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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_m	.983
2	yudixie_resnet50_rotation_reg_0_240908	.974
3	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.973
4	yudixie_resnet18_category_class_0_240719	.971
5	vonegrcnn_62e_nobn	.958
6	cvt_cvt-21-384-in1k_4_LucyV4	.954
7	0.5x_resnet-18_LC_w_sh_10_iter	.954
8	yudixie_resnet50_distance_translation_rotation_0_240908	.953
9	efficientnet_b1_imagenet_full	.949
10	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.949
11	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.943
12	convnext_large:fb_in22k_ft_in1k	.944
13	convnext_femto_ols:d1_in1k	.941
14	yudixie_resnet50_category_class_0_240908	.938
15	yudixie_resnet18_translation_reg_0_240719	.938
16	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.937
17	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.937
18	xception	.937
19	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.937
20	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.936
21	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.936
22	cvt_cvt-21-224-in1k_4_LucyV4	.935
23	yudixie_resnet50_distance_rotation_0_240908	.932
24	cvt_cvt-13-224-in1k_4_LucyV4	.933
25	compact_vgg19_V4	.932
26	blt_vs	.931
27	yudixie_resnet50_translation_rotation_0_240908	.928
28	mobilenet_v2_1.3_224-tf	.930
29	mobilenet_v2_1_0_128	.929
30	inception_v1	.926
31	resnet-18-LC_w_sh_1_iter_m	.926
32	resnet-18-LC_1st_conv_m	.926
33	briaai_rmbg_1_4	.926
34	resnet-152_v2-tf	.922
35	vgg_19	.921
36	AdvProp_efficientnet-b6	.921
37	compact_cornets_V4	.921
38	efficientnet-b7	.918
39	AlexNet_SIN	.919
40	resnet50_ewconplus_wzc_seed7_2_323	.917
41	BiT-M-R50x3	.916
42	resnet-18-LC_d_w_sh_1x1_conv_init_m	.916
43	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.915
44	compact_resnet50_V4	.915
45	compact_cornets_IT	.914
46	ReAlnet01_cornet_fov4	.914
47	alexnet	.912
48	yudixie_resnet18_translation_rotation_0_240719	.911
49	convnext_base:clip_laiona_augreg_ft_in1k_384	.911
50	grcnn	.911
51	resnet50_st_wzc_seed4_2_323	.909
52	alexnet_robust_correct	.909
53	resnet50_ewconplus_wzc_2_323	.908
54	texture_shape_alexnet_trained_on_SIN	.906
55	resnext101_32x8d_wsl	.905
56	alexnet_random_l2_3_perturb	.903
57	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.903
58	resnet50_ewconplus_wzc_seed3_2_323	.903
59	resnet50_ewconplus_wzc	.902
60	resnet-18-LC_w_sh_10_iter_conv_init_m	.903
61	focalnet_tiny_lrf_in1k	.901
62	yudixie_resnet18_object_class_0_240719	.901
63	mobilenet_v2_1.0_160-tf	.901
64	yudixie_resnet50_distance_reg_0_240908	.901
65	AdvProp_efficientnet-b8	.900
66	resnet50_st_wzc_seed7_2_323	.898
67	omnivore_swinS	.898
68	compact_resnet50_robust_V4	.895
69	resnet50_primary_visual_cortex	.896
70	Res2Net50_26w_4s	.896
71	BiT-S-R50x1	.895
72	resnet50_imagenet_100_seed-0	.894
73	mobilenet_v2_1.0_224-tf	.893
74	yudixie_resnet50_distance_translation_0_240908	.892
