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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	resnet50_simsiam_linhead	1.0
3	nasnet_large-tf	.998
4	resnet-18-LC_w_sh_10_iter_conv_init_m	.997
5	imagenet_l2_10_0	.997
6	resnet50-vicreg	.997
7	resnet50	.996
8	vgg_19	.995
9	inception_v4-tf	.996
10	antialiased-r50	.995
11	resnet50_st_wzc_seed7_2_323	.995
12	SWSL_resnet50	.995
13	pnasnet_large_halfPrecision	.995
14	resnet50_st_wzc_seed6_2_323	.994
15	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.993
16	resnet18_ecoset_full	.992
17	AlexNet_SIN_fov12	.993
18	resnet50_random_linf8_perturb	.992
19	voneresnet-50-robust	.991
20	resnet50_vicreg_linhead	.991
21	deit_small_imagenet_100_seed-0	.991
22	vit_large_patch14_clip_224:laion2b_ft_in1k	.991
23	voneresnet-50	.990
24	voneresnet-50-non_stochastic	.991
25	pnasnet_large-tf	.989
26	inception_v1	.989
27	resnet-50-robust	.988
28	resnet50-vicregl0p9	.988
29	SWSL_resnext101_32x8d	.987
30	mobilenet_v2_0_75_192	.989
31	vit_relpos_base_patch16_clsgap_224:sw_in1k	.988
32	vit_base_patch16_clip_224:openai_ft_in1k	.986
33	resnet50-barlow	.987
34	resnet50-vicregl0p75	.986
35	resnet50_ecoset_full	.987
36	resnet50_linf_8_robust	.987
37	resnet_SIN_IN_FT_IN	.987
38	resnext101_32x16d_wsl	.986
39	v1-pyr-nodown	.986
40	ReAlnet06_cornet	.985
41	yudixie_resnet50_object_class_0_240908	.985
42	ReAlnet06	.985
43	resnet50_robust_l2_eps1	.984
44	vgg-16-keras	.984
45	resnet101_ecoset_full	.984
46	inception_v3-tf	.984
47	vit_base_patch14_reg4_dinov2-lvd142m	.984
48	resnet50_st_wzc_seed3_2_323	.983
49	resnet_50_v2	.983
50	alexnet_fov4	.983
51	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.982
52	mobilenet_v2_1_0_192	.982
53	eBarlow_lmda_02_1000ep	.983
54	inception_v2-tf	.982
55	vit_large_patch14_clip_224:openai_ft_in1k	.983
56	hmax	.983
57	VOneCORnet-S	.983
58	resnet34_imagenet_full	.982
59	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.982
60	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.983
61	BiT-M-R50x3	.981
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	vit_large_clip336_openai	.974
94	convnext_femto_ols:d1_in1k	.974
95	ReAlnet10_cornet	.975
96	resnet101	.972
97	resnet-18-LC_w_sh_1_iter_m	.973
98	cvt_cvt-21-224-in1k_4_LucyV4	.974
99	resnet50_linf_4_robust	.973
100	resnet152_ecoset_full	.973
101	cvt_cvt-13-384-in1k_4_LucyV4	.972
102	CLIP_ViT-B_32	.973
103	resnet-101_v1-tf	.972
104	omnivore_swinS	.973
105	cvt_cvt-13-224-in1k_4_LucyV4	.971
106	alexnet_random_l2_3_perturb	.972
107	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.970
108	ReAlnet01_cornet	.971
109	convnext_base_fb_in22k_ft_in1k	.970
110	alexnet_fov16	.972
111	ReAlnet08_ALL	.970
112	resnet50-simclr-vissl	.972
113	ReAlnet01	.970
114	ReAlnet04_ALL	.972
115	ReAlnet04_cornet	.970
116	0.5x_resnet-18	.970
117	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.969
118	ReAlnet04	.971
119	ReAlnet03_cornet	.970
120	resnet50_random_l2_perturb	.969
121	ReAlnet10_ALL	.970
122	ReAlnet03	.969
123	resnet101_imagenet_full	.968
124	mobilenet_v2_1_4_224	.969
125	vit_large_patch14_clip_336:laion2b_ft_in1k	.967
126	resnet50_simclr_linhead_01norm	.969
127	resnext101_32x48d_wsl	.968
128	barlow-twins-resnet50	.967
129	convnext_base_imagenet_full_seed-0	.968
130	resnet50_ewconplus_wzc_seed2_2__323	.968
131	vonegrcnn_52e_full	.968
132	ReAlnet09	.967
133	resnet50_l2_3_robust	.967
134	deit_base_imagenet_full_seed-0	.967
135	ReAlnet09_cornet	.965
136	ijepa_vith14_linhead	.966
137	ReAlnet05_ALL	.966
138	densenet-201	.965
139	CLIP-RN50	.965
140	resnet-50_v2-tf	.966
