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

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: pref_or