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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	resnet50_ewconplus_wzc_seed7_2_323	.946
19	yudixie_resnet50_distance_translation_0_240908	.945
20	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.945
21	omnivore_swinB	.944
22	resnet-18-LC_w_sh_100_iter_m	.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	resnet50	.930
40	resnet-50_untrained	.930
41	resnet50_ewconplus_wzc_seed2_2__323	.930
42	ReAlnet08_ALL	.931
43	cvt_cvt-21-224-in1k_4_LucyV4	.928
44	ReAlnet02_ALL	.930
45	resnet-18-LC_w_sh_1_iter_m	.928
46	AdvProp_efficientnet-b8	.928
47	resnet50-SIN_IN	.927
48	ReAlnet05_ALL	.927
49	resnet18_imagenet_full	.926
50	ReAlnet10_ALL	.927
51	cvt_cvt-21-384-in1k_4_LucyV4	.927
52	mobilenet_v2_1.3_224-tf	.925
53	resnet50-moclr8deg	.924
54	resnet-50_v1-tf	.923
55	BiT-S-R101x3	.923
56	vgg_19	.922
57	resnet-152_v2-tf	.922
58	compact_cornets_IT	.921
59	convnext_base_imagenet_full_seed-0	.920
60	xception	.920
61	voneresnet-50-non_stochastic	.920
62	compact_vgg19_IT	.919
63	resnet50_st_wzc_2_323	.917
64	alexnet_early_checkpoint	.917
65	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.917
66	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.917
67	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.916
68	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.916
69	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.915
70	alexnet_training_seed_01_fov12	.915
71	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.915
72	ReAlnet07_ALL	.916
73	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.915
74	mobilenet_v2_1.4_224-tf	.915
75	antialias-resnet152	.914
76	inception_v4-tf	.913
77	Res2Net50_26w_4s	.913
78	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.913
79	inception_v3-tf	.911
80	yudixie_resnet50_distance_rotation_0_240908	.911
81	yudixie_resnet50_translation_reg_0_240908	.911
82	resnet50_ewconplus_noseed_2_323	.911
83	focalnet_tiny_lrf_in1k	.911
84	yudixie_resnet50_distance_translation_rotation_0_240908	.910
85	resnet50_st_wzc_seed7_2_323	.910
86	BiT-M-R101x1	.910
87	yudixie_wbh_object_class_scaling_0415_run_3	.911
88	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.910
89	resnet50-simclr-vissl	.909
90	yudixie_resnet50_rotation_reg_0_240908	.909
91	vgg_16	.907
92	resnet50_l2_3_robust	.907
93	resnet-18_test_m	.906
94	BiT-M-R50x3	.907
95	texture_shape_alexnet_trained_on_SIN	.906
96	resnet50_st_wzc_seed3_2_323	.906
97	inception_v2-tf	.905
98	CORnet-S	.905
99	blt_vs	.904
100	resnext101_32x8d_wsl	.904
101	omnivore_swinT	.904
102	0.5x_resnet-18_LC_w_sh_1_iter	.904
103	resnet34_ecoset_full	.903
104	alexnet_random_l2_3_perturb	.902
105	resnet-50x2_untrained	.903
106	resnet50_byol	.901
107	BiT-S-R50x3	.900
108	resnet50_random_linf8_perturb	.900
109	vonealexnet_gaussian_noise_std4_fixed	.899
110	compact_resnet50_IT	.899
111	resnet101_ecoset_full	.897
112	SWSL_resnet50	.896
113	mobilenet_v2_1.0_160-tf	.896
114	resnet50_ewconplus_wzc_seed6_2_323	.895
115	AdvProp_efficientnet-b7	.895
116	convnext_tiny:in12k_ft_in1k	.893
117	resnet50-vicregl0p9	.892
118	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.892
119	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.891
120	alexnet_linf_8_robust	.890
121	BiT-S-R152x2	.889
122	resnet50_st_wzc_noseed_2_323	.889
123	resnet-18-LC_1st_conv_m	.889
