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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_w_sh_1_iter_conv_init_m	.984
2	omnivore_swinS	.984
3	yudixie_resnet18_rotation_reg_0_240719	.982
4	efficientnet-b7	.981
5	resnet-18-LC_w_sh_10_iter_conv_init_m	.969
6	resnet50_simsiam_linhead	.968
7	compact_vgg19_V4	.965
8	alexnet_robust_correct	.965
9	yudixie_resnet18_distance_reg_0_240719	.961
10	resnet50_barlowtwins_linhead	.956
11	AdvProp_efficientnet-b6	.956
12	BiT-S-R50x1	.954
13	vonegrcnn_62e_nobn	.955
14	vggface	.952
15	convnext_large_imagenet_full_seed-0	.952
16	yudixie_resnet18_distance_rotation_0_240719	.950
17	resnet_101_v1	.949
18	convnext_base:clip_laiona_augreg_ft_in1k_384	.950
19	convnext_base_fb_in22k_ft_in1k	.947
20	yudixie_resnet50_distance_translation_0_240908	.945
21	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.945
22	omnivore_swinB	.944
23	resnet-18-LC_w_sh_100_iter_m	.941
24	convnext_large_clip_laion2b_finelayers	.941
25	resnet34_imagenet_full	.941
26	resnet50_vicreg_linhead	.939
27	nasnet_large-tf	.939
28	ReAlnet03_ALL	.939
29	yudixie_resnet18_distance_translation_rotation_0_240719	.938
30	cvt_cvt-13-224-in1k_4_LucyV4	.937
31	yudixie_resnet18_distance_translation_0_240719	.936
32	alexnet_l2_3_robust	.934
33	resnet50_st_wzc_2	.934
34	ReAlnet09_ALL	.933
35	resnet101	.932
36	ReAlnet01_ALL	.933
37	yudixie_resnet50_translation_rotation_0_240908	.932
38	mobilenet_v2_1.0_96	.932
39	ReAlnet06_ALL	.933
40	resnet50_st_wzc_seed6_2_323	.931
41	ReAlnet04_ALL	.931
42	resnet-50_untrained	.930
43	resnet50_ewconplus_wzc_seed2_2__323	.930
44	ReAlnet08_ALL	.931
45	cvt_cvt-21-224-in1k_4_LucyV4	.928
46	ReAlnet02_ALL	.930
47	resnet-18-LC_w_sh_1_iter_m	.928
48	AdvProp_efficientnet-b8	.928
49	resnet50_byol_linhead	.928
50	resnet50-SIN_IN	.927
51	ReAlnet05_ALL	.927
52	resnet18_imagenet_full	.926
53	ReAlnet10_ALL	.927
54	cvt_cvt-21-384-in1k_4_LucyV4	.927
55	mobilenet_v2_1.3_224-tf	.925
56	resnet50-moclr8deg	.924
57	resnet-50_v1-tf	.923
58	BiT-S-R101x3	.923
59	vgg_19	.922
60	resnet-152_v2-tf	.922
61	compact_cornets_IT	.921
62	convnext_base_imagenet_full_seed-0	.920
63	xception	.920
64	voneresnet-50-non_stochastic	.920
65	compact_vgg19_IT	.919
66	alexnet_early_checkpoint	.917
67	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.917
68	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.917
69	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.916
70	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.916
71	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.915
72	alexnet_training_seed_01_fov12	.915
73	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.915
74	ReAlnet07_ALL	.916
75	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.915
76	mobilenet_v2_1.4_224-tf	.915
77	antialias-resnet152	.914
78	inception_v4-tf	.913
79	Res2Net50_26w_4s	.913
80	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.913
81	inception_v3-tf	.911
82	yudixie_resnet50_distance_rotation_0_240908	.911
83	yudixie_resnet50_translation_reg_0_240908	.911
84	focalnet_tiny_lrf_in1k	.911
85	yudixie_resnet50_distance_translation_rotation_0_240908	.910
