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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	1.0
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
3	eva02_large_in22k	.980
4	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.971
5	vit_large_patch14_clip_224:laion2b_ft_in1k	.952
6	vit_large_patch14_clip_336:laion2b_ft_in1k	.913
7	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.892
8	vit_large_clip336_openai	.882
9	vit_large_patch14_clip_224:openai_ft_in1k	.882
10	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.850
11	dinov2_vitg14_reg_lc	.840
12	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.840
13	dinov2_vitg14_lc	.819
14	dinov2_vitl14_reg_lc	.808
15	convnext_large_clip_laion2b_finelayers	.756
16	vit_huge_clip336_laion	.724
17	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.672
18	convnext_base:clip_laiona_augreg_ft_in1k_384	.609
19	dinov2_vitl14_lc_res336	.577
20	convnext_base_fb_in22k_ft_in1k	.577
21	resnext101_32x48d_wsl	.577
22	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.504
23	convnext_base_fb_in1k	.472
24	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.462
25	convnext_xlarge:fb_in22k_ft_in1k	.441
26	AdvProp_efficientnet-b7	.430
27	AdvProp_efficientnet-b6	.430
28	resnext101_32x32d_wsl	.430
29	convnext_large:fb_in22k_ft_in1k	.420
30	AdvProp_efficientnet-b4	.409
31	resnext101_32x16d_wsl	.409
32	dinov2_vitl14_lc	.399
33	AdvProp_efficientnet-b8	.399
34	resnext101_32x8d_wsl	.378
35	blt_vs	.367
36	mobilenet_v2_0_5_192	.357
37	vit_base_patch16_clip_224:openai_ft_in1k	.336
38	inception_v4	.325
39	mobilenet_v2_0_75_192	.325
40	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.315
41	inception_v3_pytorch	.315
42	convnext_large_in22k_supervised	.304
43	resnet50_robust_l2_eps1	.304
44	convnext_large_imagenet_full_seed-0	.294
45	efficientnet_b0_imagenet_full	.294
46	resnet_101_v1	.283
47	grcnn_109	.283
48	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.283
49	resnet50_robust_l2_eps3	.283
50	imagenet_l2_3_0	.283
51	resnet-50-robust	.283
52	mobilenet_v2_0_75_160	.273
53	Res2Net50_26w_4s	.273
54	densenet-201	.273
55	BiT-S-R101x1	.273
56	resnet18_imagenet_full	.273
57	densenet_201_pytorch	.273
58	mobilenet_v2_1_0_128	.262
59	vonegrcnn_62e_nobn	.252
60	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.252
61	cvt_cvt-21-384-in1k_4_LucyV4	.252
62	ReAlnet08	.241
63	ReAlnet07	.241
64	voneresnet-50	.241
65	vit_relpos_base_patch16_clsgap_224:sw_in1k	.241
66	AT_efficientnet-b2	.241
67	AdvProp_efficientnet-b2	.241
68	vonegrcnn_47e	.241
69	convnext_base_imagenet_full_seed-0	.241
70	deit_large_imagenet_full_seed-0	.241
71	resnet50_ewconplus_wzc_seed2_2__323	.231
72	ReAlnet04	.231
73	vonegrcnn_52e_full	.231
74	deit_small_imagenet_full_seed-0	.231
75	mobilenet_v2_1_0_224	.220
76	mobilenet_v2_0_75_224	.220
77	mobilenet_v2_0_5_224	.220
78	antialiased-r50	.220
79	convnext_small_imagenet_full_seed-0	.220
80	cvt_cvt-21-224-in1k_4_LucyV4	.220
81	AlexNet_SIN_fov4	.220
82	alexnet_fov4	.220
83	voneresnet-50-non_stochastic	.220
84	focalnet_tiny_lrf_in1k	.220
85	resnet50_st_wzc_seed3_2_323	.210
86	resnet50_ewconplus_wzc_seed6_2_323	.210
87	resnet50_st_wzc_2	.210
88	resnet_101_v2	.210
89	nasnet_large	.210
90	inception_v1	.210
91	ReAlnet02	.210
92	ReAlnet01	.210
93	voneresnet-50-robust	.210
94	shufflenet_v2_x1_0	.210
