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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Marques2020_DeValois1982-pref_or")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50-SIN_IN	1.0
2	nasnet_large-tf	.998
3	resnet-18-LC_w_sh_10_iter_conv_init_m	.997
4	imagenet_l2_10_0	.997
5	resnet50-vicreg	.997
6	resnet50	.996
7	vgg_19	.995
8	inception_v4-tf	.996
9	antialiased-r50	.995
10	resnet50_st_wzc_seed7_2_323	.995
11	SWSL_resnet50	.995
12	pnasnet_large_halfPrecision	.995
13	resnet50_st_wzc_seed6_2_323	.994
14	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.993
15	resnet18_ecoset_full	.992
16	AlexNet_SIN_fov12	.993
17	resnet50_random_linf8_perturb	.992
18	voneresnet-50-robust	.991
19	deit_small_imagenet_100_seed-0	.991
20	vit_large_patch14_clip_224:laion2b_ft_in1k	.991
21	voneresnet-50	.990
22	voneresnet-50-non_stochastic	.991
23	pnasnet_large-tf	.989
24	inception_v1	.989
25	resnet-50-robust	.988
26	resnet50-vicregl0p9	.988
27	SWSL_resnext101_32x8d	.987
28	mobilenet_v2_0_75_192	.989
29	vit_relpos_base_patch16_clsgap_224:sw_in1k	.988
30	vit_base_patch16_clip_224:openai_ft_in1k	.986
31	resnet50-barlow	.987
32	resnet50-vicregl0p75	.986
33	resnet50_ecoset_full	.987
34	resnet50_linf_8_robust	.987
35	resnet_SIN_IN_FT_IN	.987
36	v1-pyr-nodown	.986
37	ReAlnet06_cornet	.985
38	yudixie_resnet50_object_class_0_240908	.985
39	ReAlnet06	.985
40	resnet50_robust_l2_eps1	.984
41	vgg-16-keras	.984
42	resnet101_ecoset_full	.984
43	inception_v3-tf	.984
44	vit_base_patch14_reg4_dinov2-lvd142m	.984
45	resnet50_st_wzc_seed3_2_323	.983
46	resnet_50_v2	.983
47	alexnet_fov4	.983
48	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.982
49	mobilenet_v2_1_0_192	.982
50	eBarlow_lmda_02_1000ep	.983
51	inception_v2-tf	.982
52	vit_large_patch14_clip_224:openai_ft_in1k	.983
53	hmax	.983
54	VOneCORnet-S	.983
55	resnet34_imagenet_full	.982
56	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.982
57	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.983
58	BiT-M-R50x3	.981
59	resnet50-sup	.980
60	alexnet_l2_3_robust	.980
61	ReAlnet01_ALL	.978
62	ReAlnet01_cornet_fov4	.979
63	resnet18_imagenet_full	.980
64	alexnet_linf_8_robust	.980
65	omnivore_swinB	.980
66	resnet_50_v1_spiking_l3	.978
67	ReAlnet02	.979
68	yudixie_resnet50_imagenet1kpret_0_240908	.978
69	resnet_50_v1_spiking_l4a	.978
70	resnet_101_v2	.979
71	resnet_50_v1	.979
72	ReAlnet02_cornet	.979
73	compact_vgg19_V4	.979
74	resnet_50_v1_spiking_l4	.979
75	resnet50_tutorial	.977
76	resnet_50_v1_spiking	.978
77	yudixie_resnet50_rotation_reg_0_240908	.978
78	alexnet_robust_correct	.976
79	antialias-resnet152	.977
80	alexnet_fov12	.977
81	mobilenet_v2_1_3_224	.977
82	vonegrcnn_47e	.976
83	ReAlnet09_ALL	.977
84	antialiased-rnext101_32x8d	.974
85	inception_v3	.976
86	ReAlnet02_ALL	.976
87	yudixie_wbh_object_class_scaling_0415_run_3	.975
88	ReAlnet10	.975
89	resnet50-moclr8deg	.974
90	vit_large_clip336_openai	.974
91	convnext_femto_ols:d1_in1k	.974
92	ReAlnet10_cornet	.975
