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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	pnasnet_large_halfPrecision	.995
12	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.993
13	resnet18_ecoset_full	.992
14	AlexNet_SIN_fov12	.993
15	resnet50_random_linf8_perturb	.992
16	voneresnet-50-robust	.991
17	deit_small_imagenet_100_seed-0	.991
18	vit_large_patch14_clip_224:laion2b_ft_in1k	.991
19	voneresnet-50	.990
20	voneresnet-50-non_stochastic	.991
21	pnasnet_large-tf	.989
22	inception_v1	.989
23	resnet-50-robust	.988
24	resnet50-vicregl0p9	.988
25	SWSL_resnext101_32x8d	.987
26	mobilenet_v2_0_75_192	.989
27	vit_relpos_base_patch16_clsgap_224:sw_in1k	.988
28	vit_base_patch16_clip_224:openai_ft_in1k	.986
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	vit_base_patch14_reg4_dinov2-lvd142m	.984
43	resnet_50_v2	.983
44	alexnet_fov4	.983
45	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.982
46	mobilenet_v2_1_0_192	.982
47	eBarlow_lmda_02_1000ep	.983
48	inception_v2-tf	.982
49	vit_large_patch14_clip_224:openai_ft_in1k	.983
50	hmax	.983
51	VOneCORnet-S	.983
52	resnet34_imagenet_full	.982
53	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.982
54	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.983
55	BiT-M-R50x3	.981
56	aughost_fair_resnet18	.979
57	resnet50-sup	.980
58	alexnet_l2_3_robust	.980
59	ReAlnet01_ALL	.978
60	ReAlnet01_cornet_fov4	.979
61	resnet18_imagenet_full	.980
62	alexnet_linf_8_robust	.980
63	omnivore_swinB	.980
64	resnet_50_v1_spiking_l3	.978
65	ReAlnet02	.979
66	yudixie_resnet50_imagenet1kpret_0_240908	.978
67	resnet_50_v1_spiking_l4a	.978
68	resnet_101_v2	.979
69	resnet_50_v1	.979
70	ReAlnet02_cornet	.979
71	compact_vgg19_V4	.979
72	resnet_50_v1_spiking_l4	.979
73	resnet50_tutorial	.977
74	resnet_50_v1_spiking	.978
75	yudixie_resnet50_rotation_reg_0_240908	.978
76	alexnet_robust_correct	.976
77	antialias-resnet152	.977
78	alexnet_fov12	.977
79	mobilenet_v2_1_3_224	.977
80	vonegrcnn_47e	.976
81	ReAlnet09_ALL	.977
82	antialiased-rnext101_32x8d	.974
83	inception_v3	.976
84	ReAlnet02_ALL	.976
85	ReAlnet10	.975
86	resnet50-moclr8deg	.974
87	convnext_femto_ols:d1_in1k	.974
88	ReAlnet10_cornet	.975
89	resnet101	.972
90	resnet-18-LC_w_sh_1_iter_m	.973
91	cvt_cvt-21-224-in1k_4_LucyV4	.974
92	resnet50_linf_4_robust	.973
93	resnet152_ecoset_full	.973
94	cvt_cvt-13-384-in1k_4_LucyV4	.972
95	CLIP_ViT-B_32	.973
96	resnet-101_v1-tf	.972
97	omnivore_swinS	.973
98	cvt_cvt-13-224-in1k_4_LucyV4	.971
99	alexnet_random_l2_3_perturb	.972
100	ReAlnet01_cornet	.971
101	alexnet_fov16	.972
102	ReAlnet08_ALL	.970
103	resnet50-simclr-vissl	.972
104	ReAlnet01	.970
105	ReAlnet04_ALL	.972
106	ReAlnet04_cornet	.970
107	0.5x_resnet-18	.970
108	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.969
109	ReAlnet04	.971
110	ReAlnet03_cornet	.970
111	resnet50_random_l2_perturb	.969
112	ReAlnet10_ALL	.970
113	ReAlnet03	.969
114	resnet101_imagenet_full	.968
115	mobilenet_v2_1_4_224	.969
116	vit_large_patch14_clip_336:laion2b_ft_in1k	.967
117	barlow-twins-resnet50	.967
118	convnext_base_imagenet_full_seed-0	.968
119	vonegrcnn_52e_full	.968
120	ReAlnet09	.967
121	resnet50_l2_3_robust	.967
