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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Marques2020_Ringach2002-cv_bandwidth_ratio")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	ViT_L_32_imagenet1k	.966
2	convnext_small_imagenet_full_seed-0	.963
3	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.961
4	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.962
5	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.961
6	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.960
7	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.961
8	resnet-18-LC_w_sh_10_iter_conv_init_m	.961
9	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.959
10	compact_vgg19_V4	.956
11	resnet50-vicregl0p75	.955
12	antialiased-rnext101_32x8d	.950
13	vit_large_patch14_clip_336:laion2b_ft_in1k	.949
14	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.947
15	resnet-18-LC_1st_conv_m	.947
16	vgg_16	.944
17	vit_huge_clip336_laion	.943
18	resnet-152_v1-tf	.943
19	cv_18_dagger_408_pretrained	.943
20	RN50	.941
21	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.941
22	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.939
23	CLIP_resnet50_float32	.942
24	CLIP_resnet50	.940
25	nasnet_mobile	.940
26	vit_relpos_base_patch16_clsgap_224:sw_in1k	.939
27	BiT-S-R50x3	.939
28	my-model	.939
29	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.939
30	vonegrcnn_52e_full	.937
31	vision_transformer_vit_large_patch16_224	.937
32	resnet50_simclr	.936
33	vonegrcnn_47e	.935
34	convnext_tiny_sup	.935
35	grcnn_109	.934
36	regnety_032	.934
37	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.933
38	resnet-18-LC_w_sh_10_iter_m	.931
39	AdvProp_efficientnet-b8	.931
40	cvt_cvt-13-384-in1k_4_LucyV4	.931
41	resnext101_32x16d_wsl	.929
42	inception_v3	.929
43	grcnn_v2_text_noise	.927
44	alexnet_training_seed_04	.926
45	convnext_base:clip_laiona_augreg_ft_in1k_384	.925
46	dinov2_vitg14_lc	.926
47	resnet-50_v1-tf	.926
48	efficientnet-b7	.926
49	resnext101_32x48d_wsl	.926
50	blt_vs	.924
51	custom_model_cv_18_dagger_408	.924
52	resnet50-SIN_IN_IN	.923
53	cvt_cvt-21-384-in1k_4_LucyV4	.921
54	CLIP-RN50	.922
55	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.921
56	resnet_50_v1	.921
57	cvt_cvt-13-224-in1k_4_LucyV4	.922
58	resnet_SIN_IN_FT_IN	.921
59	dinov2_vitl14_lc_res336	.921
60	resnet50-sup	.921
61	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.920
62	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.920
63	resnet_50_v1_spiking_l4	.921
64	deepeisnn_ei_imagenet_resnet18	.920
65	resnet50_tutorial	.920
66	resnet_50_v1_spiking	.919
67	resnet_50_v1_spiking_l3	.920
68	resnet50-barlow	.918
69	yudixie_resnet50_imagenet1kpret_0_240908	.919
70	resnet_50_v1_spiking_l4a	.918
71	resnet-50_v2-tf	.919
72	BiT-S-R101x3	.917
73	vit_base_patch14_dinov2-lvd142m	.917
74	yudixie_resnet18_object_class_0_240719	.916
75	alexnet_training_seed_01	.915
76	alexnet_training_seed_01_fov4	.914
77	vit_base_patch14_reg4_dinov2-lvd142m	.915
78	BiT-S-R101x1	.914
79	mobilenet_v2_1.4_224-tf	.915
80	alexnet_training_seed_07	.914
81	alexnet_training_seed_02	.915