86	resnet50_st_wzc_seed7_2_323	.910
87	BiT-M-R101x1	.910
88	yudixie_wbh_object_class_scaling_0415_run_3	.911
89	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.910
90	resnet50-simclr-vissl	.909
91	yudixie_resnet50_rotation_reg_0_240908	.909
92	vgg_16	.907
93	resnet50_l2_3_robust	.907
94	resnet-18_test_m	.906
95	BiT-M-R50x3	.907
96	texture_shape_alexnet_trained_on_SIN	.906
97	resnet50_st_wzc_seed3_2_323	.906
98	inception_v2-tf	.905
99	CORnet-S	.905
100	blt_vs	.904
101	resnext101_32x8d_wsl	.904
102	omnivore_swinT	.904
103	0.5x_resnet-18_LC_w_sh_1_iter	.904
104	resnet34_ecoset_full	.903
105	alexnet_random_l2_3_perturb	.902
106	resnet-50x2_untrained	.903
107	mehrer2020_alexnet_training_seed_07	.902
108	resnet50_byol	.901
109	BiT-S-R50x3	.900
110	resnet50_random_linf8_perturb	.900
111	vonealexnet_gaussian_noise_std4_fixed	.899
112	compact_resnet50_IT	.899
113	resnet101_ecoset_full	.897
114	SWSL_resnet50	.896
115	mobilenet_v2_1.0_160-tf	.896
116	resnet50_ewconplus_wzc_seed6_2_323	.895
117	AdvProp_efficientnet-b7	.895
118	convnext_tiny:in12k_ft_in1k	.893
119	resnet50-vicregl0p9	.892
120	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.892
121	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.891
122	mehrer2020_alexnet_training_seed_08	.891
123	alexnet_linf_8_robust	.890
124	BiT-S-R152x2	.889
125	resnet-18-LC_1st_conv_m	.889
126	resnet50-vicregl0p75	.888
127	imagenet_l2_3_0	.888
128	mehrer2020_alexnet_training_seed_01_fov12	.888
129	barlow-twins-resnet50	.888
130	yudixie_resnet50_distance_reg_0_240908	.888
131	resnet50_robust_l2_eps3	.886
132	resnet152_ecoset_full	.887
133	resnext101_32x16d_wsl	.886
134	BiT-M-R101x3	.885
135	resnet-18-LC_w_sh_100_iter_conv_init_m	.885
136	alexnet_random_linf8_perturb	.883
137	resnext101_32x48d_wsl	.884
138	convnext_xxlarge_clip	.884
139	grcnn	.884
140	compact_resnet50_robust_IT	.882
141	ViT_L_32_imagenet1k	.882
142	resnet_50_v2	.881
143	grcnn_robust_v1	.883
144	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.881
145	yudixie_resnet50_random_0_240908	.879
146	CLIP-RN50	.879
147	ReAlnet01_cornet_fov12	.878
148	resnet50_imagenet_100_seed-0	.879
149	ReAlnet01_cornet_fov16	.879
150	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.878
151	resnet50_ewconplus_wzc_seed5_2__323	.877
152	resnet_50_v1_spiking	.877
153	resnet_50_v1_spiking_l4	.876
154	yudixie_resnet50_imagenet1kpret_0_240908	.876
155	resnet_50_v1_spiking_l4a	.876
156	alexnet	.876
157	alexnet_fov16	.876
158	resnet50_tutorial	.875
159	resnet_50_v1	.875
160	grcnn_v2_text_noise	.875
161	resnet_50_v1_spiking_l3	.874
162	resnet50	.874
163	resnet18_imagenet21kP	.874
164	yolos_tiny	.874
165	resnext101_32x32d_wsl	.874
166	yudixie_wbh_object_class_scaling_0415_run_2	.874
167	resnet50-sup	.874
168	grcnn_109	.872
169	mobilenet_v2_0.75_192-tf	.873
170	convnext_large_in22k_supervised	.872
171	mobilenet_v2_1.0_224-tf	.871
172	resnet50_linf_8_robust	.871
173	CLIP_resnet50	.871
174	imagenet_l2_10_0	.870
175	resnet50-vitoimagevidnet8	.870
176	cornet_s	.869
177	deepeisnn_ei_cifar10_resnet18	.869
178	resnet18_ecoset_full	.867
179	convnext_tiny_imagenet_full_seed-0	.868
180	CLIP_resnet50_float32	.867
