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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	mobilenet_v2_0.75_192-tf	.991
2	yudixie_resnet50_translation_rotation_0_240908	.988
3	alexnet_training_seed_09	.989
4	convnext_base:clip_laiona_augreg_ft_in1k_384	.989
5	alexnet_training_seed_02	.987
6	yudixie_resnet50_rotation_reg_0_240908	.987
7	yudixie_resnet18_translation_reg_0_240719	.987
8	resnet-50x2_untrained	.984
9	resnet-18-LC_d_w_sh_1x1_conv_init_m	.981
10	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.980
11	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.978
12	yudixie_resnet18_object_class_0_240719	.978
13	blt_vs	.977
14	cvt_cvt-21-384-in1k_4_LucyV4	.978
15	convnext_base_fb_in22k_ft_in1k	.976
16	resnet-18-LC_w_sh_10_iter_conv_init_m	.976
17	yudixie_resnet18_distance_reg_0_240719	.976
18	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.976
19	efficientnet_b1_imagenet_full	.973
20	yudixie_resnet18_distance_translation_0_240719	.973
21	efficientnet-b7	.972
22	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.972
23	yudixie_resnet18_rotation_reg_0_240719	.971
24	vit_base_patch14_dinov2-lvd142m	.969
25	omnivore_swinS	.969
26	yudixie_wbh_object_class_scaling_0415_run_2	.969
27	yudixie_resnet50_distance_rotation_0_240908	.968
28	resnet50_primary_visual_cortex	.968
29	yudixie_resnet50_category_class_0_240908	.966
30	yudixie_resnet18_category_class_0_240719	.965
31	BiT-M-R101x1	.966
32	AdvProp_efficientnet-b8	.965
33	grcnn_109	.964
34	ReAlnet01_cornet_fov12	.964
35	focalnet_tiny_lrf_in1k	.964
36	compact_resnet50_V4	.963
37	omnivore_swinB	.963
38	yudixie_resnet50_distance_translation_rotation_0_240908	.962
39	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.962
40	yudixie_wbh_object_class_scaling_0415_run_3	.962
41	ReAlnet01_cornet_fov16	.961
42	alexnet_training_seed_04	.960
43	yudixie_resnet50_distance_translation_0_240908	.959
44	vonegrcnn_47e	.958
45	resnet-18_untrained	.958
46	resnet-50_untrained	.957
47	yudixie_resnet18_distance_rotation_0_240719	.954
48	compact_cornets_IT	.953
49	alexnet_training_seed_01_fov12	.951
50	yudixie_resnet50_translation_reg_0_240908	.952
51	r3m_resnet34_nocrop	.950
52	alexnet_training_seed_01_fov16	.949
53	mobilenet_v2_1-4_224_pytorch	.949
54	convnext_xlarge:fb_in22k_ft_in1k	.948
55	resnet-152_v2-tf	.948
56	ReAlnet01_cornet_fov4	.946
57	alexnet_fov4	.946
58	ReAlnet08_cornet	.945
59	ReAlnet08	.944
60	convnext_large:fb_in22k_ft_in1k	.944
61	vonegrcnn_52e_full	.943
62	yudixie_resnet50_distance_reg_0_240908	.942
63	mobilenet_v2_1.3_224-tf	.942
64	compact_resnet50_robust_IT	.941
65	0.5x_resnet-18_LC_w_sh_10_iter	.941
66	alexnet	.941
67	BiT-M-R50x3	.939
68	compact_resnet50_robust_V4	.939
69	deit_small_imagenet_100_seed-0	.939
70	alexnet_training_seed_07	.937
71	ReAlnet03_cornet	.936
72	resnet50-vicregl0p75	.935
73	vonegrcnn_47e	.934
74	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.935
75	inception_v3	.935
76	resnet50_byol	.934