82	compact_resnet50_robust_IT	.915
83	alexnet_training_seed_01_fov16	.914
84	mobilenet_v2_1_4_224	.914
85	BiT-M-R152x4	.914
86	alexnet_training_seed_10	.915
87	efficientnet_b2_imagenet_full	.914
88	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.913
89	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.913
90	alexnet_training_seed_03	.912
91	dinov2_vitl14_lc	.912
92	alexnet_training_seed_09	.911
93	vonegrcnn_47e	.911
94	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.911
95	mobilenet_v2_1.3_224-tf	.909
96	alexnet_fov16	.908
97	seresnext50_32x4d	.908
98	resnet50_primary_visual_cortex	.908
99	resnet50_vicreg_linhead	.907
100	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.906
101	0.5x_resnet-18_LC_w_sh_10_iter	.905
102	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.905
103	resnet50_random_l2_perturb	.905
104	convnext_base_fb_in22k_ft_in1k	.904
105	compact_cornets_IT	.904
106	SWSL_resnext101_32x8d	.902
107	resnet50_byol	.903
108	cvt_cvt-21-224-in1k_4_LucyV4	.903
109	deit_base_imagenet_full_seed-0	.902
110	focalnet_tiny_lrf_in1k	.900
111	effnetv2m_custom384	.899
112	resnet50_imagenet_full	.899
113	resnet50-vicreg	.898
114	xception	.899
115	BiT-M-R101x1	.897
116	nasnet_mobile-tf	.898
117	resnet-101_v1-tf	.898
118	mobilenet_v2_0.5_192-tf	.898
119	dinov2_vitl14_reg_lc_featread	.897
120	resnet-18-LC_w_sh_1_iter_conv_init_m	.898
121	omnivore_swinT	.896
122	convnext_small_imagenet_100_seed-0	.897
123	shufflenet_v2_x1_0	.896
124	dinov2_vitg14_reg_lc	.896
125	dinov2_vitl14_reg_lc	.896
126	resnet50_moco_v2	.894
127	AlexNet_SIN	.894
128	resnet50-moclr8deg	.894
129	grcnn	.893
130	resnet50_FractalDB	.893
131	inception_v4-tf	.892
132	BiT-M-R50x3	.891
133	r3m_resnet50_nocrop	.889
134	mobilenet_v2_1.0_160-tf	.889
135	konkle_alexnetgn_ipcl_ref01_primary_model	.888
136	efficientnet_b0_imagenet_full	.888
137	resnet-18_untrained	.887
138	AdvProp_efficientnet-b4	.886
139	r3m_resnet34_nocrop	.886
140	BiT-S-R152x4	.884
141	0.5x_resnet-18_LC_w_sh_100_iter	.884
142	yudixie_resnet50_distance_rotation_0_240908	.884
143	resnet50_imagenet_100_seed-0	.884
144	BiT-S-R50x1	.883
145	r3m_resnet50	.882
146	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.882
147	CLIP_ViT-B_32	.882
148	inception_v3-tf	.881
149	BiT-M-R50x1	.881
150	resnet50	.880
151	resnet50_byol_linhead	.880
152	mobilenet_v2_0.75_192-tf	.880
153	vonegrcnn_62e_nobn	.879
154	inception_v2-tf	.878
155	mobilenet_v2_1.0_96	.878
156	yudixie_wbh_object_class_scaling_0415_imagenet	.878
157	yudixie_resnet18_random_0_240719	.877
158	convnext_large_clip_laion2b_finelayers	.876
159	yudixie_resnet18_imagenet1kpret_0_240719	.876
160	mobilenet_v2_1.0_224-tf	.876
161	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.875
162	SWSL_resnet50	.876
163	resnet50_random_linf8_perturb	.876
164	vit_large_clip336_openai	.873
165	AdvProp_efficientnet-b6	.873
166	BiT-M-R152x2	.873
167	alexnet_training_seed_08	.872
168	omnivore_swinS	.871
169	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.871
170	resnet18_ecoset_full	.872
171	mobilenet_v2_0.5_224-tf	.872
172	mobilenet_v2_0_5_192	.871
173	alexnet	.871
