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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	yudixie_resnet18_object_class_0_240719	.978
12	blt_vs	.977
13	cvt_cvt-21-384-in1k_4_LucyV4	.978
14	resnet-18-LC_w_sh_10_iter_conv_init_m	.976
15	yudixie_resnet18_distance_reg_0_240719	.976
16	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.976
17	efficientnet_b1_imagenet_full	.973
18	yudixie_resnet18_distance_translation_0_240719	.973
19	efficientnet-b7	.972
20	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.972
21	yudixie_resnet18_rotation_reg_0_240719	.971
22	omnivore_swinS	.969
23	yudixie_resnet50_distance_rotation_0_240908	.968
24	resnet50_primary_visual_cortex	.968
25	yudixie_resnet50_category_class_0_240908	.966
26	yudixie_resnet18_category_class_0_240719	.965
27	BiT-M-R101x1	.966
28	AdvProp_efficientnet-b8	.965
29	grcnn_109	.964
30	focalnet_tiny_lrf_in1k	.964
31	omnivore_swinB	.963
32	yudixie_resnet50_distance_translation_rotation_0_240908	.962
33	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.962
34	alexnet_training_seed_04	.960
35	yudixie_resnet50_distance_translation_0_240908	.959
36	vonegrcnn_47e	.958
37	resnet-18_untrained	.958
38	resnet-50_untrained	.957
39	yudixie_resnet18_distance_rotation_0_240719	.954
40	yudixie_resnet50_translation_reg_0_240908	.952
41	r3m_resnet34_nocrop	.950
42	mobilenet_v2_1-4_224_pytorch	.949
43	convnext_xlarge:fb_in22k_ft_in1k	.948
44	resnet-152_v2-tf	.948
45	ReAlnet08_cornet	.945
46	ReAlnet08	.944
47	convnext_large:fb_in22k_ft_in1k	.944
48	vonegrcnn_52e_full	.943
49	yudixie_resnet50_distance_reg_0_240908	.942
50	mobilenet_v2_1.3_224-tf	.942
51	alexnet	.941
52	alexnet	.941
53	0.5x_resnet-18_LC_w_sh_10_iter	.941
54	alexnet	.940
55	alexnet	.941
56	alexnet	.940
57	alexnet	.940
58	alexnet-baseline	.940
59	alexnet	.940
60	BiT-M-R50x3	.939
61	deit_small_imagenet_100_seed-0	.939
62	alexnet_training_seed_07	.937
63	ReAlnet03_cornet	.936
64	resnet50-vicregl0p75	.935
65	vonegrcnn_47e	.934
66	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.935
67	inception_v3	.935
68	resnet50_byol	.934
69	resnet-18-LC_w_sh_1_iter_conv_init_m	.934
70	ReAlnet03	.934
71	yudixie_resnet50_random_0_240908	.933
72	CORnet-S	.933
73	ReAlnet04	.934
74	ReAlnet04_cornet	.933
75	convnext_femto_ols:d1_in1k	.933
76	alexnet_random_linf8_perturb	.932
77	yudixie_resnet18_translation_rotation_0_240719	.931
78	ReAlnet01_cornet	.930
79	ReAlnet01	.930
80	BiT-M-R50x1	.930
81	xception	.929
82	alexnet_training_seed_01	.928
83	ReAlnet04_ALL	.927
84	mobilenet_v2_1.4_224-tf	.927
85	ReAlnet06_cornet	.926
86	mobilenet_v2_1.0_96	.926
87	0.5x_resnet-18_LC_w_sh_100_iter	.926
88	ReAlnet06	.926
89	ReAlnet09	.926
90	ReAlnet09_cornet	.924
91	AlexNet_SIN	.924
92	yudixie_resnet18_distance_translation_rotation_0_240719	.924
93	alexnet_early_checkpoint	.924
94	inception_v1	.924
95	ReAlnet08_ALL	.924
96	briaai_rmbg_1_4	.923
97	ReAlnet03_ALL	.923
98	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.922
99	ReAlnet07_ALL	.922
100	ReAlnet07_cornet	.921
101	ReAlnet07	.921
102	0.5x_resnet-18	.920
103	vgg_19	.918
104	ReAlnet10_ALL	.919
105	ReAlnet02_ALL	.919
106	ReAlnet01_ALL	.919
107	cvt_cvt-13-224-in1k_4_LucyV4	.920
108	yudixie_resnet50_object_class_0_240908	.918
109	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.919
110	resnet-50_v1-tf	.919
111	BiT-S-R101x1	.919
112	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.919