77	resnet-18-LC_w_sh_1_iter_conv_init_m	.934
78	ReAlnet03	.934
79	yudixie_resnet50_random_0_240908	.933
80	CORnet-S	.933
81	ReAlnet04	.934
82	ReAlnet04_cornet	.933
83	convnext_large_clip_laion2b_finelayers	.932
84	convnext_femto_ols:d1_in1k	.933
85	alexnet_random_linf8_perturb	.932
86	dinov2_vitl14_lc_res336	.932
87	yudixie_resnet18_translation_rotation_0_240719	.931
88	ReAlnet01_cornet	.930
89	vit_base_patch14_reg4_dinov2-lvd142m	.930
90	ReAlnet01	.930
91	BiT-M-R50x1	.930
92	xception	.929
93	alexnet_training_seed_01	.928
94	ReAlnet04_ALL	.927
95	mobilenet_v2_1.4_224-tf	.927
96	ReAlnet06_cornet	.926
97	mobilenet_v2_1.0_96	.926
98	0.5x_resnet-18_LC_w_sh_100_iter	.926
99	ReAlnet06	.926
100	ReAlnet09	.926
101	ReAlnet09_cornet	.924
102	AlexNet_SIN	.924
103	yudixie_resnet18_distance_translation_rotation_0_240719	.924
104	alexnet_early_checkpoint	.924
105	inception_v1	.924
106	ReAlnet08_ALL	.924
107	briaai_rmbg_1_4	.923
108	ReAlnet03_ALL	.923
109	yudixie_wbh_object_class_scaling_0415_run_1	.923
110	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.922
111	ReAlnet07_ALL	.922
112	ReAlnet07_cornet	.921
113	ReAlnet07	.921
114	0.5x_resnet-18	.920
115	vgg_19	.918
116	ReAlnet10_ALL	.919
117	ReAlnet02_ALL	.919
118	ReAlnet01_ALL	.919
119	cvt_cvt-13-224-in1k_4_LucyV4	.920
120	yudixie_resnet50_object_class_0_240908	.918
121	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.919
122	resnet-50_v1-tf	.919
123	BiT-S-R101x1	.919
124	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.919
125	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.918
126	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.919
127	grcnn_v2_text_noise	.918
128	ReAlnet06_ALL	.918
129	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.918
130	ReAlnet09_ALL	.918
131	ReAlnet10_cornet	.917
132	grcnn	.916
133	ReAlnet05_cornet	.916
134	ReAlnet05	.916
135	ReAlnet05_ALL	.915
136	resnet-18-LC_1st_conv_m	.915
137	convnext_tiny_sup	.915
138	ReAlnet10	.915
139	resnet_SIN_IN_FT_IN	.913
140	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
141	convnext_tiny:in12k_ft_in1k	.911
142	deepeisnn_ei_cifar10_resnet18	.910
143	ReAlnet02_cornet	.910
144	ReAlnet02	.909
145	convnext_large_in22k_supervised	.910
146	resnet-18-LC_m	.909
147	compact_cornets_V4	.908
148	resnet50-sup	.908
149	yudixie_resnet50_imagenet1kpret_0_240908	.908
150	resnet50_tutorial	.908
151	alexnet_fov12	.908
152	dinov2_vitg14_reg_lc	.908
153	resnet_50_v1	.908
154	resnet_50_v1_spiking_l4a	.907
155	resnet_50_v1_spiking	.908
156	resnet50	.907
157	resnet_50_v1_spiking_l3	.907
158	mobilenet_v2_1.0_160-tf	.907
159	resnet_50_v1_spiking_l4	.905
160	alexnet_robust_correct	.906
161	mobilenet_v2_1.0_128-tf	.904
162	BiT-S-R152x2	.902
163	resnet-18-LC_w_sh_100_iter_conv_init_m	.901
164	cvt_cvt-21-224-in1k_4_LucyV4	.900
165	mobilenet_v2_0.5_192-tf	.900
166	alexnet_fov16	.899
167	resnet18_ecoset_full	.897
168	deit_large_imagenet_full_seed-0	.898
169	texture_shape_alexnet_trained_on_SIN	.897