124	resnet50-vicregl0p75	.888
125	imagenet_l2_3_0	.888
126	barlow-twins-resnet50	.888
127	yudixie_resnet50_distance_reg_0_240908	.888
128	resnet50_robust_l2_eps3	.886
129	resnet152_ecoset_full	.887
130	resnet50_st_wzc_seed4_2_323	.886
131	BiT-M-R101x3	.885
132	resnet50_st_wzc_seed5_2_323	.885
133	resnet-18-LC_w_sh_100_iter_conv_init_m	.885
134	alexnet_random_linf8_perturb	.883
135	grcnn	.884
136	compact_resnet50_robust_IT	.882
137	ViT_L_32_imagenet1k	.882
138	resnet_50_v2	.881
139	grcnn_robust_v1	.883
140	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.881
141	yudixie_resnet50_random_0_240908	.879
142	CLIP-RN50	.879
143	ReAlnet01_cornet_fov12	.878
144	resnet50_imagenet_100_seed-0	.879
145	ReAlnet01_cornet_fov16	.879
146	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.878
147	resnet50_ewconplus_wzc_seed5_2__323	.877
148	resnet_50_v1_spiking	.877
149	resnet_50_v1_spiking_l4	.876
150	yudixie_resnet50_imagenet1kpret_0_240908	.876
151	resnet_50_v1_spiking_l4a	.876
152	alexnet	.876
153	alexnet_fov16	.876
154	resnet50_tutorial	.875
155	resnet50_ewconplus_wzc_seed3_2_323	.876
156	resnet_50_v1	.875
157	grcnn_v2_text_noise	.875
158	resnet_50_v1_spiking_l3	.874
159	resnet50	.874
160	resnet18_imagenet21kP	.874
161	yolos_tiny	.874
162	yudixie_wbh_object_class_scaling_0415_run_2	.874
163	resnet50-sup	.874
164	grcnn_109	.872
165	mobilenet_v2_0.75_192-tf	.873
166	mobilenet_v2_1.0_224-tf	.871
167	resnet50_linf_8_robust	.871
168	CLIP_resnet50	.871
169	imagenet_l2_10_0	.870
170	resnet50-vitoimagevidnet8	.870
171	cornet_s	.869
172	deepeisnn_ei_cifar10_resnet18	.869
173	resnet18_ecoset_full	.867
174	convnext_tiny_imagenet_full_seed-0	.868
175	CLIP_resnet50_float32	.867
176	mobilenet_v2_0_75_192	.867
177	resnet-101_v2-tf	.866
178	densenet-169	.866
179	convnext_tiny_sup	.865
180	resnet50_ewconplus_wzc	.865
181	CLIP_ViT-B_32	.864
182	resnet-18-LC_w_sh_10_iter_m	.863
183	RN50	.863
184	AdvProp_efficientnet-b4	.861
185	resnet152_imagenet_full	.861
186	convnext_xlarge:fb_in22k_ft_in1k	.861
187	resnet50-VITO-8deg-cc	.859
188	ReAlnet09	.860
189	convnext_small_imagenet_1_seed-0	.859
190	mobilenet_v2_1_4_224	.858
191	ReAlnet09_cornet	.858
192	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.857
193	resnet101_imagenet_full	.857
194	resnet-18_untrained	.857
195	resnet50_linf_4_robust	.857
196	resnet50_FractalDB	.856
197	ReAlnet01	.855
198	mobilenet_v2_1.0_192-tf	.855
199	AdvProp_efficientnet-b0	.854
200	densenet-121	.854
201	convnext_small_imagenet_100_seed-0	.854
202	resnet-50_v2-tf	.853
203	resnet50_random_l2_perturb	.853
204	resnet_SIN_IN_FT_IN	.852
205	ReAlnet01_cornet	.853
206	AdvProp_efficientnet-b2	.852
207	effnetv2m_custom384	.852
208	inception_v3	.851
209	antialiased-r50	.852
210	AT_efficientnet-b2	.849
211	inception_v1	.849
212	yudixie_resnet18_translation_reg_0_240719	.849
213	resnet50_primary_visual_cortex	.847
214	resnet50_robust_l2_eps1	.848
215	0.5x_resnet-18_LC_w_sh_100_iter	.843
216	ReAlnet07	.842
217	resnet50-vicreg	.842
218	ReAlnet03	.842
219	resnet50-SIN_IN_IN	.841
220	resnet50_ewconplus_wzc_2_323	.841
221	ReAlnet07_cornet	.840
222	ReAlnet03_cornet	.838
223	mobilenet_v2_0.75_224-tf	.838
224	compact_cornets_V4	.838
225	ReAlnet04	.838
226	yudixie_resnet18_translation_rotation_0_240719	.838
227	antialiased-rnext101_32x8d	.837
228	ReAlnet04_cornet	.836
229	vgg-16-keras	.836
