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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_femto_ols:d1_in1k	.933
84	alexnet_random_linf8_perturb	.932
85	yudixie_resnet18_translation_rotation_0_240719	.931
86	ReAlnet01_cornet	.930
87	vit_base_patch14_reg4_dinov2-lvd142m	.930
88	ReAlnet01	.930
89	BiT-M-R50x1	.930
90	xception	.929
91	alexnet_training_seed_01	.928
92	ReAlnet04_ALL	.927
93	mobilenet_v2_1.4_224-tf	.927
94	ReAlnet06_cornet	.926
95	mobilenet_v2_1.0_96	.926
96	0.5x_resnet-18_LC_w_sh_100_iter	.926
97	ReAlnet06	.926
98	ReAlnet09	.926
99	ReAlnet09_cornet	.924
100	AlexNet_SIN	.924
101	yudixie_resnet18_distance_translation_rotation_0_240719	.924
102	alexnet_early_checkpoint	.924
103	inception_v1	.924
104	ReAlnet08_ALL	.924
105	briaai_rmbg_1_4	.923
106	ReAlnet03_ALL	.923
107	yudixie_wbh_object_class_scaling_0415_run_1	.923
108	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.922
109	ReAlnet07_ALL	.922
110	ReAlnet07_cornet	.921
111	ReAlnet07	.921
112	0.5x_resnet-18	.920
113	vgg_19	.918
114	ReAlnet10_ALL	.919
115	ReAlnet02_ALL	.919
116	ReAlnet01_ALL	.919
117	cvt_cvt-13-224-in1k_4_LucyV4	.920
118	yudixie_resnet50_object_class_0_240908	.918
119	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.919
120	resnet-50_v1-tf	.919
121	BiT-S-R101x1	.919
122	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.919
123	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.918
124	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.919
125	grcnn_v2_text_noise	.918
126	ReAlnet06_ALL	.918
127	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.918
128	ReAlnet09_ALL	.918
129	ReAlnet10_cornet	.917
130	grcnn	.916
131	ReAlnet05_cornet	.916
132	ReAlnet05	.916
133	ReAlnet05_ALL	.915
134	resnet-18-LC_1st_conv_m	.915
135	convnext_tiny_sup	.915
136	ReAlnet10	.915
137	resnet_SIN_IN_FT_IN	.913
138	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
139	convnext_tiny:in12k_ft_in1k	.911
140	deepeisnn_ei_cifar10_resnet18	.910
141	ReAlnet02_cornet	.910
142	ReAlnet02	.909
143	resnet-18-LC_m	.909
144	compact_cornets_V4	.908
145	resnet50-sup	.908
146	yudixie_resnet50_imagenet1kpret_0_240908	.908
147	resnet50_tutorial	.908
148	alexnet_fov12	.908
149	resnet_50_v1	.908
150	resnet_50_v1_spiking_l4a	.907
151	resnet_50_v1_spiking	.908
152	resnet50	.907
153	resnet_50_v1_spiking_l3	.907
154	mobilenet_v2_1.0_160-tf	.907
155	resnet_50_v1_spiking_l4	.905
156	alexnet_robust_correct	.906
157	mobilenet_v2_1.0_128-tf	.904
158	BiT-S-R152x2	.902
159	resnet-18-LC_w_sh_100_iter_conv_init_m	.901
160	cvt_cvt-21-224-in1k_4_LucyV4	.900
161	mobilenet_v2_0.5_192-tf	.900
162	alexnet_fov16	.899
163	resnet18_ecoset_full	.897
164	deit_large_imagenet_full_seed-0	.898
165	texture_shape_alexnet_trained_on_SIN	.897
166	alexnet_training_seed_10	.896
167	SWSL_resnext101_32x8d	.896
168	vgg-16-keras	.895
169	alexnet_random_l2_3_perturb	.893
170	convnext_small_imagenet_full_seed-0	.894
171	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.894
172	densenet-201-keras	.892
173	AlexNet_SIN_fov12	.892
174	mobilenet_v2_1_4_224	.891
175	resnet50-SIN_IN_IN	.891
176	SWSL_resnet50	.891
177	yudixie_resnet18_imagenet1kpret_0_240719	.889
178	deepeisnn_ei_imagenet_resnet18	.888
179	yudixie_wbh_object_class_scaling_0415_imagenet	.889
180	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.889
181	resnet-50-robust	.888
182	vgg-19-keras	.889
183	convnext_small_imagenet_10_seed-0	.886
184	AlexNet_SIN_fov4	.885
185	BiT-S-R152x4	.884
186	konkle_alexnetgn_ipcl_ref01_primary_model	.884
187	RN50	.883
188	CLIP-RN50	.882
189	compact_resnet50_IT	.879
190	resnet-18-LC_w_sh_10_iter_m	.880
191	AdvProp_efficientnet-b6	.878
192	cvt_cvt-13-384-in1k_4_LucyV4	.878
193	voneresnet-50-non_stochastic	.878
194	convnext_small_imagenet_100_seed-0	.875
195	alexnet_training_seed_03	.874
196	my-model	.874
197	resnet50_random_l2_perturb	.873
