323	.136
151	resnet_50_v1_spiking_l4	.136
152	convnext_small_imagenet_100_seed-0	.136
153	bp_resnet50_julios	.136
154	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.126
155	mobilenet_v2_1_3_224	.126
156	pnasnet_large	.126
157	alexnet_training_seed_03	.126
158	convnext_tiny_sup	.126
159	artResNet18_1	.126
160	resnet101_imagenet_full	.126
161	pnasnet_large_halfPrecision	.115
162	resnet50_ewconplus_wzc	.115
163	xception	.115
164	alexnet_training_seed_04	.115
165	resnet_50_v2	.115
166	resnet50-SIN_IN_IN	.115
167	efficientnet_b0	.115
168	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.115
169	BiT-S-R152x2	.115
170	resnet_SIN_IN_FT_IN	.115
171	resnet34_imagenet_full	.115
172	resnet_50_v1_spiking_l3	.105
173	alexnet_training_seed_10	.105
174	alexnet_training_seed_08	.105
175	alexnet_training_seed_02	.105
176	alexnet_training_seed_06	.105
177	alexnet_training_seed_05	.105
178	alexnet_training_seed_09	.105
179	resnet_152_v2	.105
180	resnet50-moclr8deg	.105
181	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.105
182	resnet50-vicregl0p9	.105
183	resnet50-vicregl0p75	.105
184	convnext_small_imagenet_10_seed-0	.105
185	convnext_small_imagenet_1_seed-0	.105
186	deit_small_imagenet_1_seed-0	.105
187	deit_small_imagenet_10_seed-0	.105
188	alexnet_training_seed_01_fov16	.105
189	alexnet_training_seed_01_fov12	.105
190	pnasnet_large_pytorch	.105
191	resnet-152_v2_pytorch	.105
192	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
193	ViT_L_32_imagenet1k	.105
194	alexnet_fov16	.094
195	vgg_19	.084
196	alexnet_training_seed_01_fov4	.084
197	AlexNet_SIN_fov12	.084
198	resnet_50_v1_spiking_l4a	.073
199	mobilenet_v2_1_4_224	.073
200	alexnet_training_seed_01	.073
201	alexnet_training_seed_07	.073
202	resnet50_imagenet_10_seed-0	.073
203	alexnet_fov12	.073
204	mobilenet_v2_1-4_224_pytorch	.073
205	deepeisnn_ei_imagenet_resnet18
206	deepeisnn_ei_cifar10_resnet18
207	deepeisnn_ei_cifar10_vgg19
208	yudixie_wbh_object_class_scaling_0415_run_1
209	yudixie_wbh_object_class_scaling_0415_run_2
210	yudixie_wbh_object_class_scaling_0415_run_3
211	yudixie_wbh_object_class_scaling_0415_imagenet
212	yudixie_wbh_object_class_scaling_0415_run_0
213	predictive_coding_pc
214	pr1_stl10_disentangled_alpha04
215	resnet18_fair
216	vit_base_patch16_dinov3-lvd1689m
217	vit_base_patch14_reg4_dinov2-lvd142m
218	vit_base_patch14_dinov2-lvd142m
219	aughost_fair_resnet18
220	compact_resnet50_robust_IT
221	compact_vgg19_IT
222	compact_cornets_IT
223	compact_cornets_V4
224	compact_resnet50_robust_V4
225	compact_vgg19_V4
226	compact_resnet50_IT
227	compact_resnet50_V4
228	ReAlnet10_ALL
229	ReAlnet09_ALL
230	ReAlnet08_ALL
231	ReAlnet07_ALL
232	ReAlnet05_ALL
233	ReAlnet04_ALL
234	ReAlnet03_ALL
235	ReAlnet02_ALL
236	ReAlnet01_ALL
237	resnet50_primary_visual_cortex
238	yolos_tiny
239	briaai_rmbg_1_4
240	yudixie_resnet50_distance_reg_0_240908
241	yudixie_resnet50_category_class_0_240908
242	yudixie_resnet50_cat_obj_class_all_latents_0_240908
243	yudixie_resnet50_object_class_0_240908
244	yudixie_resnet50_distance_translation_rotation_0_240908
245	yudixie_resnet50_random_0_240908
246	yudixie_resnet50_imagenet1kpret_0_240908
247	ReAlnet10_cornet
248	ReAlnet09_cornet
249	ReAlnet06_cornet
250	ReAlnet05_cornet
251	ReAlnet04_cornet
252	ReAlnet02_cornet
253	ReAlnet03_cornet
254	ReAlnet01_cornet
255	yudixie_resnet50_translation_rotation_0_240908
256	yudixie_resnet50_distance_translation_0_240908
257	yudixie_resnet50_rotation_reg_0_240908
258	yudixie_resnet50_translation_reg_0_240908
259	yudixie_resnet50_distance_rotation_0_240908
260	resnet50-vicreg
261	efficientnet-b7
262	resnet-18_test_m
263	omnivore_swinS
264	VOneCORnet-S
265	omnivore_swinB
266	yudixie_resnet18_distance_reg_0_240719
267	yudixie_resnet18_translation_reg_0_240719
268	yudixie_resnet18_imagenet1kpret_0_240719
269	yudixie_resnet18_rotation_reg_0_240719
270	yudixie_resnet18_object_class_0_240719
271	yudixie_resnet18_distance_translation_rotation_0_240719
272	yudixie_resnet18_cat_obj_class_all_latents_0_240719
273	yudixie_resnet18_random_0_240719
274	yudixie_resnet18_category_class_0_240719
275	yudixie_resnet18_distance_rotation_0_240719
276	yudixie_resnet18_translation_rotation_0_240719
277	yudixie_resnet18_distance_translation_0_240719
278	resnet152_ecoset_full
279	resnet101_ecoset_full
280	resnet50_ecoset_full
281	resnet34_ecoset_full
282	resnet18_ecoset_full
283	ReAlnet01_cornet_fov16
284	ReAlnet01_cornet_fov12
285	ReAlnet01_cornet_fov4
286	ReAlnet08_cornet
287	ReAlnet07_cornet
288	ReAlnet06_ALL
289	SimVP
290	MIM
291	TAU
292	PredRNN
293	ConvLSTM
294	resnet18_imagenet21kP
295	antialiased-rnext101_32x8d
296	hmax

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_2Behavioral

Metric: accuracy_distance