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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	SWSL_resnet50	.995
11	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.993
12	resnet18_ecoset_full	.992
13	AlexNet_SIN_fov12	.993
14	resnet50_random_linf8_perturb	.992
15	voneresnet-50-robust	.991
16	deit_small_imagenet_100_seed-0	.991
17	vit_large_patch14_clip_224:laion2b_ft_in1k	.991
18	voneresnet-50	.990
19	voneresnet-50-non_stochastic	.991
20	pnasnet_large-tf	.989
21	inception_v1	.989
22	resnet-50-robust	.988
23	resnet50-vicregl0p9	.988
24	SWSL_resnext101_32x8d	.987
25	mobilenet_v2_0_75_192	.989
26	vit_relpos_base_patch16_clsgap_224:sw_in1k	.988
27	vit_base_patch16_clip_224:openai_ft_in1k	.986
28	alexnet	.987
29	resnet50-barlow	.987
30	resnet50-vicregl0p75	.986
31	resnet50_ecoset_full	.987
32	resnet50_linf_8_robust	.987
33	resnet_SIN_IN_FT_IN	.987
34	v1-pyr-nodown	.986
35	ReAlnet06_cornet	.985
36	yudixie_resnet50_object_class_0_240908	.985
37	ReAlnet06	.985
38	resnet50_robust_l2_eps1	.984
39	vgg-16-keras	.984
40	resnet101_ecoset_full	.984
41	inception_v3-tf	.984
42	resnet_50_v2	.983
43	alexnet_fov4	.983
44	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.982
45	mobilenet_v2_1_0_192	.982
46	inception_v2-tf	.982
47	vit_large_patch14_clip_224:openai_ft_in1k	.983
48	hmax	.983
49	VOneCORnet-S	.983
50	resnet34_imagenet_full	.982
51	vit_base_patch14_reg4_dinov2:lvd142m	.982
52	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.982
53	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.983
54	BiT-M-R50x3	.981
55	resnet50-sup	.980
56	alexnet_l2_3_robust	.980
57	ReAlnet01_ALL	.978
58	ReAlnet01_cornet_fov4	.979
59	resnet18_imagenet_full	.980
60	alexnet_linf_8_robust	.980
61	omnivore_swinB	.980
62	resnet_50_v1_spiking_l3	.978
63	ReAlnet02	.979
64	yudixie_resnet50_imagenet1kpret_0_240908	.978
65	resnet_50_v1_spiking_l4a	.978
66	resnet_101_v2	.979
67	resnet_50_v1	.979
68	ReAlnet02_cornet	.979
69	compact_vgg19_V4	.979
70	resnet_50_v1_spiking_l4	.979
71	resnet50_tutorial	.977
72	resnet_50_v1_spiking	.978
73	yudixie_resnet50_rotation_reg_0_240908	.978
74	alexnet_robust_correct	.976
75	antialias-resnet152	.977
76	alexnet_fov12	.977
77	mobilenet_v2_1_3_224	.977
78	vonegrcnn_47e	.976
79	ReAlnet09_ALL	.977
80	antialiased-rnext101_32x8d	.974
81	inception_v3	.976
82	ReAlnet02_ALL	.976
83	ReAlnet10	.975
84	resnet50-moclr8deg	.974
85	convnext_femto_ols:d1_in1k	.974
86	ReAlnet10_cornet	.975
87	resnet101	.972
88	resnet-18-LC_w_sh_1_iter_m	.973
89	cvt_cvt-21-224-in1k_4_LucyV4	.974
90	resnet50_linf_4_robust	.973
91	resnet152_ecoset_full	.973
92	cvt_cvt-13-384-in1k_4_LucyV4	.972
93	CLIP_ViT-B_32	.973
94	resnet-101_v1-tf	.972
95	omnivore_swinS	.973
96	cvt_cvt-13-224-in1k_4_LucyV4	.971
97	alexnet_random_l2_3_perturb	.972
98	ReAlnet01_cornet	.971
99	alexnet_fov16	.972
100	ReAlnet08_ALL	.970
101	resnet50-simclr-vissl	.972
102	ReAlnet01	.970
103	ReAlnet04_ALL	.972
104	ReAlnet04_cornet	.970
105	0.5x_resnet-18	.970
106	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.969
107	ReAlnet04	.971
108	ReAlnet03_cornet	.970
109	resnet50_random_l2_perturb	.969
110	ReAlnet10_ALL	.970
111	ReAlnet03	.969
112	resnet101_imagenet_full	.968
113	mobilenet_v2_1_4_224	.969
114	vit_large_patch14_clip_336:laion2b_ft_in1k	.967