174	resnet50_simsiam_linhead	.870
175	CORnet-Z	.870
176	vit_base_patch16_dinov3-lvd1689m	.870
177	resnet50-SIN	.870
178	resnet50_linf_8_robust	.870
179	omnivore_swinB	.868
180	yudixie_resnet18_category_class_0_240719	.868
181	convnext_base_imagenet_full_seed-0	.868
182	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.868
183	convnext_large:fb_in22k_ft_in1k	.866
184	resnet50_barlowtwins_linhead	.866
185	convnext_femto_ols:d1_in1k	.866
186	pnasnet_large_halfPrecision	.865
187	eBarlow_lmda_02_1000ep	.865
188	gabor_filter_mean_abs_4x4_v2	.865
189	effnetb1_272x240	.863
190	convnext_tiny:in12k_ft_in1k	.863
191	antialiased-r50	.862
192	yudixie_resnet50_distance_reg_0_240908	.861
193	texture_shape_resnet50_trained_on_SIN	.861
194	resnet-50x2_untrained	.860
195	BiT-M-R101x3	.859
196	mobilenet_v2_0_75_224	.859
197	vit_large_patch14_clip_224:openai_ft_in1k	.856
198	mobilenet_v2_0_75_160	.854
199	vit_base_patch16_clip_224:openai_ft_in1k	.853
200	imagenet_l2_10_0	.853
201	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.853
202	inception_resnet_v2	.851
203	eicircuit_resnet18_bn_20260919	.850
204	AlexNet_SIN_fov16	.849
205	AdvProp_efficientnet-b7	.849
206	mobilenet_v2_1_0_224	.848
207	pnasnet_large-tf	.847
208	vonealexnet_gaussian_noise_std4_fixed	.847
209	AlexNet_SIN_fov12	.844
210	resnet50-VITO-8deg-cc	.843
211	resnet-50-robust	.843
212	FrankRobWobv0	.842
213	yudixie_resnet18_translation_rotation_0_240719	.843
214	resnet-50_untrained	.839
215	ijepa_vith14_linhead	.838
216	yudixie_resnet50_distance_translation_rotation_0_240908	.838
217	alexnet_fov12	.837
218	resnet-152_v2-tf	.837
219	mobilenet_v2_1_0_160	.836
220	mobilenet_v2_0.75_224-tf	.834
221	deit_small_imagenet_100_seed-0	.833
222	mobilenet_v2_1.0_192-tf	.833
223	compact_cornets_V4	.833
224	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.830
225	resnet-101_v2-tf	.830
226	yudixie_resnet50_rotation_reg_0_240908	.830
227	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.829
228	deit3_base_patch16_224_fb_in1k	.828
229	alexnet_reduced_aliasing_early_checkpoint	.829
230	vgg_19	.829
231	mobilenet_v2_1_0_192	.827
232	resnet50_linf_4_robust	.827
233	compact_resnet50_V4	.826
234	alexnet_fov4	.826
235	AdvProp_efficientnet-b0	.826
236	convnext_large_imagenet_full_seed-0	.821
237	grcnn_robust_v1	.821
238	yudixie_resnet50_category_class_0_240908	.821
239	r3m_resnet18	.819
240	vit_large_patch14_clip_224:laion2b_ft_in1k	.819
241	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.818
242	resnet-18-LC_w_sh_100_iter_conv_init_m	.819
243	yudixie_wbh_object_class_scaling_0415_run_3	.817
244	efficientnet_b1_imagenet_full	.817
245	efficientnet_b0	.816
246	nasnet_large-tf	.814
247	resnet50_robust_l2_eps1	.813
248	resnet50_imagenet_10_seed-0	.814
249	resnext101_32x32d_wsl	.813
250	yudixie_resnet50_translation_rotation_0_240908	.811
251	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.811
252	deit3_base_patch16_224_fb_in22k_ft_in1k	.811
253	alexnet_random_linf8_perturb	.810
254	resnet-18-LC_w_sh_1_iter_m	.809
255	CORnetZ_CIFAR10	.808
256	deit_large_imagenet_full_seed-0	.806