181	mobilenet_v2_0_75_192	.867
182	resnet-101_v2-tf	.866
183	densenet-169	.866
184	convnext_tiny_sup	.865
185	resnet50_ewconplus_wzc	.865
186	CLIP_ViT-B_32	.864
187	resnet-18-LC_w_sh_10_iter_m	.863
188	RN50	.863
189	AdvProp_efficientnet-b4	.861
190	resnet152_imagenet_full	.861
191	convnext_xlarge:fb_in22k_ft_in1k	.861
192	resnet50-VITO-8deg-cc	.859
193	ReAlnet09	.860
194	convnext_small_imagenet_1_seed-0	.859
195	mobilenet_v2_1_4_224	.858
196	ReAlnet09_cornet	.858
197	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.857
198	resnet101_imagenet_full	.857
199	resnet-18_untrained	.857
200	resnet50_linf_4_robust	.857
201	resnet50_FractalDB	.856
202	ReAlnet01	.855
203	mobilenet_v2_1.0_192-tf	.855
204	AdvProp_efficientnet-b0	.854
205	densenet-121	.854
206	convnext_small_imagenet_100_seed-0	.854
207	resnet-50_v2-tf	.853
208	resnet50_random_l2_perturb	.853
209	resnet_SIN_IN_FT_IN	.852
210	ReAlnet01_cornet	.853
211	AdvProp_efficientnet-b2	.852
212	effnetv2m_custom384	.852
213	inception_v3	.851
214	antialiased-r50	.852
215	AT_efficientnet-b2	.849
216	inception_v1	.849
217	yudixie_resnet18_translation_reg_0_240719	.849
218	resnet50_primary_visual_cortex	.847
219	resnet50_robust_l2_eps1	.848
220	dinov2_vitl14_lc_res336	.845
221	0.5x_resnet-18_LC_w_sh_100_iter	.843
222	ReAlnet07	.842
223	resnet50-vicreg	.842
224	ReAlnet03	.842
225	resnet50-SIN_IN_IN	.841
226	ReAlnet07_cornet	.840
227	ReAlnet03_cornet	.838
228	mobilenet_v2_0.75_224-tf	.838
229	compact_cornets_V4	.838
230	ReAlnet04	.838
231	yudixie_resnet18_translation_rotation_0_240719	.838
232	antialiased-rnext101_32x8d	.837
233	ReAlnet04_cornet	.836
234	vgg-16-keras	.836
235	SWSL_resnext101_32x8d	.836
236	ReAlnet10_cornet	.835
237	mehrer2020_alexnet_training_seed_03	.835
238	ReAlnet10	.834
239	AlexNet_SIN_fov16	.834
240	effnetb1_272x240	.833
241	compact_resnet50_robust_V4	.833
242	resnet-101_v1-tf	.832
243	resnet-152_v2_pytorch	.832
244	densenet-201	.831
245	cv_18_dagger_408_pretrained	.831
246	mobilenet_v2_1_0_160	.830
247	pnasnet_large_halfPrecision	.829
248	pnasnet_large-tf	.829
249	mobilenet_v2_1_3_224	.830
250	ReAlnet08_cornet	.829
251	ReAlnet08	.828
252	deepeisnn_ei_cifar10_vgg19	.827
253	convnext_femto_ols:d1_in1k	.826
254	ReAlnet05_cornet	.826
255	ReAlnet05	.826
256	convnext_base_fb_in1k_gram_aligned_dinov3	.826
257	mehrer2020_alexnet_training_seed_09	.825
258	densenet-201-keras	.823
259	alexnet_fov12	.823
260	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.821
261	mobilenet_v2_1.0_128-tf	.822
262	mobilenet_v2_1_0_192	.820
263	vit_base_patch16_clip_224:openai_ft_in1k	.819
264	resnet50-barlow	.819
265	briaai_rmbg_1_4	.819
266	resnet50_hvs_wzc	.819
267	eBarlow_lmda_02_1000ep	.818
268	0.5x_resnet-18	.817
269	ReAlnet02	.816
270	eva02_large_in22k	.816
271	BiT-S-R101x1	.816
272	ReAlnet02_cornet	.815
273	AlexNet_SIN_fov4	.814
274	konkle_alexnetgn_ipcl_ref01_primary_model	.813
275	resnet50-SIN	.813
276	deepeisnn_ei_imagenet_resnet18	.813
277	ReAlnet06	.813
278	BiT-S-R152x4	.811
279	BiT-M-R152x2	.811
280	ReAlnet06_cornet	.811
281	resnet50_imagenet_10_seed-0	.811
282	vit_huge_clip336_laion	.810