113	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.918
114	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.919
115	grcnn_v2_text_noise	.918
116	ReAlnet06_ALL	.918
117	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.918
118	ReAlnet09_ALL	.918
119	ReAlnet10_cornet	.917
120	grcnn	.916
121	ReAlnet05_cornet	.916
122	ReAlnet05	.916
123	ReAlnet05_ALL	.915
124	resnet-18-LC_1st_conv_m	.915
125	convnext_tiny_sup	.915
126	ReAlnet10	.915
127	resnet_SIN_IN_FT_IN	.913
128	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
129	convnext_tiny:in12k_ft_in1k	.911
130	ReAlnet02_cornet	.910
131	ReAlnet02	.909
132	resnet-18-LC_m	.909
133	resnet50-sup	.908
134	yudixie_resnet50_imagenet1kpret_0_240908	.908
135	resnet50_tutorial	.908
136	resnet_50_v1	.908
137	resnet_50_v1_spiking_l4a	.907
138	resnet_50_v1_spiking	.908
139	resnet50	.907
140	resnet_50_v1_spiking_l3	.907
141	mobilenet_v2_1.0_160-tf	.907
142	resnet_50_v1_spiking_l4	.905
143	alexnet_robust_correct	.906
144	mobilenet_v2_1.0_128-tf	.904
145	BiT-S-R152x2	.902
146	resnet-18-LC_w_sh_100_iter_conv_init_m	.901
147	cvt_cvt-21-224-in1k_4_LucyV4	.900
148	mobilenet_v2_0.5_192-tf	.900
149	resnet18_ecoset_full	.897
150	deit_large_imagenet_full_seed-0	.898
151	texture_shape_alexnet_trained_on_SIN	.897
152	alexnet_training_seed_10	.896
153	SWSL_resnext101_32x8d	.896
154	vgg-16-keras	.895
155	alexnet_random_l2_3_perturb	.893
156	convnext_small_imagenet_full_seed-0	.894
157	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.894
158	densenet-201-keras	.892
159	mobilenet_v2_1_4_224	.891
160	resnet50-SIN_IN_IN	.891
161	SWSL_resnet50	.891
162	yudixie_resnet18_imagenet1kpret_0_240719	.889
163	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.889
164	resnet-50-robust	.888
165	vgg-19-keras	.889
166	convnext_small_imagenet_10_seed-0	.886
167	BiT-S-R152x4	.884
168	konkle_alexnetgn_ipcl_ref01_primary_model	.884
169	RN50	.883
170	CLIP-RN50	.882
171	resnet-18-LC_w_sh_10_iter_m	.880
172	AdvProp_efficientnet-b6	.878
173	cvt_cvt-13-384-in1k_4_LucyV4	.878
174	voneresnet-50-non_stochastic	.878
175	alexnet	.875
176	convnext_small_imagenet_100_seed-0	.875
177	alexnet_training_seed_03	.874
178	my-model	.874
179	resnet50_random_l2_perturb	.873
180	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.870
181	AdvProp_efficientnet-b7	.870
182	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.870
183	BiT-M-R152x4	.870
184	cornet_s	.869
185	vgg_16	.869
186	ViT_L_32_imagenet1k	.864
187	BiT-S-R101x3	.865
188	resnet50_robust_l2_eps3	.865
189	resnet50_imagenet_full	.865
190	resnet-152_v1-tf	.865
191	alexnet_l2_3_robust	.862
192	densenet-201	.862
193	mobilenet_v2_1_0_128	.861
194	mobilenet_v2_1_0_224	.861
195	grcnn_robust_v1	.861
196	r3m_resnet34	.860
197	CLIP_resnet50	.860
198	resnet50-SIN	.859
199	resnet50-barlow	.859
200	CLIP_resnet50_float32	.858
201	resnet-152_v2_pytorch	.856
202	inception_v3-tf	.856
203	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.855
204	convnext_large_imagenet_full_seed-0	.855
205	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.855
206	resnet-50_v2-tf	.855
207	resnet50-VITO-8deg-cc	.854
208	texture_shape_resnet50_trained_on_SIN	.852
209	resnet-18-LC_w_sh_1_iter_m	.852
210	BiT-S-R50x3	.850
211	r3m_resnet18	.850
212	convnext_base_imagenet_full_seed-0	.850
213	resnet50_imagenet_100_seed-0	.849
214	resnet50-vicreg	.848
215	resnet101	.849