122	deit_base_imagenet_full_seed-0	.967
123	resnet50-meshes-lt-100-original-scratch	.966
124	ReAlnet09_cornet	.965
125	ReAlnet05_ALL	.966
126	densenet-201	.965
127	CLIP-RN50	.965
128	resnet-50_v2-tf	.966
129	alexnet_early_checkpoint	.966
130	AlexNet_SIN	.965
131	resnet50-vitoimagevidnet8	.964
132	resnet-50_v1-tf	.964
133	resnet50_byol	.965
134	vision_transformer_vit_large_patch16_224	.963
135	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.963
136	convnext_base:clip_laiona_augreg_ft_in1k_384	.963
137	ReAlnet07	.964
138	ReAlnet03_ALL	.964
139	r3m_resnet34_nocrop	.963
140	ReAlnet07_ALL	.963
141	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.963
142	ReAlnet07_cornet	.963
143	vonegrcnn_62e_nobn	.963
144	vonealexnet_gaussian_noise_std4_fixed	.963
145	CORnet-S	.962
146	vgg-19-keras	.963
147	ReAlnet05	.963
148	ReAlnet05_cornet	.963
149	resnet-18-LC_w_sh_1_iter_conv_init_m	.962
150	ReAlnet06_ALL	.959
151	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.960
152	ReAlnet08_cornet	.960
153	mobilenet_v2_1_0_224	.961
154	ReAlnet08	.960
155	imagenet_l2_3_0	.960
156	efficientnet_b1_imagenet_full	.959
157	BiT-S-R101x1	.959
158	resnet-101_v2-tf	.960
159	cvt_cvt-21-384-in1k_4_LucyV4	.960
160	grcnn_robust_v1	.958
161	resnet152_imagenet_full	.959
162	BiT-S-R50x1	.957
163	compact_cornets_V4	.957
164	grcnn_v2_text_noise	.956
165	resnet-18_test_m	.956
166	resnet34_ecoset_full	.956
167	FrankRobWobv0	.954
168	resnext101_32x8d_wsl	.955
169	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.955
170	resnet50_moco_v2	.954
171	mobilenet_v2_0_75_160	.954
172	BiT-S-R50x3	.955
173	CORnet-Z	.954
174	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.954
175	BiT-S-R152x2	.953
176	omnivore_swinT	.954
177	cornet_s	.952
178	AdvProp_efficientnet-b7	.951
179	yudixie_resnet50_translation_reg_0_240908	.951
180	vgg_16	.950
181	cv_18_dagger_408_pretrained	.950
182	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.951
183	texture_shape_resnet50_trained_on_SIN	.950
184	CLIP_resnet50	.949
185	mobilenet_v2_1.0_192-tf	.948
186	resnet50_ewconplus_wzc	.947
187	convnext_large_imagenet_full_seed-0	.950
188	CLIP_resnet50_float32	.948
189	resnet50_robust_l2_eps3	.949
190	alexnet_reduced_aliasing_early_checkpoint	.947
191	resnet-18-LC_w_sh_100_iter_conv_init_m	.948
192	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.947
193	AdvProp_efficientnet-b8	.946
194	convnext_large:fb_in22k_ft_in1k	.947
195	densenet-169	.945
196	ViT_L_32_imagenet1k	.945
197	yudixie_resnet18_imagenet1kpret_0_240719	.943
198	blt_vs	.943
199	custom_model_cv_18_dagger_408	.943
200	inception_resnet_v2	.941
201	yudixie_resnet18_translation_rotation_0_240719	.941
202	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.940
203	effnetv2m_custom384	.939
204	resnet50_primary_visual_cortex	.940
205	resnet-152_v2-tf	.940
206	BiT-S-R152x4	.938
207	alexnet_training_seed_09	.938
208	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.939
209	resnet50_imagenet_100_seed-0	.938
210	BiT-S-R101x3	.938
211	yudixie_resnet50_distance_reg_0_240908	.936
212	mobilenet_v2_1.3_224-tf	.935
213	resnet50_simclr	.935
214	ReAlnet01_cornet_fov12	.934