257	r3m_resnet34	.804
258	resnet50_l2_3_robust	.805
259	alexnet_random_l2_3_perturb	.805
260	yudixie_resnet50_object_class_0_240908	.802
261	yudixie_resnet18_translation_reg_0_240719	.801
262	texture_shape_alexnet_trained_on_SIN	.800
263	resnet18_imagenet21kP	.800
264	resnet_101_v1	.797
265	BiT-S-R152x2	.797
266	densenet-169-keras	.797
267	resnet50_robust_l2_eps3	.796
268	antialias-resnet152	.794
269	yudixie_wbh_object_class_scaling_0415_run_0	.794
270	convnext_xlarge:fb_in22k_ft_in1k	.793
271	mobilenet_v2_0.35_224	.792
272	mehrer2020_alexnet_training_seed_10	.791
273	compact_resnet50_IT	.790
274	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.789
275	yudixie_resnet18_distance_translation_rotation_0_240719	.789
276	resnet101	.787
277	resnet50_pretrained_with_retinal_waves	.787
278	AlexNet_SIN_fov4	.787
279	mehrer2020_alexnet_training_seed_01_fov12	.786
280	resnet-18-LC_m	.786
281	compact_resnet50_robust_V4	.784
282	inception_v1	.785
283	yudixie_resnet50_distance_translation_0_240908	.781
284	compact_vgg19_IT	.777
285	vgg-16-keras	.778
286	alexnet_robust_correct	.778
287	vgg-19-keras	.776
288	convnext_large_in22k_supervised	.775
289	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.775
290	alexnet_training_seed_05	.773
291	voneresnet-50-non_stochastic	.772
292	yudixie_resnet18_distance_translation_0_240719	.771
293	ReAlnet01_cornet_fov16	.770
294	mobilenet_v2_0_75_192	.769
295	VOneCORnet-S	.767
296	voneresnet-50	.766
297	alexnet_early_checkpoint	.764
298	mehrer2020_alexnet_training_seed_08	.764
299	voneresnet-50-robust	.763
300	mehrer2020_alexnet_training_seed_01_fov4	.761
301	resnet-18-LC_d_w_sh_1x1_conv_init_m	.761
302	convnext_tiny_imagenet_full_seed-0	.761
303	alexnet_training_seed_01_fov12	.760
304	imagenet_l2_3_0	.757
305	mobilenet_v2_0.75_96	.757
306	artResNet18_1	.755
307	mobilenet_v2_1_3_224	.746
308	yudixie_resnet18_distance_rotation_0_240719	.746
309	resnet50-vicregl0p9	.746
310	yudixie_resnet50_random_0_240908	.746
311	alexnet_training_seed_06	.745
312	deit_small_imagenet_full_seed-0	.745
313	resnet50_imagenet_1_seed-0	.746
314	gabor_filter_entropy_4x4_v2_forcedCosine	.746
315	inception_v1-tf	.745
316	my-model	.745
317	resnet50-cifar	.745
318	mobilenet_v2_1.0_128-tf	.745
319	resnet50-vitoimagevidnet8	.742
320	alexnet_linf_8_robust	.742
321	0.5x_resnet-18_LC	.741
322	mehrer2020_alexnet_training_seed_02	.741
323	densenet-121	.738
324	densenet-121-keras	.737
325	densenet-169	.734
326	densenet-201	.733
327	yudixie_resnet50_translation_reg_0_240908	.732
328	briaai_rmbg_1_4	.731
329	deepeisnn_ei_cifar10_vgg19	.730
330	mehrer2020_alexnet_training_seed_03	.727
331	resnet50_st_wzc_seed6_2_323	.725
332	resnext101_32x8d_wsl	.724
333	mobilenet_v1_0.25_128	.722
334	yudixie_wbh_object_class_scaling_0415_run_2	.721
335	densenet-201-keras	.720
336	mehrer2020_alexnet_training_seed_09	.718
337	ViT-B/32	.715
338	resnet50_ewconplus_wzc_seed5_2__323	.713
339	ReAlnet01	.712
340	alexnet_l2_3_robust	.712
341	ReAlnet01_cornet	.710
342	resnet50_ecoset_full	.710
343	ReAlnet09_cornet	.707
344	barlow-twins-resnet50	.707
345	resnet50-simclr-vissl	.706