93	resnet101	.972
94	resnet-18-LC_w_sh_1_iter_m	.973
95	cvt_cvt-21-224-in1k_4_LucyV4	.974
96	resnet50_linf_4_robust	.973
97	resnet152_ecoset_full	.973
98	cvt_cvt-13-384-in1k_4_LucyV4	.972
99	CLIP_ViT-B_32	.973
100	resnet-101_v1-tf	.972
101	omnivore_swinS	.973
102	cvt_cvt-13-224-in1k_4_LucyV4	.971
103	alexnet_random_l2_3_perturb	.972
104	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.970
105	ReAlnet01_cornet	.971
106	convnext_base_fb_in22k_ft_in1k	.970
107	alexnet_fov16	.972
108	ReAlnet08_ALL	.970
109	resnet50-simclr-vissl	.972
110	ReAlnet01	.970
111	ReAlnet04_ALL	.972
112	ReAlnet04_cornet	.970
113	0.5x_resnet-18	.970
114	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.969
115	ReAlnet04	.971
116	ReAlnet03_cornet	.970
117	resnet50_random_l2_perturb	.969
118	ReAlnet10_ALL	.970
119	ReAlnet03	.969
120	resnet101_imagenet_full	.968
121	mobilenet_v2_1_4_224	.969
122	vit_large_patch14_clip_336:laion2b_ft_in1k	.967
123	barlow-twins-resnet50	.967
124	convnext_base_imagenet_full_seed-0	.968
125	resnet50_ewconplus_wzc_seed2_2__323	.968
126	vonegrcnn_52e_full	.968
127	ReAlnet09	.967
128	resnet50_l2_3_robust	.967
129	deit_base_imagenet_full_seed-0	.967
130	ReAlnet09_cornet	.965
131	ReAlnet05_ALL	.966
132	densenet-201	.965
133	CLIP-RN50	.965
134	resnet-50_v2-tf	.966
135	alexnet_early_checkpoint	.966
136	AlexNet_SIN	.965
137	resnet50-vitoimagevidnet8	.964
138	resnet-50_v1-tf	.964
139	resnet50_byol	.965
140	vision_transformer_vit_large_patch16_224	.963
141	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.963
142	convnext_base:clip_laiona_augreg_ft_in1k_384	.963
143	ReAlnet07	.964
144	ReAlnet03_ALL	.964
145	r3m_resnet34_nocrop	.963
146	ReAlnet07_ALL	.963
147	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.963
148	ReAlnet07_cornet	.963
149	vonegrcnn_62e_nobn	.963
150	vonealexnet_gaussian_noise_std4_fixed	.963
151	CORnet-S	.962
152	vgg-19-keras	.963
153	ReAlnet05	.963
154	ReAlnet05_cornet	.963
155	resnet-18-LC_w_sh_1_iter_conv_init_m	.962
156	dinov2_vitl14_lc_res336	.961
157	ReAlnet06_ALL	.959
158	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.960
159	ReAlnet08_cornet	.960
160	mobilenet_v2_1_0_224	.961
161	ReAlnet08	.960
162	imagenet_l2_3_0	.960
163	efficientnet_b1_imagenet_full	.959
164	BiT-S-R101x1	.959
165	resnet-101_v2-tf	.960
166	cvt_cvt-21-384-in1k_4_LucyV4	.960
167	grcnn_robust_v1	.958
168	resnet50_st_wzc_2	.959
169	resnet152_imagenet_full	.959
170	dinov2_vitl14_lc	.958
171	BiT-S-R50x1	.957
172	compact_cornets_V4	.957
173	yudixie_wbh_object_class_scaling_0415_run_1	.957
174	convnext_large_in22k_supervised	.957
175	grcnn_v2_text_noise	.956
176	resnet-18_test_m	.956
177	resnet34_ecoset_full	.956
178	FrankRobWobv0	.954
179	resnext101_32x8d_wsl	.955
180	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.955
181	resnet50_moco_v2	.954
182	mobilenet_v2_0_75_160	.954
183	BiT-S-R50x3	.955
184	CORnet-Z	.954
185	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.954
186	BiT-S-R152x2	.953
187	omnivore_swinT	.954