75	resnet-18-LC_w_sh_100_iter_conv_init_m	.893
76	alexnet_fov4	.892
77	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.889
78	convnext_base_fb_in22k_ft_in1k	.889
79	grcnn_robust_v1	.887
80	yudixie_wbh_object_class_scaling_0415_run_0	.888
81	yudixie_resnet18_distance_rotation_0_240719	.886
82	deepeisnn_ei_cifar10_vgg19	.885
83	resnet101	.887
84	compact_vgg19_IT	.885
85	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.885
86	resnet50_st_wzc_seed6_2_323	.885
87	0.5x_resnet-18_LC_w_sh_100_iter	.884
88	resnet50_st_wzc_noseed_2_323	.880
89	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
90	resnet50-vitoimagevidnet8	.876
91	yudixie_resnet50_translation_reg_0_240908	.876
92	resnet50_ewconplus_wzc_seed6_2_323	.875
93	omnivore_swinB	.874
94	vgg-16-keras	.874
95	alexnet_reduced_aliasing_early_checkpoint	.874
96	barlow-twins-resnet50	.873
97	resnet50_ewconplus_wzc_seed5_2__323	.873
98	resnet18_ecoset_full	.872
99	compact_resnet50_IT	.872
100	vgg_16	.871
101	grcnn_109	.870
102	resnet50_st_wzc_seed5_2_323	.870
103	resnet50_byol	.868
104	resnet50-SIN_IN	.867
105	convnext_small_imagenet_full_seed-0	.867
106	resnet18_fair	.868
107	CORnet-Z	.867
108	resnet50_st_wzc_2_323	.867
109	grcnn_v2_text_noise	.866
110	alexnet_random_linf8_perturb	.864
111	resnet50_st_wzc_seed3_2_323	.862
112	resnet_50_v2	.862
113	resnet-50_v1-tf	.861
114	alexnet_l2_3_robust	.860
115	resnet-18-LC_w_sh_10_iter_m	.859
116	0.5x_resnet-18_LC_w_sh_1_iter	.858
117	ReAlnet04	.857
118	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.857
119	ReAlnet04_cornet	.857
120	ReAlnet03	.855
121	ReAlnet03_cornet	.856
122	ReAlnet01_cornet_fov16	.855
123	0.5x_resnet-18_LC	.853
124	BiT-M-R101x1	.853
125	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.852
126	resnet50_ewconplus_noseed_2_323	.851
127	inception_v3-tf	.850
128	CORnetZ_CIFAR10_bs32_20_04	.850
129	ReAlnet01	.850
130	resnet50-vicregl0p9	.850
131	ReAlnet08_cornet	.849
132	ReAlnet08	.850
133	ReAlnet01_cornet	.847
134	ReAlnet09	.846
135	ReAlnet09_cornet	.847
136	convnext_tiny_imagenet_full_seed-0	.847
137	resnet50-simclr-vissl	.847
138	ReAlnet02	.847
139	ReAlnet07	.847
140	ReAlnet02_cornet	.846
141	yudixie_resnet50_object_class_0_240908	.846
142	ReAlnet07_cornet	.846
143	inception_v3	.845
144	yudixie_wbh_object_class_scaling_0415_run_3	.844
145	alexnet_linf_8_robust	.844
146	yudixie_resnet18_distance_translation_rotation_0_240719	.843
147	BiT-S-R50x3	.844
148	ReAlnet10	.843
149	nasnet_large-tf	.842
150	resnet18_imagenet21kP	.841
151	vonealexnet_gaussian_noise_std4_fixed	.839
152	ReAlnet10_cornet	.839
153	alexnet_early_checkpoint	.838
154	compact_resnet50_robust_IT	.837
155	BiT-S-R101x3	.837
156	resnet50_imagenet_10_seed-0	.837
157	ReAlnet06_cornet	.835
158	ReAlnet06	.836
159	AlexNet_SIN_fov4	.835
160	ReAlnet05	.833
161	ReAlnet05_cornet	.832
162	yudixie_wbh_object_class_scaling_0415_run_1	.832
163	resnet101_imagenet_full	.829
164	convnext_tiny_sup	.829
165	antialias-resnet152	.827