230	SWSL_resnext101_32x8d	.836
231	ReAlnet10_cornet	.835
232	ReAlnet10	.834
233	AlexNet_SIN_fov16	.834
234	effnetb1_272x240	.833
235	compact_resnet50_robust_V4	.833
236	resnet-101_v1-tf	.832
237	resnet-152_v2_pytorch	.832
238	densenet-201	.831
239	cv_18_dagger_408_pretrained	.831
240	mobilenet_v2_1_0_160	.830
241	pnasnet_large_halfPrecision	.829
242	pnasnet_large-tf	.829
243	mobilenet_v2_1_3_224	.830
244	ReAlnet08_cornet	.829
245	ReAlnet08	.828
246	deepeisnn_ei_cifar10_vgg19	.827
247	convnext_femto_ols:d1_in1k	.826
248	ReAlnet05_cornet	.826
249	ReAlnet05	.826
250	convnext_base_fb_in1k_gram_aligned_dinov3	.826
251	densenet-201-keras	.823
252	alexnet_fov12	.823
253	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.821
254	mobilenet_v2_1.0_128-tf	.822
255	mobilenet_v2_1_0_192	.820
256	vit_base_patch16_clip_224:openai_ft_in1k	.819
257	resnet50-barlow	.819
258	briaai_rmbg_1_4	.819
259	eBarlow_lmda_02_1000ep	.818
260	0.5x_resnet-18	.817
261	ReAlnet02	.816
262	BiT-S-R101x1	.816
263	ReAlnet02_cornet	.815
264	AlexNet_SIN_fov4	.814
265	konkle_alexnetgn_ipcl_ref01_primary_model	.813
266	resnet50-SIN	.813
267	deepeisnn_ei_imagenet_resnet18	.813
268	ReAlnet06	.813
269	BiT-S-R152x4	.811
270	BiT-M-R152x2	.811
271	ReAlnet06_cornet	.811
272	resnet50_imagenet_10_seed-0	.811
273	yudixie_wbh_object_class_scaling_0415_run_1	.811
274	densenet-169-keras	.810
275	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.810
276	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.807
277	0.5x_resnet-18_LC	.808
278	yudixie_resnet18_category_class_0_240719	.807
279	FrankRobWobv0	.807
280	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.806
281	convnext_base_fb_in1k	.804
282	resnet50_ewconplus_wzc_seed4_2_323	.803
283	mobilenet_v2_0_5_224	.804
284	AlexNet_SIN	.803
285	BiT-M-R152x4	.802
286	resnet-50-robust	.801
287	compact_resnet50_V4	.799
288	resnet50_simclr	.795
289	convnext_large:fb_in22k_ft_in1k	.794
290	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.794
291	resnet50_moco_v2	.794
292	resnet-18-LC_d_w_sh_1x1_conv_init_m	.794
293	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.790
294	mobilenet_v2_0_5_192	.790
295	AlexNet_SIN_fov12	.790
296	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.788
297	vit_large_patch14_clip_224:laion2b_ft_in1k	.788
298	alexnet_training_seed_07	.787
299	0.5x_resnet-18_LC_w_sh_10_iter	.787
300	texture_shape_resnet50_trained_on_SIN	.786
301	yudixie_resnet18_random_0_240719	.785
302	mobilenet_v2_0_75_160	.783
303	efficientnet_b1_imagenet_full	.784
304	my-model	.783
305	shufflenet_v2_x1_0	.782
306	ViT-B/32	.781
307	yudixie_resnet50_object_class_0_240908	.779
308	yudixie_resnet18_object_class_0_240719	.778
309	mobilenet_v2_0_75_224	.777
310	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.777
311	resnet18_fair	.777
312	yudixie_resnet50_category_class_0_240908	.776
313	vgg-19-keras	.774
314	vit_relpos_base_patch16_clsgap_224:sw_in1k	.774
315	alexnet_training_seed_09	.774
316	nasnet_mobile-tf	.769
317	vit_large_patch14_clip_336:laion2b_ft_in1k	.764
318	vit_large_patch14_clip_224:openai_ft_in1k	.762
319	efficientnet_b0	.762
320	convnext_small_imagenet_full_seed-0	.761
321	alexnet_fov4	.762
322	cvt_cvt-13-384-in1k_4_LucyV4	.760
323	inception_v1-tf	.759
324	mobilenet_v2_1-4_224_pytorch	.753
325	alexnet_training_seed_04	.753
326	vit_base_patch14_reg4_dinov2-lvd142m	.751
