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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_ewconplus_wzc_seed3_2_323	.989
27	resnet50-vicregl0p9	.988
28	SWSL_resnext101_32x8d	.987
29	mobilenet_v2_0_75_192	.989
30	vit_relpos_base_patch16_clsgap_224:sw_in1k	.988
31	vit_base_patch16_clip_224:openai_ft_in1k	.986
32	resnet50-barlow	.987
33	resnet50-vicregl0p75	.986
34	resnet50_ecoset_full	.987
35	resnet50_linf_8_robust	.987
36	resnet_SIN_IN_FT_IN	.987
37	v1-pyr-nodown	.986
38	resnet50_st_wzc_noseed_2_323	.986
39	ReAlnet06_cornet	.985
40	yudixie_resnet50_object_class_0_240908	.985
41	ReAlnet06	.985
42	resnet50_robust_l2_eps1	.984
43	vgg-16-keras	.984
44	resnet101_ecoset_full	.984
45	inception_v3-tf	.984
46	vit_base_patch14_reg4_dinov2-lvd142m	.984
47	resnet50_st_wzc_seed3_2_323	.983
48	resnet_50_v2	.983
49	alexnet_fov4	.983
50	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.982
51	mobilenet_v2_1_0_192	.982
52	eBarlow_lmda_02_1000ep	.983
53	inception_v2-tf	.982
54	vit_large_patch14_clip_224:openai_ft_in1k	.983
55	hmax	.983
56	VOneCORnet-S	.983
57	resnet34_imagenet_full	.982
58	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.982
59	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.983
60	BiT-M-R50x3	.981
61	aughost_fair_resnet18	.979
62	resnet50-sup	.980
63	alexnet_l2_3_robust	.980
64	ReAlnet01_ALL	.978
65	ReAlnet01_cornet_fov4	.979
66	resnet18_imagenet_full	.980
67	alexnet_linf_8_robust	.980
68	omnivore_swinB	.980
69	resnet_50_v1_spiking_l3	.978
70	ReAlnet02	.979
71	yudixie_resnet50_imagenet1kpret_0_240908	.978
72	resnet_50_v1_spiking_l4a	.978
73	resnet_101_v2	.979
74	resnet_50_v1	.979
75	ReAlnet02_cornet	.979
76	compact_vgg19_V4	.979
77	resnet_50_v1_spiking_l4	.979
78	resnet50_tutorial	.977
79	resnet_50_v1_spiking	.978
80	yudixie_resnet50_rotation_reg_0_240908	.978
81	alexnet_robust_correct	.976
82	antialias-resnet152	.977
83	alexnet_fov12	.977
84	mobilenet_v2_1_3_224	.977
85	vonegrcnn_47e	.976
86	ReAlnet09_ALL	.977
87	antialiased-rnext101_32x8d	.974
88	inception_v3	.976
89	ReAlnet02_ALL	.976
90	yudixie_wbh_object_class_scaling_0415_run_3	.975
91	ReAlnet10	.975
92	resnet50-moclr8deg	.974
93	convnext_femto_ols:d1_in1k	.974
94	ReAlnet10_cornet	.975
95	resnet101	.972
96	resnet-18-LC_w_sh_1_iter_m	.973
97	cvt_cvt-21-224-in1k_4_LucyV4	.974
98	resnet50_linf_4_robust	.973
99	resnet152_ecoset_full	.973
100	cvt_cvt-13-384-in1k_4_LucyV4	.972
101	CLIP_ViT-B_32	.973
102	resnet-101_v1-tf	.972
103	omnivore_swinS	.973
104	cvt_cvt-13-224-in1k_4_LucyV4	.971
105	alexnet_random_l2_3_perturb	.972
106	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.970
107	ReAlnet01_cornet	.971
108	convnext_base_fb_in22k_ft_in1k	.970
109	alexnet_fov16	.972
110	ReAlnet08_ALL	.970
111	resnet50-simclr-vissl	.972
112	ReAlnet01	.970
113	ReAlnet04_ALL	.972
114	ReAlnet04_cornet	.970
115	0.5x_resnet-18	.970
116	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.969
117	ReAlnet04	.971
118	ReAlnet03_cornet	.970
119	resnet50_random_l2_perturb	.969
120	ReAlnet10_ALL	.970
121	ReAlnet03	.969
122	resnet101_imagenet_full	.968
123	mobilenet_v2_1_4_224	.969
124	vit_large_patch14_clip_336:laion2b_ft_in1k	.967
125	barlow-twins-resnet50	.967