188	cornet_s	.952
189	yudixie_wbh_object_class_scaling_0415_run_0	.952
190	AdvProp_efficientnet-b7	.951
191	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.951
192	yudixie_resnet50_translation_reg_0_240908	.951
193	deit3_base_patch16_224_fb_in22k_ft_in1k	.950
194	vgg_16	.950
195	cv_18_dagger_408_pretrained	.950
196	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.951
197	convnext_large_clip_laion2b_finelayers	.949
198	texture_shape_resnet50_trained_on_SIN	.950
199	CLIP_resnet50	.949
200	mobilenet_v2_1.0_192-tf	.948
201	resnet50_ewconplus_wzc	.947
202	convnext_large_imagenet_full_seed-0	.950
203	dinov2_vitl14_reg_lc	.948
204	CLIP_resnet50_float32	.948
205	resnet50_robust_l2_eps3	.949
206	alexnet_reduced_aliasing_early_checkpoint	.947
207	resnet-18-LC_w_sh_100_iter_conv_init_m	.948
208	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.947
209	dinov2_vitl14_reg_lc_featread	.947
210	AdvProp_efficientnet-b8	.946
211	convnext_large:fb_in22k_ft_in1k	.947
212	densenet-169	.945
213	dinov2_vitg14_lc	.945
214	ViT_L_32_imagenet1k	.945
215	resnet50_hvs_wzc	.946
216	yudixie_resnet18_imagenet1kpret_0_240719	.943
217	blt_vs	.943
218	yudixie_wbh_object_class_scaling_0415_imagenet	.943
219	custom_model_cv_18_dagger_408	.943
220	inception_resnet_v2	.941
221	yudixie_resnet18_translation_rotation_0_240719	.941
222	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.940
223	effnetv2m_custom384	.939
224	deepeisnn_ei_imagenet_resnet18	.940
225	resnet50_primary_visual_cortex	.940
226	resnet-152_v2-tf	.940
227	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.938
228	BiT-S-R152x4	.938
229	alexnet_training_seed_09	.938
230	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.939
231	deit3_base_patch16_224_fb_in1k	.938
232	resnet50_ewconplus_wzc_seed6_2_323	.939
233	resnet50_imagenet_100_seed-0	.938
234	BiT-S-R101x3	.938
235	yudixie_resnet50_distance_reg_0_240908	.936
236	mobilenet_v2_1.3_224-tf	.935
237	resnet50_simclr	.935
238	ReAlnet01_cornet_fov12	.934
239	densenet-121-keras	.934
240	resnet50_FractalDB	.934
241	resnet50_imagenet_full	.933
242	grcnn	.933
243	grcnn_109	.933
244	yudixie_resnet50_random_0_240908	.932
245	convnext_small_imagenet_100_seed-0	.932
246	nasnet_mobile-tf	.931
247	alexnet	.932
248	resnet_101_v1	.931
249	vonegrcnn_52e_full	.930
250	densenet-169-keras	.931
251	texture_shape_alexnet_trained_on_SIN	.930
252	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.931
253	yudixie_resnet50_distance_rotation_0_240908	.930
254	effnetb1_272x240	.930
255	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.930
256	mobilenet_v2_0_75_224	.929
257	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.928
258	convnext_small_imagenet_1_seed-0	.928
259	0.5x_resnet-18_LC_w_sh_10_iter	.928
260	konkle_alexnetgn_ipcl_ref01_primary_model	.927
261	yudixie_resnet50_distance_translation_0_240908	.927
262	xception	.926
263	resnet50-SIN_IN_IN	.927
264	resnet-18-LC_d_w_sh_1x1_conv_init_m	.925
265	BiT-M-R101x3	.925
266	BiT-M-R50x1	.924