141	alexnet_early_checkpoint	.966
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	dinov2_vitl14_lc_res336	.961
163	ReAlnet06_ALL	.959
164	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.960
165	ReAlnet08_cornet	.960
166	mobilenet_v2_1_0_224	.961
167	ReAlnet08	.960
168	imagenet_l2_3_0	.960
169	efficientnet_b1_imagenet_full	.959
170	BiT-S-R101x1	.959
171	resnet-101_v2-tf	.960
172	cvt_cvt-21-384-in1k_4_LucyV4	.960
173	grcnn_robust_v1	.958
174	resnet50_st_wzc_2	.959
175	resnet152_imagenet_full	.959
176	dinov2_vitl14_lc	.958
177	BiT-S-R50x1	.957
178	compact_cornets_V4	.957
179	yudixie_wbh_object_class_scaling_0415_run_1	.957
180	convnext_large_in22k_supervised	.957
181	grcnn_v2_text_noise	.956
182	resnet-18_test_m	.956
183	resnet34_ecoset_full	.956
184	FrankRobWobv0	.954
185	mehrer2020_alexnet_training_seed_01_fov12	.955
186	resnext101_32x8d_wsl	.955
187	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.955
188	resnet50_moco_v2	.954
189	mobilenet_v2_0_75_160	.954
190	resnet50_byol_linhead	.956
191	BiT-S-R50x3	.955
192	CORnet-Z	.954
193	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.954
194	BiT-S-R152x2	.953
195	omnivore_swinT	.954
196	cornet_s	.952
197	yudixie_wbh_object_class_scaling_0415_run_0	.952
198	AdvProp_efficientnet-b7	.951
199	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.951
200	yudixie_resnet50_translation_reg_0_240908	.951
201	deit3_base_patch16_224_fb_in22k_ft_in1k	.950
202	vgg_16	.950
203	cv_18_dagger_408_pretrained	.950
204	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.951
205	convnext_large_clip_laion2b_finelayers	.949
206	texture_shape_resnet50_trained_on_SIN	.950
207	CLIP_resnet50	.949
208	mobilenet_v2_1.0_192-tf	.948
209	resnet50_ewconplus_wzc	.947
210	convnext_large_imagenet_full_seed-0	.950
211	dinov2_vitl14_reg_lc	.948
212	CLIP_resnet50_float32	.948
213	resnet50_robust_l2_eps3	.949
214	alexnet_reduced_aliasing_early_checkpoint	.947
215	resnet-18-LC_w_sh_100_iter_conv_init_m	.948
216	resnet50_barlowtwins_linhead	.947
217	resnext101_32x32d_wsl	.946
218	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.947
219	dinov2_vitl14_reg_lc_featread	.947
220	AdvProp_efficientnet-b8	.946
221	convnext_large:fb_in22k_ft_in1k	.947
222	densenet-169	.945
223	dinov2_vitg14_lc	.945
224	ViT_L_32_imagenet1k	.945
225	resnet50_hvs_wzc	.946
226	mehrer2020_alexnet_training_seed_01	.944
227	yudixie_resnet18_imagenet1kpret_0_240719	.943
228	blt_vs	.943
229	yudixie_wbh_object_class_scaling_0415_imagenet	.943
230	custom_model_cv_18_dagger_408	.943
231	inception_resnet_v2	.941
232	yudixie_resnet18_translation_rotation_0_240719	.941
233	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.940
234	effnetv2m_custom384	.939
235	deepeisnn_ei_imagenet_resnet18	.940
236	resnet50_primary_visual_cortex	.940
237	resnet-152_v2-tf	.940
238	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.938
239	BiT-S-R152x4	.938
240	alexnet_training_seed_09	.938
241	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.939
242	deit3_base_patch16_224_fb_in1k	.938
243	resnet50_ewconplus_wzc_seed6_2_323	.939
244	resnet50_imagenet_100_seed-0	.938
245	BiT-S-R101x3	.938
246	yudixie_resnet50_distance_reg_0_240908	.936
247	mobilenet_v2_1.3_224-tf	.935
248	resnet50_simclr	.935
249	ReAlnet01_cornet_fov12	.934
250	densenet-121-keras	.934
251	resnet50_FractalDB	.934
252	resnet50_imagenet_full	.933
253	grcnn	.933
254	grcnn_109	.933
255	yudixie_resnet50_random_0_240908	.932
256	convnext_small_imagenet_100_seed-0	.932
257	nasnet_mobile-tf	.931
258	alexnet	.932
259	resnet_101_v1	.931