115	barlow-twins-resnet50	.967
116	convnext_base_imagenet_full_seed-0	.968
117	vonegrcnn_52e_full	.968
118	ReAlnet09	.967
119	resnet50_l2_3_robust	.967
120	deit_base_imagenet_full_seed-0	.967
121	resnet50-meshes-lt-100-original-scratch	.966
122	ReAlnet09_cornet	.965
123	ReAlnet05_ALL	.966
124	densenet-201	.965
125	CLIP-RN50	.965
126	resnet-50_v2-tf	.966
127	alexnet_early_checkpoint	.966
128	AlexNet_SIN	.965
129	resnet50-vitoimagevidnet8	.964
130	resnet-50_v1-tf	.964
131	resnet50_byol	.965
132	vision_transformer_vit_large_patch16_224	.963
133	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.963
134	convnext_base:clip_laiona_augreg_ft_in1k_384	.963
135	ReAlnet07	.964
136	ReAlnet03_ALL	.964
137	r3m_resnet34_nocrop	.963
138	ReAlnet07_ALL	.963
139	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.963
140	ReAlnet07_cornet	.963
141	vonegrcnn_62e_nobn	.963
142	vonealexnet_gaussian_noise_std4_fixed	.963
143	CORnet-S	.962
144	vgg-19-keras	.963
145	ReAlnet05	.963
146	ReAlnet05_cornet	.963
147	resnet-18-LC_w_sh_1_iter_conv_init_m	.962
148	ReAlnet06_ALL	.959
149	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.960
150	ReAlnet08_cornet	.960
151	mobilenet_v2_1_0_224	.961
152	ReAlnet08	.960
153	imagenet_l2_3_0	.960
154	efficientnet_b1_imagenet_full	.959
155	BiT-S-R101x1	.959
156	resnet-101_v2-tf	.960
157	cvt_cvt-21-384-in1k_4_LucyV4	.960
158	grcnn_robust_v1	.958
159	resnet152_imagenet_full	.959
160	BiT-S-R50x1	.957
161	compact_cornets_V4	.957
162	grcnn_v2_text_noise	.956
163	resnet-18_test_m	.956
164	resnet34_ecoset_full	.956
165	FrankRobWobv0	.954
166	resnext101_32x8d_wsl	.955
167	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.955
168	resnet50_moco_v2	.954
169	mobilenet_v2_0_75_160	.954
170	BiT-S-R50x3	.955
171	CORnet-Z	.954
172	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.954
173	BiT-S-R152x2	.953
174	omnivore_swinT	.954
175	cornet_s	.952
176	AdvProp_efficientnet-b7	.951
177	yudixie_resnet50_translation_reg_0_240908	.951
178	vgg_16	.950
179	cv_18_dagger_408_pretrained	.950
180	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.951
181	texture_shape_resnet50_trained_on_SIN	.950
182	CLIP_resnet50	.949
183	mobilenet_v2_1.0_192-tf	.948
184	resnet50_ewconplus_wzc	.947
185	convnext_large_imagenet_full_seed-0	.950
186	CLIP_resnet50_float32	.948
187	resnet50_robust_l2_eps3	.949
188	alexnet_reduced_aliasing_early_checkpoint	.947
189	resnet-18-LC_w_sh_100_iter_conv_init_m	.948
190	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.947
191	AdvProp_efficientnet-b8	.946
192	convnext_large:fb_in22k_ft_in1k	.947
193	densenet-169	.945
194	ViT_L_32_imagenet1k	.945
195	yudixie_resnet18_imagenet1kpret_0_240719	.943
196	blt_vs	.943
197	custom_model_cv_18_dagger_408	.943
198	inception_resnet_v2	.941
199	yudixie_resnet18_translation_rotation_0_240719	.941
200	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.940
201	effnetv2m_custom384	.939
202	resnet50_primary_visual_cortex	.940
203	resnet-152_v2-tf	.940
204	BiT-S-R152x4	.938
205	alexnet_training_seed_09	.938
206	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.939
207	resnet50_imagenet_100_seed-0	.938
208	BiT-S-R101x3	.938
209	yudixie_resnet50_distance_reg_0_240908	.936
210	mobilenet_v2_1.3_224-tf	.935
211	resnet50_simclr	.935