166	yudixie_resnet18_distance_translation_0_240719	.826
167	densenet-201	.826
168	convnext_small_imagenet_100_seed-0	.825
169	resnet_50_v1_spiking_l4a	.824
170	resnet_50_v1	.824
171	resnet_50_v1_spiking	.823
172	yudixie_wbh_object_class_scaling_0415_run_2	.823
173	resnet50_ewconplus_wzc_seed2_2__323	.822
174	yudixie_resnet50_imagenet1kpret_0_240908	.821
175	resnet50_tutorial	.822
176	resnet50-sup	.821
177	resnet_50_v1_spiking_l4	.821
178	alexnet_fov12	.821
179	densenet-201-keras	.821
180	AlexNet_SIN_fov12	.820
181	resnet_50_v1_spiking_l3	.820
182	AdvProp_efficientnet-b7	.819
183	resnet50_ewconplus_wzc_seed4_2_323	.819
184	CORnet-S	.816
185	mobilenet_v2_0_75_192	.817
186	convnext_xlarge:fb_in22k_ft_in1k	.817
187	resnet50-moclr8deg	.814
188	resnet-50_untrained	.815
189	ReAlnet07_ALL	.814
190	resnet50-vicregl0p75	.812
191	CLIP-RN50	.811
192	imagenet_l2_10_0	.810
193	ReAlnet03_ALL	.810
194	vgg-19-keras	.810
195	imagenet_l2_3_0	.810
196	ReAlnet04_ALL	.809
197	ReAlnet08_ALL	.808
198	RN50	.807
199	resnet50	.807
200	ReAlnet10_ALL	.807
201	resnet-50x2_untrained	.806
202	mobilenet_v2_1_4_224	.806
203	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.805
204	inception_v4-tf	.804
205	ReAlnet05_ALL	.804
206	resnet50_st_wzc_2	.804
207	cornet_s	.803
208	ReAlnet09_ALL	.802
209	ReAlnet02_ALL	.802
210	ReAlnet01_ALL	.802
211	resnet50-SIN_IN_IN	.800
212	resnet-50-robust	.800
213	mobilenet_v2_1_3_224	.799
214	resnet50_robust_l2_eps1	.796
215	resnet50_random_linf8_perturb	.795
216	deit_small_imagenet_full_seed-0	.795
217	r3m_resnet34_nocrop	.795
218	ReAlnet06_ALL	.795
219	alexnet_fov16	.793
220	resnet50_l2_3_robust	.792
221	resnet50_linf_8_robust	.787
222	deepeisnn_ei_cifar10_resnet18	.786
223	BiT-S-R152x2	.786
224	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.785
225	convnext_base_fb_in1k	.784
226	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.784
227	resnet50_robust_l2_eps3	.783
228	antialiased-r50	.782
229	resnet50_random_l2_perturb	.780
230	resnet_SIN_IN_FT_IN	.779
231	yudixie_wbh_object_class_scaling_0415_imagenet	.779
232	resnet50-vicreg	.779
233	yudixie_resnet18_imagenet1kpret_0_240719	.779
234	resnet34_imagenet_full	.778
235	resnet18_imagenet_full	.776
236	efficientnet_b0	.775
237	convnext_large_imagenet_full_seed-0	.775
238	convnext_base_imagenet_full_seed-0	.772
239	mobilenet_v2_1.0_96	.772
240	VOneCORnet-S	.772
241	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.769
242	texture_shape_resnet50_trained_on_SIN	.769
243	vit_base_patch16_clip_224:openai_ft_in1k	.769
244	densenet-121	.767
245	mobilenet_v2_0_5_224	.767
246	inception_v2-tf	.766
247	voneresnet-50-robust	.764
248	voneresnet-50	.758
249	mobilenet_v2_0.75_192-tf	.757
250	resnet50_linf_4_robust	.756
251	CLIP_resnet50	.756
252	ReAlnet01_cornet_fov12	.755
253	convnext_tiny:in12k_ft_in1k	.755
254	CLIP_resnet50_float32	.755
255	AdvProp_efficientnet-b4	.754
256	mobilenet_v2_1.4_224-tf	.755