283	yudixie_wbh_object_class_scaling_0415_run_1	.811
284	densenet-169-keras	.810
285	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.810
286	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.807
287	0.5x_resnet-18_LC	.808
288	yudixie_resnet18_category_class_0_240719	.807
289	FrankRobWobv0	.807
290	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.806
291	convnext_base_fb_in1k	.804
292	mobilenet_v2_0_5_224	.804
293	AlexNet_SIN	.803
294	regnety_032	.802
295	BiT-M-R152x4	.802
296	resnet-50-robust	.801
297	compact_resnet50_V4	.799
298	resnet50_simclr	.795
299	convnext_large:fb_in22k_ft_in1k	.794
300	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.794
301	resnet50_moco_v2	.794
302	resnet-18-LC_d_w_sh_1x1_conv_init_m	.794
303	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.790
304	seresnext50_32x4d	.790
305	mobilenet_v2_0_5_192	.790
306	AlexNet_SIN_fov12	.790
307	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.788
308	vit_large_patch14_clip_224:laion2b_ft_in1k	.788
309	alexnet_training_seed_07	.787
310	0.5x_resnet-18_LC_w_sh_10_iter	.787
311	texture_shape_resnet50_trained_on_SIN	.786
312	yudixie_resnet18_random_0_240719	.785
313	mobilenet_v2_0_75_160	.783
314	efficientnet_b1_imagenet_full	.784
315	my-model	.783
316	shufflenet_v2_x1_0	.782
317	ViT-B/32	.781
318	yudixie_resnet50_object_class_0_240908	.779
319	yudixie_resnet18_object_class_0_240719	.778
320	mobilenet_v2_0_75_224	.777
321	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.777
322	resnet18_fair	.777
323	yudixie_resnet50_category_class_0_240908	.776
324	vgg-19-keras	.774
325	vit_relpos_base_patch16_clsgap_224:sw_in1k	.774
326	alexnet_training_seed_09	.774
327	nasnet_mobile-tf	.769
328	vit_large_patch14_clip_336:laion2b_ft_in1k	.764
329	vit_large_patch14_clip_224:openai_ft_in1k	.762
330	efficientnet_b0	.762
331	convnext_small_imagenet_full_seed-0	.761
332	alexnet_fov4	.762
333	cvt_cvt-13-384-in1k_4_LucyV4	.760
334	inception_v1-tf	.759
335	mobilenet_v2_1-4_224_pytorch	.753
336	alexnet_training_seed_04	.753
337	vit_base_patch14_reg4_dinov2-lvd142m	.751
338	custom_model_cv_18_dagger_408	.751
339	ReAlnet01_cornet_fov4	.749
340	alexnet_training_seed_01_fov16	.746
341	vit_large_clip336_openai	.745
342	densenet-121-keras	.743
343	yudixie_resnet18_imagenet1kpret_0_240719	.741
344	yudixie_wbh_object_class_scaling_0415_imagenet	.740
345	mobilenet_v2_0.35_224	.740
346	deit_small_imagenet_full_seed-0	.739
347	mobilenet_v2_1_0_128	.739
348	alexnet_training_seed_01	.739
349	resnet50_ecoset_full	.739
350	alexnet_training_seed_02	.739
351	nasnet_mobile	.734
352	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.730
353	inception_resnet_v2	.728
354	vision_transformer_vit_large_patch16_224	.728
355	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.724
356	resnet-152_v1-tf	.722
357	mobilenet_v2_0.75_96	.719
358	yudixie_wbh_object_class_scaling_0415_run_0	.719
359	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.718
360	vonegrcnn_52e_full	.714
361	resnet-18-LC_m	.710
362	CORnet-Z	.706
363	vonegrcnn_47e	.705
364	efficientnet_b0_imagenet_full	.702
365	resnet18-supervised	.702