126	convnext_base_imagenet_full_seed-0	.968
127	resnet50_ewconplus_wzc_seed2_2__323	.968
128	vonegrcnn_52e_full	.968
129	ReAlnet09	.967
130	resnet50_l2_3_robust	.967
131	deit_base_imagenet_full_seed-0	.967
132	resnet50_st_wzc_2_323	.965
133	resnet50-meshes-lt-100-original-scratch	.966
134	ReAlnet09_cornet	.965
135	ReAlnet05_ALL	.966
136	resnet50_st_wzc_seed5_2_323	.967
137	densenet-201	.965
138	CLIP-RN50	.965
139	resnet-50_v2-tf	.966
140	alexnet_early_checkpoint	.966
141	resnet50_st_wzc_seed4_2_323	.964
142	AlexNet_SIN	.965
143	resnet50-vitoimagevidnet8	.964
144	resnet-50_v1-tf	.964
145	resnet50_byol	.965
146	vision_transformer_vit_large_patch16_224	.963
147	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.963
148	convnext_base:clip_laiona_augreg_ft_in1k_384	.963
149	ReAlnet07	.964
150	ReAlnet03_ALL	.964
151	r3m_resnet34_nocrop	.963
152	ReAlnet07_ALL	.963
153	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.963
154	ReAlnet07_cornet	.963
155	vonegrcnn_62e_nobn	.963
156	vonealexnet_gaussian_noise_std4_fixed	.963
157	CORnet-S	.962
158	vgg-19-keras	.963
159	ReAlnet05	.963
160	ReAlnet05_cornet	.963
161	resnet-18-LC_w_sh_1_iter_conv_init_m	.962
162	ReAlnet06_ALL	.959
163	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.960
164	ReAlnet08_cornet	.960
165	mobilenet_v2_1_0_224	.961
166	ReAlnet08	.960
167	imagenet_l2_3_0	.960
168	efficientnet_b1_imagenet_full	.959
169	BiT-S-R101x1	.959
170	resnet-101_v2-tf	.960
171	cvt_cvt-21-384-in1k_4_LucyV4	.960
172	grcnn_robust_v1	.958
173	resnet50_st_wzc_2	.959
174	resnet152_imagenet_full	.959
175	BiT-S-R50x1	.957
176	compact_cornets_V4	.957
177	yudixie_wbh_object_class_scaling_0415_run_1	.957
178	grcnn_v2_text_noise	.956
179	resnet-18_test_m	.956
180	resnet34_ecoset_full	.956
181	FrankRobWobv0	.954
182	resnext101_32x8d_wsl	.955
183	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.955
184	resnet50_moco_v2	.954
185	mobilenet_v2_0_75_160	.954
186	BiT-S-R50x3	.955
187	CORnet-Z	.954
188	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.954
189	BiT-S-R152x2	.953
190	omnivore_swinT	.954
191	cornet_s	.952
192	yudixie_wbh_object_class_scaling_0415_run_0	.952
193	AdvProp_efficientnet-b7	.951
194	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.951
195	yudixie_resnet50_translation_reg_0_240908	.951
196	deit3_base_patch16_224_fb_in22k_ft_in1k	.950
197	vgg_16	.950
198	cv_18_dagger_408_pretrained	.950
199	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.951
200	texture_shape_resnet50_trained_on_SIN	.950
201	CLIP_resnet50	.949
202	mobilenet_v2_1.0_192-tf	.948
203	resnet50_ewconplus_wzc	.947
204	convnext_large_imagenet_full_seed-0	.950
205	CLIP_resnet50_float32	.948
206	resnet50_robust_l2_eps3	.949
207	alexnet_reduced_aliasing_early_checkpoint	.947
208	resnet-18-LC_w_sh_100_iter_conv_init_m	.948
209	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.947
210	AdvProp_efficientnet-b8	.946
211	convnext_large:fb_in22k_ft_in1k	.947
212	densenet-169	.945
213	ViT_L_32_imagenet1k	.945
214	resnet50_ewconplus_wzc_2_323	.943
215	yudixie_resnet18_imagenet1kpret_0_240719	.943
216	blt_vs	.943
217	yudixie_wbh_object_class_scaling_0415_imagenet	.943
218	custom_model_cv_18_dagger_408	.943