257	densenet-169	.754
258	aughost_fair_resnet18	.753
259	resnet50_ecoset_full	.752
260	resnet-18_untrained	.749
261	deepeisnn_ei_imagenet_resnet18	.750
262	resnet50-VITO-8deg-cc	.747
263	0.5x_resnet-18	.745
264	resnet50-cifar	.743
265	resnet50-SIN	.741
266	SWSL_resnet50	.741
267	resnet50_imagenet_full	.741
268	alexnet_training_seed_01_fov16	.741
269	alexnet_training_seed_01_fov12	.738
270	mobilenet_v2_0_75_224	.739
271	AdvProp_efficientnet-b0	.738
272	resnet152_imagenet_full	.738
273	resnet101_ecoset_full	.735
274	alexnet_training_seed_02	.735
275	resnet-101_v2-tf	.732
276	mobilenet_v2_1.0_192-tf	.730
277	mobilenet_v2_1-4_224_pytorch	.728
278	pnasnet_large-tf	.727
279	alexnet_training_seed_07	.727
280	cvt_cvt-13-384-in1k_4_LucyV4	.725
281	vggface	.725
282	resnet-50_v2-tf	.724
283	resnet-18_test_m	.720
284	pnasnet_large_halfPrecision	.719
285	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.719
286	alexnet_training_seed_04	.719
287	vonegrcnn_47e	.718
288	resnet-152_v1-tf	.716
289	yudixie_resnet18_distance_reg_0_240719	.715
290	alexnet_training_seed_01	.714
291	mobilenet_v2_0.5_192-tf	.715
292	resnet-18-LC_w_sh_100_iter_m	.715
293	voneresnet-50-non_stochastic	.712
294	mobilenet_v2_0.75_128	.713
295	yudixie_resnet50_random_0_240908	.711
296	alexnet_training_seed_09	.710
297	mobilenet_v1_0.25_128	.707
298	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.707
299	FrankRobWobv0	.705
300	antialiased-rnext101_32x8d	.705
301	AlexNet_SIN_fov16	.705
302	vit_base_patch14_reg4_dinov2-lvd142m	.705
303	resnet-101_v1-tf	.704
304	BiT-S-R152x4	.702
305	vit_large_patch14_clip_224:laion2b_ft_in1k	.701
306	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.701
307	resnet34_ecoset_full	.700
308	BiT-M-R101x3	.698
309	resnet152_ecoset_full	.697
310	BiT-M-R152x4	.697
311	mobilenet_v2_1_0_192	.696
312	SWSL_resnext101_32x8d	.696
313	convnext_small_imagenet_10_seed-0	.695
314	vonegrcnn_52e_full	.693
315	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.693
316	resnet-152_v2_pytorch	.693
317	densenet-121-keras	.692
318	v1-pyr-nodown	.689
319	efficientnet_b0_imagenet_full	.687
320	deit_small_imagenet_100_seed-0	.686
321	yudixie_resnet18_rotation_reg_0_240719	.687
322	yolos_tiny	.682
323	vit_base_patch14_dinov2-lvd142m	.680
324	BiT-S-R101x1	.678
325	konkle_alexnetgn_ipcl_ref01_primary_model	.676
326	my-model	.677
327	mobilenet_v2_0.75_160-tf	.669
328	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.668
329	nasnet_mobile-tf	.664
330	resnet50-barlow	.662
331	shufflenet_v2_x1_0	.658
332	BiT-M-R152x2	.658
333	nasnet_mobile	.657
334	vision_transformer_vit_large_patch16_224	.656
335	resnet50_FractalDB	.655
336	CLIP_ViT-B_32	.653
337	densenet-169-keras	.652
338	BiT-M-R50x1	.648
339	effnetv2m_custom384	.640
340	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.639
341	vit_large_patch14_clip_336:laion2b_ft_in1k	.637
342	alexnet_training_seed_10	.636
343	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.634