198	yudixie_wbh_object_class_scaling_0415_run_0	.872
199	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.870
200	AdvProp_efficientnet-b7	.870
201	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.870
202	BiT-M-R152x4	.870
203	cornet_s	.869
204	vgg_16	.869
205	compact_vgg19_V4	.867
206	aughost_fair_resnet18	.867
207	ViT_L_32_imagenet1k	.864
208	BiT-S-R101x3	.865
209	resnet50_robust_l2_eps3	.865
210	resnet50_imagenet_full	.865
211	resnet-152_v1-tf	.865
212	AlexNet_SIN_fov16	.863
213	alexnet_l2_3_robust	.862
214	densenet-201	.862
215	mobilenet_v2_1_0_128	.861
216	mobilenet_v2_1_0_224	.861
217	grcnn_robust_v1	.861
218	r3m_resnet34	.860
219	CLIP_resnet50	.860
220	resnet50-SIN	.859
221	resnet50-barlow	.859
222	CLIP_resnet50_float32	.858
223	resnet-152_v2_pytorch	.856
224	inception_v3-tf	.856
225	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.855
226	convnext_large_imagenet_full_seed-0	.855
227	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.855
228	resnet-50_v2-tf	.855
229	resnet50-VITO-8deg-cc	.854
230	texture_shape_resnet50_trained_on_SIN	.852
231	resnet-18-LC_w_sh_1_iter_m	.852
232	BiT-S-R50x3	.850
233	r3m_resnet18	.850
234	convnext_base_imagenet_full_seed-0	.850
235	resnet18_fair	.849
236	resnet50_imagenet_100_seed-0	.849
237	resnet50-vicreg	.848
238	resnet101	.849
239	resnet-18-LC_w_sh_100_iter_m	.848
240	vision_transformer_vit_large_patch16_224	.845
241	vonealexnet_gaussian_noise_std4_fixed	.845
242	mobilenet_v2_1.0_192-tf	.844
243	BiT-S-R50x1	.842
244	BiT-M-R101x3	.842
245	resnet34_ecoset_full	.840
246	convnext_base_fb_in1k	.842
247	deepeisnn_ei_cifar10_vgg19	.840
248	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.840
249	resnet50_linf_8_robust	.839
250	0.5x_resnet-18_LC	.839
251	resnet50_robust_l2_eps1	.836
252	antialiased-r50	.836
253	yudixie_resnet18_random_0_240719	.835
254	efficientnet_b2_imagenet_full	.835
255	convnext_tiny_imagenet_full_seed-0	.834
256	shufflenet_v2_x1_0	.833
257	mobilenet_v2_0.75_160-tf	.833
258	resnet-18_test_m	.833
259	vggface	.831
260	nasnet_mobile	.831
261	inception_v4-tf	.831
262	mobilenet_v2_1.0_224-tf	.830
263	vit_base_patch16_clip_224:openai_ft_in1k	.830
264	resnet18_imagenet_full	.828
265	resnet50_moco_v2	.826
266	BiT-M-R152x2	.826
267	resnet50_random_linf8_perturb	.825
268	mobilenet_v2_0_75_224	.825
269	resnet50_st_wzc_2	.825
270	resnet50_ewconplus_wzc_seed2_2__323	.824
271	resnet50_ewconplus_wzc_seed5_2__323	.823
272	resnet50_ewconplus_wzc_seed7_2_323	.823
273	AdvProp_efficientnet-b4	.822
274	nasnet_mobile-tf	.821
275	nasnet_large-tf	.820
276	convnext_small_imagenet_1_seed-0	.821
277	resnet50-vicregl0p9	.820
278	VOneCORnet-S	.816
279	alexnet_training_seed_01_fov4	.816
280	voneresnet-50	.813
281	Res2Net50_26w_4s	.815
282	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.814
283	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.813
284	vit_base_patch16_dinov3-lvd1689m	.813
285	mobilenet_v2_0.5_224-tf	.812
286	resnet_101_v1	.812
287	resnet50_linf_4_robust	.811
288	resnext101_32x8d_wsl	.810
289	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.810
290	pnasnet_large-tf	.809
291	voneresnet-50-robust	.808
292	artResNet18_1	.809
293	deit_small_imagenet_full_seed-0	.808
294	resnet50-moclr8deg	.808
295	resnet50_st_wzc_2_323	.808
296	mobilenet_v2_0.75_96	.808
297	antialias-resnet152	.806
298	CORnet-Z	.806
299	effnetv2m_custom384	.805
300	resnet50_ewconplus_wzc_2_323	.804
301	antialiased-rnext101_32x8d	.803
302	imagenet_l2_10_0	.802
303	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.802
304	resnet50-simclr-vissl	.802
305	resnet50_imagenet_10_seed-0	.800
306	resnet18_imagenet21kP	.801
307	0.5x_resnet-18_LC_w_sh_1_iter	.801
308	imagenet_l2_3_0	.799
309	pnasnet_large_halfPrecision	.797
310	r3m_resnet50	.797
311	vit_large_patch14_clip_224:laion2b_ft_in1k	.795
312	vit_large_patch14_clip_336:laion2b_ft_in1k	.796