219	inception_resnet_v2	.941
220	yudixie_resnet18_translation_rotation_0_240719	.941
221	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.940
222	effnetv2m_custom384	.939
223	deepeisnn_ei_imagenet_resnet18	.940
224	resnet50_primary_visual_cortex	.940
225	resnet-152_v2-tf	.940
226	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.938
227	BiT-S-R152x4	.938
228	alexnet_training_seed_09	.938
229	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.939
230	deit3_base_patch16_224_fb_in1k	.938
231	resnet50_ewconplus_wzc_seed6_2_323	.939
232	resnet50_imagenet_100_seed-0	.938
233	BiT-S-R101x3	.938
234	yudixie_resnet50_distance_reg_0_240908	.936
235	mobilenet_v2_1.3_224-tf	.935
236	resnet50_simclr	.935
237	ReAlnet01_cornet_fov12	.934
238	densenet-121-keras	.934
239	resnet50_FractalDB	.934
240	resnet50_imagenet_full	.933
241	grcnn	.933
242	grcnn_109	.933
243	resnet50_ewconplus_wzc_seed7_2_323	.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	convnext_small_imagenet_10_seed-0	.918
277	efficientnet_b0_imagenet_full	.918
278	yudixie_resnet18_translation_reg_0_240719	.916
279	BiT-M-R101x1	.917
280	ReAlnet01_cornet_fov16	.915
281	alexnet_random_linf8_perturb	.916
282	yudixie_wbh_object_class_scaling_0415_run_2	.915
283	resnet50-VITO-8deg-cc	.913
284	resnet18_fair	.914
285	densenet-121	.913
286	compact_resnet50_V4	.910
287	nasnet_mobile	.911
288	Res2Net50_26w_4s	.911
289	resnet-18-LC_m	.911
290	convnext_tiny:in12k_ft_in1k	.910
291	mobilenet_v2_0_5_192	.908
292	AdvProp_efficientnet-b6	.907
293	resnet-50_untrained	.907
294	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.905
295	mobilenet_v2_1.0_160-tf	.905
296	alexnet_training_seed_05	.904
297	convnext_base_fb_in1k_gram_aligned_dinov3	.903
298	compact_cornets_IT	.901
299	0.5x_resnet-18_LC	.901
300	mobilenet_v2_1_0_160	.900
301	resnet50-cifar	.900
302	resnet-18-LC_untrained	.899
303	convnext_small_imagenet_full_seed-0	.899
304	resnet-152_v1-tf	.897
305	resnet-18-LC_w_sh_100_iter_m	.896
306	focalnet_tiny_lrf_in1k	.895
307	inception_v1-tf	.894
308	efficientnet_b0	.893
309	resnet-18-LC_conv_init_m	.893
310	yolos_tiny	.894
311	AlexNet_SIN_fov4	.892
312	BiT-M-R152x4	.892
313	resnet50_ewconplus_wzc_seed5_2__323	.892
314	resnet-18-LC_w_sh_10_iter_m	.891
315	resnet-18_untrained	.890
316	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.891
317	vggface	.889
318	ViT-B/32	.886
319	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.885
320	CORnetZ_CIFAR10_bs32_20_04	.885
321	convnext_base_fb_in1k	.885
322	resnet50_ewconplus_noseed_2_323	.885
323	efficientnet-b7	.884
324	CORnetZ_CIFAR10	.883
325	artResNet18_1	.882
326	r3m_resnet34	.882
327	shufflenet_v2_x1_0	.880
328	yudixie_resnet18_category_class_0_240719	.879
329	mobilenet_v2_0.35_224	.877
330	r3m_resnet18	.876
331	yudixie_resnet50_distance_translation_rotation_0_240908	.874
332	resnet50_ewconplus_wzc_seed4_2_323	.872
333	yudixie_resnet18_rotation_reg_0_240719	.872
334	resnet-18-LC_1st_conv_m	.868
335	mobilenet_v2_1-4_224_pytorch	.867
336	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.868
337	resnet50	.867
338	resnet18_imagenet21kP	.868
339	yudixie_resnet50_category_class_0_240908	.859
340	mobilenet_v2_0_5_224	.857