344	eBarlow_lmda_02_1000ep	.633
345	cv_18_dagger_408_pretrained	.632
346	resnet50	.630
347	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.630
348	mobilenet_v2_0_75_160	.627
349	alexnet_training_seed_03	.627
350	resnet50_moco_v2	.624
351	deit_large_imagenet_full_seed-0	.624
352	omnivore_swinT	.623
353	mobilenet_v2_1_0_224	.622
354	efficientnet_b2_imagenet_full	.619
355	yudixie_resnet18_random_0_240719	.613
356	artResNet18_1	.612
357	custom_model_cv_18_dagger_408	.612
358	inception_v1-tf	.610
359	convnext_base_fb_in1k_gram_aligned_dinov3	.606
360	resnet50_simclr	.602
361	mobilenet_v2_0.35_224	.602
362	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.598
363	deit3_base_patch16_224_fb_in22k_ft_in1k	.597
364	mobilenet_v2_1.0_128-tf	.596
365	mobilenet_v2_1_0_160	.594
366	effnetb1_272x240	.594
367	vit_large_patch14_clip_224:openai_ft_in1k	.589
368	r3m_resnet34	.585
369	mobilenet_v2_0.5_224-tf	.582
370	resnet-18-LC_conv_init_m	.583
371	alexnet_training_seed_01_fov4	.581
372	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.578
373	convnext_small_imagenet_1_seed-0	.577
374	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.561
375	mobilenet_v2_0_5_192	.559
376	hmax	.553
377	deit_base_imagenet_full_seed-0	.551
378	vit_relpos_base_patch16_clsgap_224:sw_in1k	.550
379	deit3_base_patch16_224_fb_in1k	.547
380	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.545
381	r3m_resnet50_nocrop	.528
382	AT_efficientnet-b2	.526
383	AdvProp_efficientnet-b2	.525
384	inception_resnet_v2	.521
385	r3m_resnet18	.514
386	r3m_resnet50	.506
387	resnet50_pretrained_with_retinal_waves	.489
388	my-model	.484
389	mobilenet_v2_0.75_96	.481
390	alexnet_training_seed_08	.479
391	vit_base_patch16_dinov3-lvd1689m	.474
392	CORnetZ_CIFAR10	.422
393	mobilenet_v2_0.5_160	.398
394	mobilenet_v2_0.75_224-tf	.397
395	deit_small_imagenet_10_seed-0	.388
396	ViT-B/32	.387
397	resnet50_imagenet_1_seed-0	.325
398	alexnet_training_seed_05	.313
399	alexnet_training_seed_06	.233
400	resnet-18-LC_untrained	.233
401	resnet50-meshes-lt-100-original-pretrained	.177
402	resnet50-meshes-lt-100-original-scratch	.115
403	mobilenet_v2_0.5_128	.038
404	mobilenet_v2_0.35_160
405	resnet18-supervised
406	fitvid_trained_on_physion
407	openclip
408	resnext101_32x32d_wsl
409	resnext101_32x48d_wsl
410	resnet50_ImageNet
411	resnet_101_v1
412	regnet_y_400mf
413	tv_efficientnet-b1
414	alexnet_ks_torevert
415	yudixie_resnet50_imagenet1kpret_0_240312
416	resnet_152_v1
417	ViT_L_32_imagenet1k
418	resnext101_32x16d_wsl
419	densenet_201_pytorch
420	inception_v3_pytorch
421	pnasnet_large_pytorch
422	inception_v4
423	nasnet_large
424	deit_small_imagenet_1_seed-0
425	pnasnet_large
426	vonegrcnn_62e_nobn
427	resnet_101_v2
428	vonegrcnn_47e
429	vonegrcnn_52e_full
430	vonegrcnn_47e
431	resnet_152_v2
432	pr1_stl10_disentangled_alpha04
433	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: orth_pref_ratio