313	resnet50_l2_3_robust	.794
314	resnet50_ewconplus_noseed_2_323	.793
315	resnet152_ecoset_full	.792
316	cv_18_dagger_408_pretrained	.792
317	r3m_resnet50_nocrop	.791
318	resnet34_imagenet_full	.791
319	resnet50_st_wzc_seed4_2_323	.790
320	custom_model_cv_18_dagger_408	.789
321	resnet50_ewconplus_wzc	.789
322	mobilenet_v2_0_75_192	.789
323	resnet50_st_wzc_seed5_2_323	.789
324	resnet50_FractalDB	.787
325	resnet-101_v1-tf	.785
326	resnet-101_v2-tf	.783
327	resnet50_st_wzc_seed6_2_323	.780
328	mobilenet_v2_1_3_224	.775
329	alexnet_linf_8_robust	.775
330	barlow-twins-resnet50	.774
331	deit3_base_patch16_224_fb_in22k_ft_in1k	.775
332	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.774
333	FrankRobWobv0	.774
334	resnet152_imagenet_full	.773
335	resnet50_st_wzc_seed7_2_323	.772
336	alexnet_training_seed_08	.772
337	resnet50_ewconplus_wzc_seed4_2_323	.771
338	resnet50_simclr	.770
339	resnet50-vitoimagevidnet8	.769
340	inception_v2-tf	.768
341	resnet101_ecoset_full	.764
342	densenet-121	.762
343	eBarlow_lmda_02_1000ep	.760
344	densenet-169	.760
345	AdvProp_efficientnet-b0	.758
346	vonegrcnn_62e_nobn	.757
347	resnet50_st_wzc_noseed_2_323	.756
348	resnet_50_v2	.755
349	compact_vgg19_IT	.751
350	mobilenet_v2_0_75_160	.751
351	resnet50_ecoset_full	.750
352	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.745
353	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.746
354	convnext_base_fb_in1k_gram_aligned_dinov3	.743
355	mobilenet_v2_0.35_224	.742
356	resnet50_ewconplus_wzc_seed3_2_323	.741
357	resnet50_st_wzc_seed3_2_323	.739
358	alexnet_reduced_aliasing_early_checkpoint	.738
359	resnet50_ewconplus_wzc_seed6_2_323	.737
360	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.736
361	deit_base_imagenet_full_seed-0	.735
362	mobilenet_v2_0_5_192	.734
363	resnet101_imagenet_full	.730
364	effnetb1_272x240	.727
365	resnet50-cifar	.722
366	omnivore_swinT	.721
367	vit_large_patch14_clip_224:openai_ft_in1k	.720
368	densenet-121-keras	.720
369	resnet50-SIN_IN	.719
370	densenet-169-keras	.715
371	resnet_101_v2	.714
372	CLIP_ViT-B_32	.713
373	mobilenet_v2_1_0_160	.712
374	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.710
375	inception_v1-tf	.708
376	CORnetZ_CIFAR10	.703
377	resnet50	.702
378	mobilenet_v2_1_0_192	.700
379	mobilenet_v2_0.5_160	.694
380	efficientnet_b0_imagenet_full	.693
381	inception_resnet_v2	.683
382	vit_relpos_base_patch16_clsgap_224:sw_in1k	.680
383	resnet-18-LC_conv_init_m	.676
384	yolos_tiny	.668
385	mobilenet_v2_0_5_224	.663
386	resnet50_pretrained_with_retinal_waves	.661
387	AdvProp_efficientnet-b2	.635
388	AT_efficientnet-b2	.633
389	my-model	.629
390	efficientnet_b0	.604
391	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.603
392	deit3_base_patch16_224_fb_in1k	.602
393	alexnet_training_seed_06	.563
394	CORnetZ_CIFAR10_bs32_20_04	.547
395	alexnet_training_seed_05	.546
396	ViT-B/32	.532
397	mobilenet_v2_0.75_128	.521
398	resnet50_imagenet_1_seed-0	.492
399	resnet-18-LC_untrained	.487
400	mobilenet_v2_0.75_224-tf	.437
401	v1-pyr-nodown	.419
402	hmax	.405
403	mobilenet_v2_0.5_128	.398
404	resnet50-meshes-lt-100-original-pretrained	.367
405	mobilenet_v1_0.25_128	.349
406	deit_small_imagenet_10_seed-0	.320
407	resnet50-meshes-lt-100-original-scratch	.265
408	mobilenet_v2_0.35_160
409	resnet18-supervised
410	fitvid_trained_on_physion
411	openclip
412	resnext101_32x32d_wsl
413	resnext101_32x48d_wsl
414	resnet50_ImageNet
415	regnet_y_400mf
416	tv_efficientnet-b1
417	alexnet_ks_torevert
418	yudixie_resnet50_imagenet1kpret_0_240312
419	resnet_152_v1
420	resnext101_32x16d_wsl
421	densenet_201_pytorch
422	pnasnet_large_pytorch
423	inception_v3_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	vonegrcnn_52e_full
431	resnet_152_v2
432	pr1_stl10_disentangled_alpha04
433	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: opr_cv_diff