267	convnext_xlarge:fb_in22k_ft_in1k	.923
268	densenet-201-keras	.923
269	RN50	.923
270	my-model	.922
271	0.5x_resnet-18_LC_w_sh_1_iter	.921
272	alexnet_training_seed_02	.921
273	yudixie_resnet50_translation_rotation_0_240908	.922
274	yudixie_resnet18_distance_translation_0_240719	.921
275	resnet50-SIN	.921
276	regnety_032	.919
277	convnext_small_imagenet_10_seed-0	.918
278	efficientnet_b0_imagenet_full	.918
279	yudixie_resnet18_translation_reg_0_240719	.916
280	BiT-M-R101x1	.917
281	ReAlnet01_cornet_fov16	.915
282	alexnet_random_linf8_perturb	.916
283	yudixie_wbh_object_class_scaling_0415_run_2	.915
284	resnet50-VITO-8deg-cc	.913
285	resnet18_fair	.914
286	densenet-121	.913
287	compact_resnet50_V4	.910
288	nasnet_mobile	.911
289	Res2Net50_26w_4s	.911
290	resnet-18-LC_m	.911
291	convnext_tiny:in12k_ft_in1k	.910
292	mobilenet_v2_0_5_192	.908
293	AdvProp_efficientnet-b6	.907
294	resnet-50_untrained	.907
295	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.905
296	mobilenet_v2_1.0_160-tf	.905
297	alexnet_training_seed_05	.904
298	convnext_base_fb_in1k_gram_aligned_dinov3	.903
299	compact_cornets_IT	.901
300	0.5x_resnet-18_LC	.901
301	mobilenet_v2_1_0_160	.900
302	resnet50-cifar	.900
303	resnet-18-LC_untrained	.899
304	convnext_small_imagenet_full_seed-0	.899
305	seresnext50_32x4d	.898
306	resnet-152_v1-tf	.897
307	resnet-18-LC_w_sh_100_iter_m	.896
308	focalnet_tiny_lrf_in1k	.895
309	convnext_xxlarge_clip	.896
310	inception_v1-tf	.894
311	efficientnet_b0	.893
312	resnet-18-LC_conv_init_m	.893
313	yolos_tiny	.894
314	AlexNet_SIN_fov4	.892
315	BiT-M-R152x4	.892
316	resnet50_ewconplus_wzc_seed5_2__323	.892
317	resnet-18-LC_w_sh_10_iter_m	.891
318	resnet-18_untrained	.890
319	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.891
320	eicircuit_resnet18_bn_20260919	.889
321	vggface	.889
322	ViT-B/32	.886
323	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.885
324	CORnetZ_CIFAR10_bs32_20_04	.885
325	convnext_base_fb_in1k	.885
326	efficientnet-b7	.884
327	CORnetZ_CIFAR10	.883
328	artResNet18_1	.882
329	r3m_resnet34	.882
330	shufflenet_v2_x1_0	.880
331	yudixie_resnet18_category_class_0_240719	.879
332	mobilenet_v2_0.35_224	.877
333	r3m_resnet18	.876
334	yudixie_resnet50_distance_translation_rotation_0_240908	.874
335	yudixie_resnet18_rotation_reg_0_240719	.872
336	resnet-18-LC_1st_conv_m	.868
337	mobilenet_v2_1-4_224_pytorch	.867
338	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.868
339	resnet18_imagenet21kP	.868
340	gabor_filter_entropy_4x4_v2	.865
341	yudixie_resnet50_category_class_0_240908	.859
342	mobilenet_v2_0_5_224	.857
343	gabor_filter_mean_abs_4x4_v2	.855
344	mobilenet_v2_1.0_224-tf	.852
345	yudixie_resnet18_object_class_0_240719	.850
346	yudixie_resnet18_distance_reg_0_240719	.849
347	deepeisnn_ei_cifar10_vgg19	.848
348	mobilenet_v2_1.4_224-tf	.848
349	vit_base_patch14_dinov2-lvd142m	.844
350	efficientnet_b2_imagenet_full	.839
351	vit_base_patch16_dinov3-lvd1689m	.837
352	briaai_rmbg_1_4	.833