170	alexnet_training_seed_10	.896
171	SWSL_resnext101_32x8d	.896
172	vgg-16-keras	.895
173	alexnet_random_l2_3_perturb	.893
174	convnext_small_imagenet_full_seed-0	.894
175	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.894
176	densenet-201-keras	.892
177	AlexNet_SIN_fov12	.892
178	mobilenet_v2_1_4_224	.891
179	resnet50-SIN_IN_IN	.891
180	SWSL_resnet50	.891
181	yudixie_resnet18_imagenet1kpret_0_240719	.889
182	deepeisnn_ei_imagenet_resnet18	.888
183	yudixie_wbh_object_class_scaling_0415_imagenet	.889
184	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.889
185	resnet-50-robust	.888
186	vgg-19-keras	.889
187	convnext_small_imagenet_10_seed-0	.886
188	AlexNet_SIN_fov4	.885
189	BiT-S-R152x4	.884
190	konkle_alexnetgn_ipcl_ref01_primary_model	.884
191	RN50	.883
192	CLIP-RN50	.882
193	compact_resnet50_IT	.879
194	resnet-18-LC_w_sh_10_iter_m	.880
195	AdvProp_efficientnet-b6	.878
196	cvt_cvt-13-384-in1k_4_LucyV4	.878
197	voneresnet-50-non_stochastic	.878
198	convnext_small_imagenet_100_seed-0	.875
199	alexnet_training_seed_03	.874
200	my-model	.874
201	resnet50_random_l2_perturb	.873
202	yudixie_wbh_object_class_scaling_0415_run_0	.872
203	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.870
204	AdvProp_efficientnet-b7	.870
205	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.870
206	BiT-M-R152x4	.870
207	cornet_s	.869
208	vgg_16	.869
209	compact_vgg19_V4	.867
210	ViT_L_32_imagenet1k	.864
211	BiT-S-R101x3	.865
212	resnet50_robust_l2_eps3	.865
213	resnet50_imagenet_full	.865
214	resnet-152_v1-tf	.865
215	AlexNet_SIN_fov16	.863
216	alexnet_l2_3_robust	.862
217	dinov2_vitg14_lc	.863
218	densenet-201	.862
219	mobilenet_v2_1_0_128	.861
220	mobilenet_v2_1_0_224	.861
221	grcnn_robust_v1	.861
222	r3m_resnet34	.860
223	CLIP_resnet50	.860
224	resnet50-SIN	.859
225	resnet50-barlow	.859
226	CLIP_resnet50_float32	.858
227	resnet-152_v2_pytorch	.856
228	inception_v3-tf	.856
229	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.855
230	convnext_large_imagenet_full_seed-0	.855
231	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.855
232	resnet-50_v2-tf	.855
233	resnet50_hvs_wzc	.853
234	resnet50-VITO-8deg-cc	.854
235	texture_shape_resnet50_trained_on_SIN	.852
236	resnet-18-LC_w_sh_1_iter_m	.852
237	eicircuit_resnet18_bn_20260919	.852
238	BiT-S-R50x3	.850
239	r3m_resnet18	.850
240	convnext_base_imagenet_full_seed-0	.850
241	resnet18_fair	.849
242	resnet50_imagenet_100_seed-0	.849
243	resnet50-vicreg	.848
244	resnet101	.849
245	resnet-18-LC_w_sh_100_iter_m	.848
246	vision_transformer_vit_large_patch16_224	.845
247	vonealexnet_gaussian_noise_std4_fixed	.845
248	mobilenet_v2_1.0_192-tf	.844
249	BiT-S-R50x1	.842
250	BiT-M-R101x3	.842
251	resnet34_ecoset_full	.840
252	convnext_base_fb_in1k	.842
253	deepeisnn_ei_cifar10_vgg19	.840
254	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.840
255	resnet50_linf_8_robust	.839
256	0.5x_resnet-18_LC	.839
257	regnety_032	.836
258	resnet50_robust_l2_eps1	.836
259	antialiased-r50	.836