341	mobilenet_v2_1.0_224-tf	.852
342	yudixie_resnet18_object_class_0_240719	.850
343	yudixie_resnet18_distance_reg_0_240719	.849
344	deepeisnn_ei_cifar10_vgg19	.848
345	mobilenet_v2_1.4_224-tf	.848
346	vit_base_patch14_dinov2-lvd142m	.844
347	efficientnet_b2_imagenet_full	.839
348	vit_base_patch16_dinov3-lvd1689m	.837
349	briaai_rmbg_1_4	.833
350	resnet-152_v2_pytorch	.832
351	mobilenet_v2_1.0_128-tf	.831
352	BiT-M-R152x2	.831
353	resnet-50x2_untrained	.832
354	alexnet_training_seed_04	.828
355	yudixie_resnet18_distance_rotation_0_240719	.822
356	alexnet_training_seed_01	.821
357	compact_resnet50_robust_V4	.815
358	compact_resnet50_IT	.815
359	mobilenet_v2_1_0_128	.813
360	alexnet_training_seed_07	.812
361	mobilenet_v1_0.25_128	.812
362	yudixie_resnet18_random_0_240719	.809
363	r3m_resnet50_nocrop	.808
364	compact_vgg19_IT	.804
365	mobilenet_v2_0.5_224-tf	.803
366	r3m_resnet50	.803
367	alexnet_training_seed_08	.801
368	compact_resnet50_robust_IT	.800
369	alexnet_training_seed_01_fov12	.796
370	0.5x_resnet-18_LC_w_sh_100_iter	.793
371	resnet50_imagenet_10_seed-0	.786
372	mobilevit_small	.786
373	alexnet_training_seed_10	.786
374	convnext_tiny_sup	.784
375	AdvProp_efficientnet-b4	.780
376	convnext_tiny_imagenet_full_seed-0	.778
377	mobilenet_v2_0.5_192-tf	.774
378	yudixie_resnet18_distance_translation_rotation_0_240719	.771
379	deit_large_imagenet_full_seed-0	.769
380	AdvProp_efficientnet-b0	.768
381	resnet50-meshes-lt-100-original-pretrained	.752
382	mobilenet_v2_0.75_96	.745
383	resnet50_imagenet_1_seed-0	.735
384	resnet50_pretrained_with_retinal_waves	.731
385	deepeisnn_ei_cifar10_resnet18	.726
386	mobilenet_v2_0.75_192-tf	.724
387	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.721
388	mobilenet_v2_1.0_96	.720
389	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.720
390	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.720
391	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.719
392	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.719
393	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.716
394	mobilenet_v2_0.75_128	.713
395	AT_efficientnet-b2	.697
396	mobilenet_v2_0.75_224-tf	.697
397	AdvProp_efficientnet-b2	.695
398	AlexNet_SIN_fov16	.686
399	mobilenet_v2_0.5_160	.677
400	my-model	.674
401	alexnet_training_seed_03	.674
402	alexnet_training_seed_06	.649
403	alexnet_training_seed_01_fov16	.635
404	alexnet_training_seed_01_fov4	.391
405	deit_small_imagenet_10_seed-0	.355
406	deit_small_imagenet_full_seed-0	.354
407	mobilenet_v2_0.75_160-tf	.064
408	mobilenet_v2_0.5_128	.000
409	mobilenet_v2_0.35_160
410	resnet18-supervised
411	fitvid_trained_on_physion
412	openclip
413	resnext101_32x32d_wsl
414	resnext101_32x48d_wsl
415	resnet50_ImageNet
416	regnet_y_400mf
417	tv_efficientnet-b1
418	alexnet_ks_torevert
419	yudixie_resnet50_imagenet1kpret_0_240312
420	resnet_152_v1
421	resnext101_32x16d_wsl
422	densenet_201_pytorch
423	pnasnet_large_pytorch
424	inception_v3_pytorch
425	inception_v4
426	deit_small_imagenet_1_seed-0
427	nasnet_large
428	pnasnet_large
429	vonegrcnn_62e_nobn
430	vonegrcnn_47e
431	resnet_152_v2
432	pr1_stl10_disentangled_alpha04
433	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or