95	convnext_tiny:in12k_ft_in1k	.210
96	convnext_tiny_imagenet_full_seed-0	.210
97	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.210
98	AlexNet_SIN	.210
99	effnetb1_272x240	.210
100	convnext_base_fb_in1k_gram_aligned_dinov3	.199
101	mobilenet_v2_1_0_160	.199
102	inception_v3	.199
103	resnet50-SIN_IN	.199
104	BiT-S-R50x3	.199
105	cvt_cvt-13-384-in1k_4_LucyV4	.199
106	regnet_y_400mf	.199
107	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.199
108	resnet50_st_wzc_seed7_2_323	.189
109	resnet_50_v1_spiking	.189
110	nasnet_mobile	.189
111	ReAlnet10	.189
112	ReAlnet09	.189
113	ReAlnet03	.189
114	BiT-S-R152x4	.189
115	efficientnet_b2_imagenet_full	.189
116	custom_model_cv_18_dagger_408	.189
117	deit3_base_patch16_224_fb_in1k	.178
118	mobilenet_v2_1_0_192	.178
119	resnet_50_v1	.178
120	grcnn	.178
121	resnet50-vitoimagevidnet8	.178
122	resnet50-barlow	.178
123	resnet50-VITO-8deg-cc	.178
124	convnext_femto_ols:d1_in1k	.178
125	densenet-121	.178
126	BiT-S-R50x1	.178
127	resnet50-sup	.178
128	deit_base_imagenet_full_seed-0	.178
129	resnet50_tutorial	.178
130	resnet50_imagenet_100_seed-0	.178
131	resnet152_imagenet_full	.178
132	cv_18_dagger_408_pretrained	.178
133	antialias-resnet152	.178
134	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.168
135	resnet_152_v1	.168
136	ReAlnet06	.168
137	resnet50-SIN	.168
138	densenet-169	.168
139	BiT-S-R101x3	.168
140	deit_small_imagenet_100_seed-0	.168
141	alexnet	.168
142	alexnet_ks_torevert	.168
143	resnet50_st_wzc_seed6_2_323	.157
144	resnet50_hvs_wzc	.157
145	vgg_16	.157
146	AlexNet_SIN_fov16	.157
147	resnet50_eMMCR_Vanilla	.157
148	ReAlnet05	.147
149	efficientnet_b1_imagenet_full	.147
150	resnet50_imagenet_1_seed-0	.147
151	cvt_cvt-13-224-in1k_4_LucyV4	.147
152	resnet50_imagenet_full	.147
153	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.147
154	tv_efficientnet-b1	.147
155	resnet_50_v1_spiking_l4	.136
156	convnext_small_imagenet_100_seed-0	.136
157	bp_resnet50_julios	.136
158	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.126
159	mobilenet_v2_1_3_224	.126
160	pnasnet_large	.126
161	alexnet_training_seed_03	.126
162	convnext_tiny_sup	.126
163	artResNet18_1	.126
164	resnet101_imagenet_full	.126
165	pnasnet_large_halfPrecision	.115
166	resnet50_ewconplus_wzc	.115
167	xception	.115
168	alexnet_training_seed_04	.115
169	resnet_50_v2	.115
170	resnet50-SIN_IN_IN	.115
171	efficientnet_b0	.115
172	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.115
173	BiT-S-R152x2	.115
174	resnet_SIN_IN_FT_IN	.115
175	resnet34_imagenet_full	.115
176	resnet_50_v1_spiking_l3	.105
177	alexnet_training_seed_10	.105
178	alexnet_training_seed_08	.105
179	alexnet_training_seed_02	.105
180	alexnet_training_seed_06	.105
181	alexnet_training_seed_05	.105
182	alexnet_training_seed_09	.105
183	resnet_152_v2	.105
184	resnet50-moclr8deg	.105
185	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.105
186	resnet50-vicregl0p9	.105
187	resnet50-vicregl0p75	.105
188	convnext_small_imagenet_10_seed-0	.105
189	convnext_small_imagenet_1_seed-0	.105
190	deit_small_imagenet_1_seed-0	.105
191	deit_small_imagenet_10_seed-0	.105
192	alexnet_training_seed_01_fov16	.105
193	alexnet_training_seed_01_fov12	.105
194	pnasnet_large_pytorch	.105
195	resnet-152_v2_pytorch	.105
196	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.105