260	vonegrcnn_52e_full	.930
261	densenet-169-keras	.931
262	texture_shape_alexnet_trained_on_SIN	.930
263	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.931
264	yudixie_resnet50_distance_rotation_0_240908	.930
265	effnetb1_272x240	.930
266	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.930
267	mobilenet_v2_0_75_224	.929
268	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.928
269	convnext_small_imagenet_1_seed-0	.928
270	0.5x_resnet-18_LC_w_sh_10_iter	.928
271	konkle_alexnetgn_ipcl_ref01_primary_model	.927
272	yudixie_resnet50_distance_translation_0_240908	.927
273	xception	.926
274	resnet50-SIN_IN_IN	.927
275	resnet-18-LC_d_w_sh_1x1_conv_init_m	.925
276	BiT-M-R101x3	.925
277	BiT-M-R50x1	.924
278	convnext_xlarge:fb_in22k_ft_in1k	.923
279	densenet-201-keras	.923
280	RN50	.923
281	my-model	.922
282	0.5x_resnet-18_LC_w_sh_1_iter	.921
283	alexnet_training_seed_02	.921
284	yudixie_resnet50_translation_rotation_0_240908	.922
285	yudixie_resnet18_distance_translation_0_240719	.921
286	resnet50-SIN	.921
287	regnety_032	.919
288	convnext_small_imagenet_10_seed-0	.918
289	efficientnet_b0_imagenet_full	.918
290	yudixie_resnet18_translation_reg_0_240719	.916
291	BiT-M-R101x1	.917
292	ReAlnet01_cornet_fov16	.915
293	alexnet_random_linf8_perturb	.916
294	yudixie_wbh_object_class_scaling_0415_run_2	.915
295	resnet50-VITO-8deg-cc	.913
296	resnet18_fair	.914
297	densenet-121	.913
298	compact_resnet50_V4	.910
299	nasnet_mobile	.911
300	Res2Net50_26w_4s	.911
301	resnet-18-LC_m	.911
302	mehrer2020_alexnet_training_seed_08	.910
303	convnext_tiny:in12k_ft_in1k	.910
304	mobilenet_v2_0_5_192	.908
305	AdvProp_efficientnet-b6	.907
306	resnet-50_untrained	.907
307	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.905
308	mobilenet_v2_1.0_160-tf	.905
309	alexnet_training_seed_05	.904
310	mehrer2020_alexnet_training_seed_02	.904
311	convnext_base_fb_in1k_gram_aligned_dinov3	.903
312	compact_cornets_IT	.901
313	0.5x_resnet-18_LC	.901
314	mobilenet_v2_1_0_160	.900
315	resnet50-cifar	.900
316	resnet-18-LC_untrained	.899
317	convnext_small_imagenet_full_seed-0	.899
318	seresnext50_32x4d	.898
319	mehrer2020_alexnet_training_seed_03	.900
320	resnet-152_v1-tf	.897
321	resnet-18-LC_w_sh_100_iter_m	.896
322	focalnet_tiny_lrf_in1k	.895
323	convnext_xxlarge_clip	.896
324	inception_v1-tf	.894
325	efficientnet_b0	.893
326	resnet-18-LC_conv_init_m	.893
327	yolos_tiny	.894
328	AlexNet_SIN_fov4	.892
329	BiT-M-R152x4	.892
330	resnet50_ewconplus_wzc_seed5_2__323	.892
331	resnet-18-LC_w_sh_10_iter_m	.891
332	resnet-18_untrained	.890
333	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.891
334	eicircuit_resnet18_bn_20260919	.889
335	vggface	.889
336	ViT-B/32	.886
337	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.885
338	CORnetZ_CIFAR10_bs32_20_04	.885
339	convnext_base_fb_in1k	.885
340	efficientnet-b7	.884
341	CORnetZ_CIFAR10	.883
342	artResNet18_1	.882
343	r3m_resnet34	.882
344	shufflenet_v2_x1_0	.880
345	yudixie_resnet18_category_class_0_240719	.879
346	mobilenet_v2_0.35_224	.877
347	r3m_resnet18	.876
348	yudixie_resnet50_distance_translation_rotation_0_240908	.874
349	yudixie_resnet18_rotation_reg_0_240719	.872
350	resnet-18-LC_1st_conv_m	.868
351	mobilenet_v2_1-4_224_pytorch	.867
352	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.868
353	resnet18_imagenet21kP	.868
354	gabor_filter_entropy_4x4_v2	.865
355	yudixie_resnet50_category_class_0_240908	.859
356	mobilenet_v2_0_5_224	.857
357	gabor_filter_mean_abs_4x4_v2	.855
358	mobilenet_v2_1.0_224-tf	.852