366	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.701
367	vonegrcnn_47e	.700
368	resnet50_imagenet_full	.698
369	convnext_small_imagenet_10_seed-0	.692
370	alexnet_training_seed_10	.691
371	alexnet_reduced_aliasing_early_checkpoint	.683
372	alexnet_training_seed_03	.674
373	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.671
374	mobilenet_v2_0.5_224-tf	.670
375	alexnet_training_seed_01_fov4	.669
376	vit_base_patch14_dinov2-lvd142m	.659
377	deit_base_imagenet_full_seed-0	.658
378	resnet-18-LC_conv_init_m	.648
379	eicircuit_resnet18_bn_20260919	.647
380	ijepa_vith14_linhead	.648
381	efficientnet_b2_imagenet_full	.647
382	hmax	.644
383	mobilenet_v2_1_0_224	.641
384	dinov2_vitg14_reg_lc	.640
385	dinov2_vitl14_lc	.618
386	mobilenet_v1_0.25_128	.612
387	dinov2_vitl14_reg_lc_featread	.607
388	dinov2_vitl14_reg_lc	.606
389	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.601
390	deit3_base_patch16_224_fb_in1k	.601
391	mobilenet_v2_0.5_192-tf	.600
392	BiT-M-R50x1	.597
393	v1-pyr-nodown	.581
394	r3m_resnet34_nocrop	.566
395	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.563
396	deit3_base_patch16_224_fb_in22k_ft_in1k	.563
397	CORnetZ_CIFAR10	.554
398	artResNet18_1	.548
399	mobilenet_v2_0.5_160	.518
400	r3m_resnet50_nocrop	.517
401	VOneCORnet-S	.511
402	r3m_resnet34	.505
403	vit_base_patch16_dinov3-lvd1689m	.504
404	voneresnet-50	.494
405	voneresnet-50-robust	.491
406	gabor_filter_entropy_4x4_v2_forcedCosine	.490
407	gabor_filter_mean_abs_4x4_v2	.487
408	r3m_resnet50	.483
409	deit_small_imagenet_100_seed-0	.447
410	mobilenet_v2_0.75_128	.441
411	mobilenet_v2_0.75_160-tf	.440
412	alexnet_training_seed_08	.432
413	resnet50_pretrained_with_retinal_waves	.428
414	r3m_resnet18	.427
415	deit_small_imagenet_10_seed-0	.393
416	mobilenet_v2_0.5_128	.393
417	resnet50-cifar	.393
418	resnet50_imagenet_1_seed-0	.387
419	deit_large_imagenet_full_seed-0	.386
420	alexnet_training_seed_05	.297
421	resnet-18-LC_untrained	.262
422	alexnet_training_seed_06	.254
423	CORnetZ_CIFAR10_bs32_20_04	.229
424	my-model	.150
425	gabor_filter_entropy_4x4	.000
426	gabor_filter_entropy_4x4_v2	.000
427	mobilenet_v2_0.35_160
428	fitvid_trained_on_physion
429	openclip
430	fixres_resnext101_32x48d_wsl
431	resnet50_ImageNet
432	regnet_y_400mf
433	tv_efficientnet-b1
434	alexnet_ks_torevert
435	yudixie_resnet50_imagenet1kpret_0_240312
436	resnet_152_v1
437	densenet_201_pytorch
438	inception_v3_pytorch
439	pnasnet_large_pytorch
440	mobilevit_small
441	inception_v4
442	nasnet_large
443	deit_small_imagenet_1_seed-0
444	pnasnet_large
445	vonegrcnn_62e_nobn
446	resnet_101_v2
447	vonegrcnn_52e_full
448	resnet_152_v2
449	resnet50_simclr_linhead_01norm
450	mehrer2020_alexnet_training_seed_01
451	mehrer2020_alexnet_training_seed_01_fov4
452	mehrer2020_alexnet_training_seed_02
453	mehrer2020_alexnet_training_seed_01_fov16
454	mehrer2020_alexnet_training_seed_04
455	mehrer2020_alexnet_training_seed_05
456	mehrer2020_alexnet_training_seed_06
457	mehrer2020_alexnet_training_seed_10
458	pr1_stl10_disentangled_alpha04
459	predictive_coding_pc
460	dinov2_vitg14_lc

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_bandwidth