260	yudixie_resnet18_random_0_240719	.835
261	efficientnet_b2_imagenet_full	.835
262	convnext_tiny_imagenet_full_seed-0	.834
263	shufflenet_v2_x1_0	.833
264	mobilenet_v2_0.75_160-tf	.833
265	resnet-18_test_m	.833
266	gabor_filter_mean_abs_4x4_v2	.833
267	vggface	.831
268	nasnet_mobile	.831
269	inception_v4-tf	.831
270	mobilenet_v2_1.0_224-tf	.830
271	vit_base_patch16_clip_224:openai_ft_in1k	.830
272	resnet18_imagenet_full	.828
273	resnet50_moco_v2	.826
274	BiT-M-R152x2	.826
275	resnet50_random_linf8_perturb	.825
276	mobilenet_v2_0_75_224	.825
277	resnet50_st_wzc_2	.825
278	resnet50_ewconplus_wzc_seed2_2__323	.824
279	resnet50_ewconplus_wzc_seed5_2__323	.823
280	AdvProp_efficientnet-b4	.822
281	nasnet_mobile-tf	.821
282	nasnet_large-tf	.820
283	convnext_small_imagenet_1_seed-0	.821
284	resnet50-vicregl0p9	.820
285	dinov2_vitl14_reg_lc	.818
286	dinov2_vitl14_reg_lc_featread	.818
287	VOneCORnet-S	.816
288	alexnet_training_seed_01_fov4	.816
289	voneresnet-50	.813
290	Res2Net50_26w_4s	.815
291	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.814
292	dinov2_vitl14_lc	.813
293	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.813
294	vit_base_patch16_dinov3-lvd1689m	.813
295	mobilenet_v2_0.5_224-tf	.812
296	resnet_101_v1	.812
297	resnet50_linf_4_robust	.811
298	resnext101_32x8d_wsl	.810
299	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.810
300	pnasnet_large-tf	.809
301	voneresnet-50-robust	.808
302	artResNet18_1	.809
303	deit_small_imagenet_full_seed-0	.808
304	resnet50-moclr8deg	.808
305	mobilenet_v2_0.75_96	.808
306	antialias-resnet152	.806
307	CORnet-Z	.806
308	effnetv2m_custom384	.805
309	antialiased-rnext101_32x8d	.803
310	imagenet_l2_10_0	.802
311	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.802
312	resnet50-simclr-vissl	.802
313	resnet50_imagenet_10_seed-0	.800
314	resnet18_imagenet21kP	.801
315	0.5x_resnet-18_LC_w_sh_1_iter	.801
316	imagenet_l2_3_0	.799
317	pnasnet_large_halfPrecision	.797
318	r3m_resnet50	.797
319	vit_large_patch14_clip_224:laion2b_ft_in1k	.795
320	vit_large_patch14_clip_336:laion2b_ft_in1k	.796
321	resnet50_l2_3_robust	.794
322	resnet152_ecoset_full	.792
323	cv_18_dagger_408_pretrained	.792
324	r3m_resnet50_nocrop	.791
325	resnet34_imagenet_full	.791
326	custom_model_cv_18_dagger_408	.789
327	resnet50_ewconplus_wzc	.789
328	mobilenet_v2_0_75_192	.789
329	resnet50_FractalDB	.787
330	resnet-101_v1-tf	.785
331	resnet-101_v2-tf	.783
332	resnet50_st_wzc_seed6_2_323	.780
333	seresnext50_32x4d	.778
334	mobilenet_v2_1_3_224	.775
335	alexnet_linf_8_robust	.775
336	barlow-twins-resnet50	.774
337	deit3_base_patch16_224_fb_in22k_ft_in1k	.775
338	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.774
339	FrankRobWobv0	.774
340	resnet152_imagenet_full	.773
341	resnet50_st_wzc_seed7_2_323	.772
342	alexnet_training_seed_08	.772
343	resnet50_simclr	.770
344	resnet50-vitoimagevidnet8	.769
345	inception_v2-tf	.768
346	resnet101_ecoset_full	.764
347	densenet-121	.762