212	ReAlnet01_cornet_fov12	.934
213	densenet-121-keras	.934
214	resnet50_FractalDB	.934
215	resnet50_imagenet_full	.933
216	grcnn	.933
217	grcnn_109	.933
218	yudixie_resnet50_random_0_240908	.932
219	convnext_small_imagenet_100_seed-0	.932
220	alexnet	.931
221	nasnet_mobile-tf	.931
222	alexnet	.932
223	resnet_101_v1	.931
224	alexnet	.931
225	alexnet_workflow_trigger	.931
226	vonegrcnn_52e_full	.930
227	alexnet	.931
228	alexnet	.930
229	densenet-169-keras	.931
230	alexnet	.931
231	alexnet	.931
232	texture_shape_alexnet_trained_on_SIN	.930
233	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.931
234	alexnet-baseline	.931
235	yudixie_resnet50_distance_rotation_0_240908	.930
236	alexnet	.929
237	effnetb1_272x240	.930
238	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.930
239	mobilenet_v2_0_75_224	.929
240	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.928
241	convnext_small_imagenet_1_seed-0	.928
242	0.5x_resnet-18_LC_w_sh_10_iter	.928
243	konkle_alexnetgn_ipcl_ref01_primary_model	.927
244	yudixie_resnet50_distance_translation_0_240908	.927
245	xception	.926
246	resnet50-SIN_IN_IN	.927
247	resnet-18-LC_d_w_sh_1x1_conv_init_m	.925
248	BiT-M-R101x3	.925
249	BiT-M-R50x1	.924
250	convnext_xlarge:fb_in22k_ft_in1k	.923
251	densenet-201-keras	.923
252	RN50	.923
253	my-model	.922
254	0.5x_resnet-18_LC_w_sh_1_iter	.921
255	alexnet_training_seed_02	.921
256	yudixie_resnet50_translation_rotation_0_240908	.922
257	yudixie_resnet18_distance_translation_0_240719	.921
258	resnet50-SIN	.921
259	convnext_small_imagenet_10_seed-0	.918
260	efficientnet_b0_imagenet_full	.918
261	yudixie_resnet18_translation_reg_0_240719	.916
262	BiT-M-R101x1	.917
263	ReAlnet01_cornet_fov16	.915
264	alexnet_random_linf8_perturb	.916
265	resnet50-VITO-8deg-cc	.913
266	densenet-121	.913
267	compact_resnet50_V4	.910
268	nasnet_mobile	.911
269	Res2Net50_26w_4s	.911
270	resnet-18-LC_m	.911
271	convnext_tiny:in12k_ft_in1k	.910
272	mobilenet_v2_0_5_192	.908
273	AdvProp_efficientnet-b6	.907
274	resnet-50_untrained	.907
275	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.905
276	mobilenet_v2_1.0_160-tf	.905
277	alexnet_training_seed_05	.904
278	compact_cornets_IT	.901
279	0.5x_resnet-18_LC	.901
280	mobilenet_v2_1_0_160	.900
281	resnet50-cifar	.900
282	resnet-18-LC_untrained	.899
283	convnext_small_imagenet_full_seed-0	.899
284	resnet-152_v1-tf	.897
285	resnet-18-LC_w_sh_100_iter_m	.896
286	focalnet_tiny_lrf_in1k	.895
287	inception_v1-tf	.894
288	efficientnet_b0	.893
289	resnet-18-LC_conv_init_m	.893
290	yolos_tiny	.894
291	AlexNet_SIN_fov4	.892
292	BiT-M-R152x4	.892
293	resnet-18-LC_w_sh_10_iter_m	.891
294	resnet-18_untrained	.890
295	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.891
296	vggface	.889
297	ViT-B/32	.886
298	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.885
299	CORnetZ_CIFAR10_bs32_20_04	.885
300	efficientnet-b7	.884
301	CORnetZ_CIFAR10	.883
302	artResNet18_1	.882
303	r3m_resnet34	.882
304	shufflenet_v2_x1_0	.880
305	yudixie_resnet18_category_class_0_240719	.879
306	mobilenet_v2_0.35_224	.877
307	r3m_resnet18	.876
308	yudixie_resnet50_distance_translation_rotation_0_240908	.874
309	yudixie_resnet18_rotation_reg_0_240719	.872
310	resnet-18-LC_1st_conv_m	.868
311	mobilenet_v2_1-4_224_pytorch	.867