197	ViT_L_32_imagenet1k	.105
198	alexnet_fov16	.094
199	vgg_19	.084
200	alexnet_training_seed_01_fov4	.084
201	AlexNet_SIN_fov12	.084
202	resnet_50_v1_spiking_l4a	.073
203	mobilenet_v2_1_4_224	.073
204	alexnet_training_seed_01	.073
205	alexnet_training_seed_07	.073
206	resnet50_imagenet_10_seed-0	.073
207	alexnet_fov12	.073
208	mobilenet_v2_1-4_224_pytorch	.073
209	dinov2_vitl14_reg_lc_featread
210	deepeisnn_ei_imagenet_resnet18
211	deepeisnn_ei_cifar10_resnet18
212	deepeisnn_ei_cifar10_vgg19
213	yudixie_wbh_object_class_scaling_0415_run_1
214	yudixie_wbh_object_class_scaling_0415_run_2
215	yudixie_wbh_object_class_scaling_0415_run_3
216	yudixie_wbh_object_class_scaling_0415_imagenet
217	yudixie_wbh_object_class_scaling_0415_run_0
218	predictive_coding_pc
219	pr1_stl10_disentangled_alpha04
220	resnet18_fair
221	vit_base_patch16_dinov3-lvd1689m
222	vit_base_patch14_reg4_dinov2-lvd142m
223	vit_base_patch14_dinov2-lvd142m
224	aughost_fair_resnet18
225	compact_resnet50_robust_IT
226	compact_vgg19_IT
227	compact_cornets_IT
228	compact_cornets_V4
229	compact_resnet50_robust_V4
230	compact_vgg19_V4
231	compact_resnet50_IT
232	compact_resnet50_V4
233	ReAlnet10_ALL
234	ReAlnet09_ALL
235	ReAlnet08_ALL
236	ReAlnet07_ALL
237	ReAlnet05_ALL
238	ReAlnet04_ALL
239	ReAlnet03_ALL
240	ReAlnet02_ALL
241	ReAlnet01_ALL
242	resnet50_primary_visual_cortex
243	yolos_tiny
244	briaai_rmbg_1_4
245	yudixie_resnet50_distance_reg_0_240908
246	yudixie_resnet50_category_class_0_240908
247	yudixie_resnet50_cat_obj_class_all_latents_0_240908
248	yudixie_resnet50_object_class_0_240908
249	yudixie_resnet50_distance_translation_rotation_0_240908
250	yudixie_resnet50_random_0_240908
251	yudixie_resnet50_imagenet1kpret_0_240908
252	ReAlnet10_cornet
253	ReAlnet09_cornet
254	ReAlnet06_cornet
255	ReAlnet05_cornet
256	ReAlnet04_cornet
257	ReAlnet02_cornet
258	ReAlnet03_cornet
259	ReAlnet01_cornet
260	yudixie_resnet50_translation_rotation_0_240908
261	yudixie_resnet50_distance_translation_0_240908
262	yudixie_resnet50_rotation_reg_0_240908
263	yudixie_resnet50_translation_reg_0_240908
264	yudixie_resnet50_distance_rotation_0_240908
265	resnet50-vicreg
266	efficientnet-b7
267	resnet-18_test_m
268	omnivore_swinS
269	VOneCORnet-S
270	omnivore_swinB
271	yudixie_resnet18_distance_reg_0_240719
272	yudixie_resnet18_translation_reg_0_240719
273	yudixie_resnet18_imagenet1kpret_0_240719
274	yudixie_resnet18_rotation_reg_0_240719
275	yudixie_resnet18_object_class_0_240719
276	yudixie_resnet18_distance_translation_rotation_0_240719
277	yudixie_resnet18_cat_obj_class_all_latents_0_240719
278	yudixie_resnet18_random_0_240719
279	yudixie_resnet18_category_class_0_240719
280	yudixie_resnet18_distance_rotation_0_240719
281	yudixie_resnet18_translation_rotation_0_240719
282	yudixie_resnet18_distance_translation_0_240719
283	resnet152_ecoset_full
284	resnet101_ecoset_full
285	resnet50_ecoset_full
286	resnet34_ecoset_full
287	resnet18_ecoset_full
288	ReAlnet01_cornet_fov16
289	ReAlnet01_cornet_fov12
290	ReAlnet01_cornet_fov4
291	ReAlnet08_cornet
292	ReAlnet07_cornet
293	ReAlnet06_ALL
294	SimVP
295	MIM
296	TAU
297	PredRNN
298	ConvLSTM
299	resnet18_imagenet21kP
300	antialiased-rnext101_32x8d
301	hmax

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: BMD2024.texture_2Behavioral

Metric: accuracy_distance