353	resnet-152_v2_pytorch	.832
354	mobilenet_v2_1.0_128-tf	.831
355	BiT-M-R152x2	.831
356	resnet-50x2_untrained	.832
357	alexnet_training_seed_04	.828
358	yudixie_resnet18_distance_rotation_0_240719	.822
359	alexnet_training_seed_01	.821
360	compact_resnet50_robust_V4	.815
361	compact_resnet50_IT	.815
362	mobilenet_v2_1_0_128	.813
363	alexnet_training_seed_07	.812
364	mobilenet_v1_0.25_128	.812
365	yudixie_resnet18_random_0_240719	.809
366	r3m_resnet50_nocrop	.808
367	compact_vgg19_IT	.804
368	mobilenet_v2_0.5_224-tf	.803
369	r3m_resnet50	.803
370	alexnet_training_seed_08	.801
371	compact_resnet50_robust_IT	.800
372	alexnet_training_seed_01_fov12	.796
373	0.5x_resnet-18_LC_w_sh_100_iter	.793
374	resnet50_imagenet_10_seed-0	.786
375	mobilevit_small	.786
376	alexnet_training_seed_10	.786
377	convnext_tiny_sup	.784
378	AdvProp_efficientnet-b4	.780
379	convnext_tiny_imagenet_full_seed-0	.778
380	mobilenet_v2_0.5_192-tf	.774
381	yudixie_resnet18_distance_translation_rotation_0_240719	.771
382	deit_large_imagenet_full_seed-0	.769
383	AdvProp_efficientnet-b0	.768
384	mobilenet_v2_0.75_96	.745
385	resnet50_imagenet_1_seed-0	.735
386	resnet50_pretrained_with_retinal_waves	.731
387	deepeisnn_ei_cifar10_resnet18	.726
388	mobilenet_v2_0.75_192-tf	.724
389	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.721
390	mobilenet_v2_1.0_96	.720
391	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.720
392	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.720
393	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.719
394	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.719
395	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.716
396	mobilenet_v2_0.75_128	.713
397	AT_efficientnet-b2	.697
398	mobilenet_v2_0.75_224-tf	.697
399	AdvProp_efficientnet-b2	.695
400	AlexNet_SIN_fov16	.686
401	mobilenet_v2_0.5_160	.677
402	my-model	.674
403	alexnet_training_seed_03	.674
404	alexnet_training_seed_06	.649
405	gabor_filter_entropy_4x4	.646
406	alexnet_training_seed_01_fov16	.635
407	gabor_filter_entropy_4x4_v2_forcedCosine	.597
408	alexnet_training_seed_01_fov4	.391
409	deit_small_imagenet_10_seed-0	.355
410	deit_small_imagenet_full_seed-0	.354
411	mobilenet_v2_0.75_160-tf	.064
412	mobilenet_v2_0.5_128	.000
413	mobilenet_v2_0.35_160
414	resnet18-supervised
415	fitvid_trained_on_physion
416	openclip
417	resnext101_32x32d_wsl
418	resnext101_32x48d_wsl
419	resnet50_ImageNet
420	regnet_y_400mf
421	tv_efficientnet-b1
422	alexnet_ks_torevert
423	yudixie_resnet50_imagenet1kpret_0_240312
424	resnet_152_v1
425	resnext101_32x16d_wsl
426	densenet_201_pytorch
427	pnasnet_large_pytorch
428	inception_v3_pytorch
429	inception_v4
430	deit_small_imagenet_1_seed-0
431	nasnet_large
432	pnasnet_large
433	vonegrcnn_62e_nobn
434	vonegrcnn_47e
435	resnet_152_v2
436	pr1_stl10_disentangled_alpha04
437	predictive_coding_pc
438	dinov2_vitg14_reg_lc
439	eva02_large_in22k
440	vit_huge_clip336_laion

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or