215	densenet-121-keras	.934
216	resnet50_FractalDB	.934
217	resnet50_imagenet_full	.933
218	grcnn	.933
219	grcnn_109	.933
220	yudixie_resnet50_random_0_240908	.932
221	convnext_small_imagenet_100_seed-0	.932
222	nasnet_mobile-tf	.931
223	alexnet	.932
224	resnet_101_v1	.931
225	vonegrcnn_52e_full	.930
226	densenet-169-keras	.931
227	texture_shape_alexnet_trained_on_SIN	.930
228	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.931
229	yudixie_resnet50_distance_rotation_0_240908	.930
230	effnetb1_272x240	.930
231	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.930
232	mobilenet_v2_0_75_224	.929
233	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.928
234	convnext_small_imagenet_1_seed-0	.928
235	0.5x_resnet-18_LC_w_sh_10_iter	.928
236	konkle_alexnetgn_ipcl_ref01_primary_model	.927
237	yudixie_resnet50_distance_translation_0_240908	.927
238	xception	.926
239	resnet50-SIN_IN_IN	.927
240	resnet-18-LC_d_w_sh_1x1_conv_init_m	.925
241	BiT-M-R101x3	.925
242	BiT-M-R50x1	.924
243	convnext_xlarge:fb_in22k_ft_in1k	.923
244	densenet-201-keras	.923
245	RN50	.923
246	my-model	.922
247	0.5x_resnet-18_LC_w_sh_1_iter	.921
248	alexnet_training_seed_02	.921
249	yudixie_resnet50_translation_rotation_0_240908	.922
250	yudixie_resnet18_distance_translation_0_240719	.921
251	resnet50-SIN	.921
252	convnext_small_imagenet_10_seed-0	.918
253	efficientnet_b0_imagenet_full	.918
254	yudixie_resnet18_translation_reg_0_240719	.916
255	BiT-M-R101x1	.917
256	ReAlnet01_cornet_fov16	.915
257	alexnet_random_linf8_perturb	.916
258	resnet50-VITO-8deg-cc	.913
259	densenet-121	.913
260	compact_resnet50_V4	.910
261	nasnet_mobile	.911
262	Res2Net50_26w_4s	.911
263	resnet-18-LC_m	.911
264	convnext_tiny:in12k_ft_in1k	.910
265	mobilenet_v2_0_5_192	.908
266	AdvProp_efficientnet-b6	.907
267	resnet-50_untrained	.907
268	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.905
269	mobilenet_v2_1.0_160-tf	.905
270	alexnet_training_seed_05	.904
271	compact_cornets_IT	.901
272	0.5x_resnet-18_LC	.901
273	mobilenet_v2_1_0_160	.900
274	resnet50-cifar	.900
275	resnet-18-LC_untrained	.899
276	convnext_small_imagenet_full_seed-0	.899
277	resnet-152_v1-tf	.897
278	resnet-18-LC_w_sh_100_iter_m	.896
279	focalnet_tiny_lrf_in1k	.895
280	inception_v1-tf	.894
281	efficientnet_b0	.893
282	resnet-18-LC_conv_init_m	.893
283	yolos_tiny	.894
284	AlexNet_SIN_fov4	.892
285	BiT-M-R152x4	.892
286	resnet-18-LC_w_sh_10_iter_m	.891
287	resnet-18_untrained	.890
288	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.891
289	vggface	.889
290	ViT-B/32	.886
291	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.885
292	CORnetZ_CIFAR10_bs32_20_04	.885
293	efficientnet-b7	.884
294	CORnetZ_CIFAR10	.883
295	artResNet18_1	.882
296	r3m_resnet34	.882
297	shufflenet_v2_x1_0	.880
298	yudixie_resnet18_category_class_0_240719	.879
299	mobilenet_v2_0.35_224	.877
300	r3m_resnet18	.876
301	yudixie_resnet50_distance_translation_rotation_0_240908	.874
302	yudixie_resnet18_rotation_reg_0_240719	.872
303	resnet-18-LC_1st_conv_m	.868
304	mobilenet_v2_1-4_224_pytorch	.867
305	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.868
306	resnet50	.867
307	resnet18_imagenet21kP	.868