359	yudixie_resnet18_object_class_0_240719	.850
360	yudixie_resnet18_distance_reg_0_240719	.849
361	deepeisnn_ei_cifar10_vgg19	.848
362	mobilenet_v2_1.4_224-tf	.848
363	mehrer2020_alexnet_training_seed_09	.845
364	vit_base_patch14_dinov2-lvd142m	.844
365	efficientnet_b2_imagenet_full	.839
366	vit_base_patch16_dinov3-lvd1689m	.837
367	briaai_rmbg_1_4	.833
368	resnet-152_v2_pytorch	.832
369	mobilenet_v2_1.0_128-tf	.831
370	BiT-M-R152x2	.831
371	resnet-50x2_untrained	.832
372	alexnet_training_seed_04	.828
373	yudixie_resnet18_distance_rotation_0_240719	.822
374	alexnet_training_seed_01	.821
375	compact_resnet50_robust_V4	.815
376	compact_resnet50_IT	.815
377	mobilenet_v2_1_0_128	.813
378	alexnet_training_seed_07	.812
379	mobilenet_v1_0.25_128	.812
380	yudixie_resnet18_random_0_240719	.809
381	r3m_resnet50_nocrop	.808
382	compact_vgg19_IT	.804
383	mobilenet_v2_0.5_224-tf	.803
384	r3m_resnet50	.803
385	alexnet_training_seed_08	.801
386	compact_resnet50_robust_IT	.800
387	alexnet_training_seed_01_fov12	.796
388	0.5x_resnet-18_LC_w_sh_100_iter	.793
389	resnet50_imagenet_10_seed-0	.786
390	mobilevit_small	.786
391	alexnet_training_seed_10	.786
392	convnext_tiny_sup	.784
393	AdvProp_efficientnet-b4	.780
394	convnext_tiny_imagenet_full_seed-0	.778
395	mobilenet_v2_0.5_192-tf	.774
396	yudixie_resnet18_distance_translation_rotation_0_240719	.771
397	deit_large_imagenet_full_seed-0	.769
398	AdvProp_efficientnet-b0	.768
399	mobilenet_v2_0.75_96	.745
400	resnet50_imagenet_1_seed-0	.735
401	resnet50_pretrained_with_retinal_waves	.731
402	deepeisnn_ei_cifar10_resnet18	.726
403	mobilenet_v2_0.75_192-tf	.724
404	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.721
405	mobilenet_v2_1.0_96	.720
406	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.720
407	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.720
408	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.719
409	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.719
410	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.716
411	mobilenet_v2_0.75_128	.713
412	AT_efficientnet-b2	.697
413	mobilenet_v2_0.75_224-tf	.697
414	AdvProp_efficientnet-b2	.695
415	AlexNet_SIN_fov16	.686
416	mobilenet_v2_0.5_160	.677
417	my-model	.674
418	alexnet_training_seed_03	.674
419	alexnet_training_seed_06	.649
420	gabor_filter_entropy_4x4	.646
421	alexnet_training_seed_01_fov16	.635
422	gabor_filter_entropy_4x4_v2_forcedCosine	.597
423	alexnet_training_seed_01_fov4	.391
424	deit_small_imagenet_10_seed-0	.355
425	deit_small_imagenet_full_seed-0	.354
426	mobilenet_v2_0.75_160-tf	.064
427	mobilenet_v2_0.5_128	.000
428	mobilenet_v2_0.35_160
429	resnet18-supervised
430	fitvid_trained_on_physion
431	openclip
432	resnet50_ImageNet
433	regnet_y_400mf
434	tv_efficientnet-b1
435	alexnet_ks_torevert
436	yudixie_resnet50_imagenet1kpret_0_240312
437	resnet_152_v1
438	densenet_201_pytorch
439	pnasnet_large_pytorch
440	inception_v3_pytorch
441	inception_v4
442	deit_small_imagenet_1_seed-0
443	nasnet_large
444	pnasnet_large
445	vonegrcnn_62e_nobn
446	vonegrcnn_47e
447	resnet_152_v2
448	mehrer2020_alexnet_training_seed_01_fov4
449	mehrer2020_alexnet_training_seed_01_fov16
450	mehrer2020_alexnet_training_seed_04
451	mehrer2020_alexnet_training_seed_05
452	mehrer2020_alexnet_training_seed_06
453	mehrer2020_alexnet_training_seed_07
454	mehrer2020_alexnet_training_seed_10
455	pr1_stl10_disentangled_alpha04
456	predictive_coding_pc
457	dinov2_vitg14_reg_lc
458	eva02_large_in22k
459	vit_huge_clip336_laion

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or