348	eBarlow_lmda_02_1000ep	.760
349	densenet-169	.760
350	AdvProp_efficientnet-b0	.758
351	vonegrcnn_62e_nobn	.757
352	resnet_50_v2	.755
353	compact_vgg19_IT	.751
354	mobilenet_v2_0_75_160	.751
355	resnet50_ecoset_full	.750
356	vit_large_clip336_openai	.747
357	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.745
358	eva02_large_in22k	.747
359	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.746
360	convnext_base_fb_in1k_gram_aligned_dinov3	.743
361	mobilenet_v2_0.35_224	.742
362	resnet50_st_wzc_seed3_2_323	.739
363	alexnet_reduced_aliasing_early_checkpoint	.738
364	resnet50_ewconplus_wzc_seed6_2_323	.737
365	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.736
366	deit_base_imagenet_full_seed-0	.735
367	mobilenet_v2_0_5_192	.734
368	resnet101_imagenet_full	.730
369	effnetb1_272x240	.727
370	resnet50-cifar	.722
371	omnivore_swinT	.721
372	vit_large_patch14_clip_224:openai_ft_in1k	.720
373	densenet-121-keras	.720
374	resnet50-SIN_IN	.719
375	densenet-169-keras	.715
376	resnet_101_v2	.714
377	CLIP_ViT-B_32	.713
378	mobilenet_v2_1_0_160	.712
379	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.710
380	inception_v1-tf	.708
381	CORnetZ_CIFAR10	.703
382	mobilenet_v2_1_0_192	.700
383	gabor_filter_entropy_4x4_v2_forcedCosine	.696
384	mobilenet_v2_0.5_160	.694
385	efficientnet_b0_imagenet_full	.693
386	inception_resnet_v2	.683
387	vit_relpos_base_patch16_clsgap_224:sw_in1k	.680
388	resnet-18-LC_conv_init_m	.676
389	yolos_tiny	.668
390	mobilenet_v2_0_5_224	.663
391	resnet50_pretrained_with_retinal_waves	.661
392	AdvProp_efficientnet-b2	.635
393	AT_efficientnet-b2	.633
394	my-model	.629
395	efficientnet_b0	.604
396	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.603
397	deit3_base_patch16_224_fb_in1k	.602
398	alexnet_training_seed_06	.563
399	CORnetZ_CIFAR10_bs32_20_04	.547
400	alexnet_training_seed_05	.546
401	ViT-B/32	.532
402	mobilenet_v2_0.75_128	.521
403	resnet50_imagenet_1_seed-0	.492
404	resnet-18-LC_untrained	.487
405	mobilenet_v2_0.75_224-tf	.437
406	v1-pyr-nodown	.419
407	hmax	.405
408	mobilenet_v2_0.5_128	.398
409	mobilenet_v1_0.25_128	.349
410	deit_small_imagenet_10_seed-0	.320
411	gabor_filter_entropy_4x4	.177
412	gabor_filter_entropy_4x4_v2	.177
413	mobilenet_v2_0.35_160
414	resnet18-supervised
415	fitvid_trained_on_physion
416	openclip
417	resnext101_32x32d_wsl
418	resnext101_32x48d_wsl
419	resnet50_ImageNet
420	regnet_y_400mf
421	tv_efficientnet-b1
422	alexnet_ks_torevert
423	yudixie_resnet50_imagenet1kpret_0_240312
424	resnet_152_v1
425	resnext101_32x16d_wsl
426	densenet_201_pytorch
427	pnasnet_large_pytorch
428	inception_v3_pytorch
429	mobilevit_small
430	inception_v4
431	nasnet_large
432	deit_small_imagenet_1_seed-0
433	pnasnet_large
434	vonegrcnn_62e_nobn
435	vonegrcnn_52e_full
436	resnet_152_v2
437	pr1_stl10_disentangled_alpha04
438	predictive_coding_pc
439	convnext_xxlarge_clip
440	vit_huge_clip336_laion

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: opr_cv_diff