308	yudixie_resnet50_category_class_0_240908	.859
309	mobilenet_v2_0_5_224	.857
310	mobilenet_v2_1.0_224-tf	.852
311	yudixie_resnet18_object_class_0_240719	.850
312	yudixie_resnet18_distance_reg_0_240719	.849
313	mobilenet_v2_1.4_224-tf	.848
314	vit_base_patch14_dinov2-lvd142m	.844
315	efficientnet_b2_imagenet_full	.839
316	vit_base_patch16_dinov3-lvd1689m	.837
317	briaai_rmbg_1_4	.833
318	resnet-152_v2_pytorch	.832
319	mobilenet_v2_1.0_128-tf	.831
320	BiT-M-R152x2	.831
321	resnet-50x2_untrained	.832
322	alexnet_training_seed_04	.828
323	yudixie_resnet18_distance_rotation_0_240719	.822
324	alexnet_training_seed_01	.821
325	compact_resnet50_robust_V4	.815
326	compact_resnet50_IT	.815
327	mobilenet_v2_1_0_128	.813
328	alexnet_training_seed_07	.812
329	mobilenet_v1_0.25_128	.812
330	yudixie_resnet18_random_0_240719	.809
331	r3m_resnet50_nocrop	.808
332	compact_vgg19_IT	.804
333	mobilenet_v2_0.5_224-tf	.803
334	r3m_resnet50	.803
335	alexnet_training_seed_08	.801
336	compact_resnet50_robust_IT	.800
337	alexnet_training_seed_01_fov12	.796
338	0.5x_resnet-18_LC_w_sh_100_iter	.793
339	resnet50_imagenet_10_seed-0	.786
340	mobilevit_small	.786
341	alexnet_training_seed_10	.786
342	convnext_tiny_sup	.784
343	AdvProp_efficientnet-b4	.780
344	convnext_tiny_imagenet_full_seed-0	.778
345	mobilenet_v2_0.5_192-tf	.774
346	yudixie_resnet18_distance_translation_rotation_0_240719	.771
347	deit_large_imagenet_full_seed-0	.769
348	AdvProp_efficientnet-b0	.768
349	resnet50-meshes-lt-100-original-pretrained	.752
350	mobilenet_v2_0.75_96	.745
351	resnet50_imagenet_1_seed-0	.735
352	resnet50_pretrained_with_retinal_waves	.731
353	mobilenet_v2_0.75_192-tf	.724
354	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.721
355	mobilenet_v2_1.0_96	.720
356	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.720
357	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.720
358	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.719
359	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.719
360	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.716
361	mobilenet_v2_0.75_128	.713
362	AT_efficientnet-b2	.697
363	mobilenet_v2_0.75_224-tf	.697
364	AdvProp_efficientnet-b2	.695
365	AlexNet_SIN_fov16	.686
366	mobilenet_v2_0.5_160	.677
367	my-model	.674
368	alexnet_training_seed_03	.674
369	alexnet_training_seed_06	.649
370	alexnet_training_seed_01_fov16	.635
371	alexnet_training_seed_01_fov4	.391
372	deit_small_imagenet_10_seed-0	.355
373	deit_small_imagenet_full_seed-0	.354
374	mobilenet_v2_0.75_160-tf	.064
375	mobilenet_v2_0.5_128	.000
376	mobilenet_v2_0.35_160
377	resnet18-supervised
378	fitvid_trained_on_physion
379	openclip
380	resnext101_32x32d_wsl
381	resnext101_32x48d_wsl
382	resnet50_ImageNet
383	regnet_y_400mf
384	tv_efficientnet-b1
385	alexnet_ks_torevert
386	yudixie_resnet50_imagenet1kpret_0_240312
387	resnet_152_v1
388	resnext101_32x16d_wsl
389	densenet_201_pytorch
390	pnasnet_large_pytorch
391	inception_v3_pytorch
392	inception_v4
393	deit_small_imagenet_1_seed-0
394	nasnet_large
395	pnasnet_large
396	vonegrcnn_62e_nobn
397	vonegrcnn_47e
398	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or