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

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_bandwidth