312	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.868
313	resnet50	.867
314	resnet18_imagenet21kP	.868
315	yudixie_resnet50_category_class_0_240908	.859
316	mobilenet_v2_0_5_224	.857
317	mobilenet_v2_1.0_224-tf	.852
318	yudixie_resnet18_object_class_0_240719	.850
319	yudixie_resnet18_distance_reg_0_240719	.849
320	mobilenet_v2_1.4_224-tf	.848
321	vit_base_patch14_dinov2:lvd142m	.844
322	efficientnet_b2_imagenet_full	.839
323	vit_base_patch16_dinov3:lvd1689m	.837
324	briaai_rmbg_1_4	.833
325	resnet-152_v2_pytorch	.832
326	mobilenet_v2_1.0_128-tf	.831
327	BiT-M-R152x2	.831
328	resnet-50x2_untrained	.832
329	alexnet_training_seed_04	.828
330	yudixie_resnet18_distance_rotation_0_240719	.822
331	alexnet_training_seed_01	.821
332	compact_resnet50_robust_V4	.815
333	compact_resnet50_IT	.815
334	mobilenet_v2_1_0_128	.813
335	alexnet_training_seed_07	.812
336	mobilenet_v1_0.25_128	.812
337	yudixie_resnet18_random_0_240719	.809
338	r3m_resnet50_nocrop	.808
339	compact_vgg19_IT	.804
340	mobilenet_v2_0.5_224-tf	.803
341	r3m_resnet50	.803
342	alexnet_training_seed_08	.801
343	compact_resnet50_robust_IT	.800
344	alexnet_training_seed_01_fov12	.796
345	0.5x_resnet-18_LC_w_sh_100_iter	.793
346	resnet50_imagenet_10_seed-0	.786
347	mobilevit_small	.786
348	alexnet_training_seed_10	.786
349	convnext_tiny_sup	.784
350	AdvProp_efficientnet-b4	.780
351	convnext_tiny_imagenet_full_seed-0	.778
352	mobilenet_v2_0.5_192-tf	.774
353	yudixie_resnet18_distance_translation_rotation_0_240719	.771
354	deit_large_imagenet_full_seed-0	.769
355	AdvProp_efficientnet-b0	.768
356	resnet50-meshes-lt-100-original-pretrained	.752
357	mobilenet_v2_0.75_96	.745
358	resnet50_imagenet_1_seed-0	.735
359	resnet50_pretrained_with_retinal_waves	.731
360	mobilenet_v2_0.75_192-tf	.724
361	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.721
362	mobilenet_v2_1.0_96	.720
363	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.720
364	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.720
365	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.719
366	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.719
367	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.716
368	mobilenet_v2_0.75_128	.713
369	AT_efficientnet-b2	.697
370	mobilenet_v2_0.75_224-tf	.697
371	AdvProp_efficientnet-b2	.695
372	AlexNet_SIN_fov16	.686
373	mobilenet_v2_0.5_160	.677
374	my-model	.674
375	alexnet_training_seed_03	.674
376	alexnet_training_seed_06	.649
377	alexnet_training_seed_01_fov16	.635
378	alexnet_training_seed_01_fov4	.391
379	deit_small_imagenet_10_seed-0	.355
380	deit_small_imagenet_full_seed-0	.354
381	mobilenet_v2_0.75_160-tf	.064
382	mobilenet_v2_0.5_128	.000
383	mobilenet_v2_0.35_160
384	resnet18-supervised
385	fitvid_trained_on_physion
386	openclip
387	resnext101_32x32d_wsl
388	resnext101_32x48d_wsl
389	resnet50_ImageNet
390	regnet_y_400mf
391	tv_efficientnet-b1
392	alexnet_ks_torevert
393	yudixie_resnet50_imagenet1kpret_0_240312
394	resnet_152_v1
395	resnext101_32x16d_wsl
396	densenet_201_pytorch
397	pnasnet_large_pytorch
398	inception_v3_pytorch
399	inception_v4
400	deit_small_imagenet_1_seed-0
401	nasnet_large
402	pnasnet_large
403	vonegrcnn_62e_nobn
404	vonegrcnn_47e
405	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or