346	AdvProp_efficientnet-b2	.707
347	ReAlnet09	.705
348	AT_efficientnet-b2	.705
349	v1-pyr-nodown	.705
350	ReAlnet03_ALL	.704
351	hmax	.700
352	ReAlnet08_ALL	.696
353	yudixie_wbh_object_class_scaling_0415_run_1	.695
354	convnext_base_fb_in1k_gram_aligned_dinov3	.693
355	Res2Net50_26w_4s	.693
356	deepeisnn_ei_cifar10_resnet18	.691
357	resnet34_imagenet_full	.690
358	resnet50_st_wzc_seed7_2_323	.688
359	ReAlnet07	.688
360	ReAlnet07_cornet	.688
361	ReAlnet08	.688
362	ReAlnet08_cornet	.687
363	resnet50-SIN_IN	.685
364	ReAlnet04	.684
365	ReAlnet04_cornet	.684
366	ReAlnet03	.682
367	ReAlnet03_cornet	.681
368	ReAlnet02_ALL	.680
369	ReAlnet04_ALL	.679
370	ReAlnet10	.678
371	mobilenet_v2_1_0_128	.677
372	ReAlnet02_cornet	.677
373	ReAlnet02	.677
374	ReAlnet10_cornet	.677
375	yolos_tiny	.677
376	yudixie_resnet18_distance_reg_0_240719	.676
377	mobilenet_v2_0.75_128	.672
378	ReAlnet05_ALL	.670
379	resnet18_fair	.670
380	ReAlnet06_ALL	.669
381	ReAlnet07_ALL	.667
382	yudixie_resnet18_rotation_reg_0_240719	.667
383	CORnet-S	.667
384	resnet34_ecoset_full	.665
385	ReAlnet06	.665
386	ReAlnet06_cornet	.665
387	ReAlnet01_cornet_fov4	.664
388	ReAlnet05	.664
389	ReAlnet05_cornet	.664
390	ReAlnet01_ALL	.663
391	ReAlnet09_ALL	.661
392	resnet101_imagenet_full	.661
393	ReAlnet10_ALL	.661
394	resnet-18-LC_untrained	.658
395	0.5x_resnet-18_LC_w_sh_1_iter	.655
396	resnet50_st_wzc_2	.654
397	resnet_101_v2	.652
398	resnet152_ecoset_full	.650
399	ReAlnet01_cornet_fov12	.647
400	vggface	.646
401	resnet18_imagenet_full	.646
402	resnet50_ewconplus_wzc_seed2_2__323	.645
403	resnet-18_test_m	.644
404	resnet50_st_wzc_seed3_2_323	.644
405	resnet101_ecoset_full	.644
406	resnet-18-LC_conv_init_m	.643
407	convnext_base_fb_in1k	.639
408	resnet-18-LC_w_sh_100_iter_m	.636
409	cornet_s	.635
410	0.5x_resnet-18	.633
411	resnet_50_v2	.631
412	resnet-152_v2_pytorch	.632
413	resnet50_hvs_wzc	.627
414	resnet50_ewconplus_wzc	.618
415	mobilenet_v2_1-4_224_pytorch	.616
416	resnet50_ewconplus_wzc_seed6_2_323	.604
417	mobilenet_v2_0_5_224	.597
418	convnext_small_imagenet_1_seed-0	.593
419	resnet152_imagenet_full	.590
420	mobilenet_v2_0.75_160-tf	.561
421	CORnetZ_CIFAR10_bs32_20_04	.507
422	convnext_small_imagenet_10_seed-0	.491
423	deit_small_imagenet_10_seed-0	.333
424	mobilenet_v2_0.5_160	.288
425	mobilenet_v2_0.5_128	.288
426	gabor_filter_entropy_4x4	.000
427	gabor_filter_entropy_4x4_v2	.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	inception_v3_pytorch
440	pnasnet_large_pytorch
441	inception_v4
442	nasnet_large
443	deit_small_imagenet_1_seed-0
444	pnasnet_large
445	vonegrcnn_62e_nobn
446	vonegrcnn_52e_full
447	resnet_152_v2
448	resnet50_simclr_linhead_01norm
449	mehrer2020_alexnet_training_seed_01
450	mehrer2020_alexnet_training_seed_01_fov16
451	mehrer2020_alexnet_training_seed_04
452	mehrer2020_alexnet_training_seed_05
453	mehrer2020_alexnet_training_seed_06
454	mehrer2020_alexnet_training_seed_07
455	pr1_stl10_disentangled_alpha04
456	predictive_coding_pc
457	eva02_large_in22k
458	convnext_xxlarge_clip

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: cv_bandwidth_ratio