327	custom_model_cv_18_dagger_408	.751
328	ReAlnet01_cornet_fov4	.749
329	alexnet_training_seed_01_fov16	.746
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	aughost_fair_resnet18	.734
340	nasnet_mobile	.734
341	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.730
342	inception_resnet_v2	.728
343	vision_transformer_vit_large_patch16_224	.728
344	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.724
345	resnet-152_v1-tf	.722
346	mobilenet_v2_0.75_96	.719
347	yudixie_wbh_object_class_scaling_0415_run_0	.719
348	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.718
349	vonegrcnn_52e_full	.714
350	resnet-18-LC_m	.710
351	CORnet-Z	.706
352	vonegrcnn_47e	.705
353	efficientnet_b0_imagenet_full	.702
354	resnet18-supervised	.702
355	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.701
356	vonegrcnn_47e	.700
357	resnet50_imagenet_full	.698
358	convnext_small_imagenet_10_seed-0	.692
359	alexnet_training_seed_10	.691
360	alexnet_reduced_aliasing_early_checkpoint	.683
361	alexnet_training_seed_03	.674
362	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.671
363	mobilenet_v2_0.5_224-tf	.670
364	alexnet_training_seed_01_fov4	.669
365	vit_base_patch14_dinov2-lvd142m	.659
366	deit_base_imagenet_full_seed-0	.658
367	resnet-18-LC_conv_init_m	.648
368	efficientnet_b2_imagenet_full	.647
369	hmax	.644
370	mobilenet_v2_1_0_224	.641
371	mobilenet_v1_0.25_128	.612
372	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.601
373	deit3_base_patch16_224_fb_in1k	.601
374	mobilenet_v2_0.5_192-tf	.600
375	BiT-M-R50x1	.597
376	v1-pyr-nodown	.581
377	r3m_resnet34_nocrop	.566
378	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.563
379	deit3_base_patch16_224_fb_in22k_ft_in1k	.563
380	CORnetZ_CIFAR10	.554
381	artResNet18_1	.548
382	mobilenet_v2_0.5_160	.518
383	r3m_resnet50_nocrop	.517
384	VOneCORnet-S	.511
385	r3m_resnet34	.505
386	vit_base_patch16_dinov3-lvd1689m	.504
387	voneresnet-50	.494
388	voneresnet-50-robust	.491
389	r3m_resnet50	.483
390	deit_small_imagenet_100_seed-0	.447
391	mobilenet_v2_0.75_128	.441
392	mobilenet_v2_0.75_160-tf	.440
393	alexnet_training_seed_08	.432
394	resnet50_pretrained_with_retinal_waves	.428
395	r3m_resnet18	.427
396	deit_small_imagenet_10_seed-0	.393
397	mobilenet_v2_0.5_128	.393
398	resnet50-cifar	.393
399	resnet50-meshes-lt-100-original-pretrained	.389
400	resnet50_imagenet_1_seed-0	.387
401	deit_large_imagenet_full_seed-0	.386
402	alexnet_training_seed_05	.297
403	resnet-18-LC_untrained	.262
404	alexnet_training_seed_06	.254
405	CORnetZ_CIFAR10_bs32_20_04	.229
406	my-model	.150
407	resnet50-meshes-lt-100-original-scratch	.108
408	mobilenet_v2_0.35_160
409	fitvid_trained_on_physion
410	openclip
411	resnext101_32x32d_wsl
412	resnext101_32x16d_wsl
413	resnext101_32x48d_wsl
414	fixres_resnext101_32x48d_wsl
415	resnet50_ImageNet
416	regnet_y_400mf
417	tv_efficientnet-b1
418	alexnet_ks_torevert
419	yudixie_resnet50_imagenet1kpret_0_240312
420	resnet_152_v1
421	densenet_201_pytorch
422	inception_v3_pytorch
423	pnasnet_large_pytorch
424	mobilevit_small
425	inception_v4
426	nasnet_large
427	deit_small_imagenet_1_seed-0
428	pnasnet_large
429	vonegrcnn_62e_nobn
430	resnet_101_v2
431	vonegrcnn_52e_full
432	resnet_152_v2
433	pr1_stl10_disentangled_alpha04
434	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_bandwidth