216	resnet-18-LC_w_sh_100_iter_m	.848
217	vision_transformer_vit_large_patch16_224	.845
218	vonealexnet_gaussian_noise_std4_fixed	.845
219	mobilenet_v2_1.0_192-tf	.844
220	BiT-S-R50x1	.842
221	BiT-M-R101x3	.842
222	resnet34_ecoset_full	.840
223	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.840
224	resnet50_linf_8_robust	.839
225	0.5x_resnet-18_LC	.839
226	resnet50_robust_l2_eps1	.836
227	antialiased-r50	.836
228	yudixie_resnet18_random_0_240719	.835
229	efficientnet_b2_imagenet_full	.835
230	convnext_tiny_imagenet_full_seed-0	.834
231	shufflenet_v2_x1_0	.833
232	mobilenet_v2_0.75_160-tf	.833
233	resnet-18_test_m	.833
234	vggface	.831
235	nasnet_mobile	.831
236	inception_v4-tf	.831
237	mobilenet_v2_1.0_224-tf	.830
238	vit_base_patch16_clip_224:openai_ft_in1k	.830
239	resnet18_imagenet_full	.828
240	resnet50_moco_v2	.826
241	BiT-M-R152x2	.826
242	resnet50_random_linf8_perturb	.825
243	mobilenet_v2_0_75_224	.825
244	AdvProp_efficientnet-b4	.822
245	nasnet_mobile-tf	.821
246	nasnet_large-tf	.820
247	convnext_small_imagenet_1_seed-0	.821
248	resnet50-vicregl0p9	.820
249	VOneCORnet-S	.816
250	voneresnet-50	.813
251	Res2Net50_26w_4s	.815
252	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.814
253	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.813
254	mobilenet_v2_0.5_224-tf	.812
255	resnet_101_v1	.812
256	resnet50_linf_4_robust	.811
257	resnext101_32x8d_wsl	.810
258	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.810
259	pnasnet_large-tf	.809
260	voneresnet-50-robust	.808
261	artResNet18_1	.809
262	deit_small_imagenet_full_seed-0	.808
263	resnet50-moclr8deg	.808
264	mobilenet_v2_0.75_96	.808
265	antialias-resnet152	.806
266	CORnet-Z	.806
267	effnetv2m_custom384	.805
268	antialiased-rnext101_32x8d	.803
269	imagenet_l2_10_0	.802
270	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.802
271	resnet50-simclr-vissl	.802
272	resnet50_imagenet_10_seed-0	.800
273	resnet18_imagenet21kP	.801
274	0.5x_resnet-18_LC_w_sh_1_iter	.801
275	imagenet_l2_3_0	.799
276	r3m_resnet50	.797
277	vit_large_patch14_clip_224:laion2b_ft_in1k	.795
278	vit_large_patch14_clip_336:laion2b_ft_in1k	.796
279	resnet50_l2_3_robust	.794
280	resnet152_ecoset_full	.792
281	cv_18_dagger_408_pretrained	.792
282	r3m_resnet50_nocrop	.791
283	resnet34_imagenet_full	.791
284	custom_model_cv_18_dagger_408	.789
285	mobilenet_v2_0_75_192	.789
286	resnet50_FractalDB	.787
287	resnet-101_v1-tf	.785
288	resnet-101_v2-tf	.783
289	mobilenet_v2_1_3_224	.775
290	alexnet_linf_8_robust	.775
291	barlow-twins-resnet50	.774
292	FrankRobWobv0	.774
293	resnet152_imagenet_full	.773
294	alexnet_training_seed_08	.772
295	resnet50_simclr	.770
296	resnet50-vitoimagevidnet8	.769
297	inception_v2-tf	.768
298	resnet101_ecoset_full	.764
299	densenet-121	.762
300	densenet-169	.760
301	AdvProp_efficientnet-b0	.758
302	vonegrcnn_62e_nobn	.757
303	resnet_50_v2	.755
304	mobilenet_v2_0_75_160	.751
305	resnet50_ecoset_full	.750
306	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.745
307	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.746
308	mobilenet_v2_0.35_224	.742
309	alexnet_reduced_aliasing_early_checkpoint	.738
310	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.736
311	deit_base_imagenet_full_seed-0	.735
312	mobilenet_v2_0_5_192	.734
313	resnet101_imagenet_full	.730
314	effnetb1_272x240	.727
315	resnet50-cifar	.722
316	omnivore_swinT	.721
317	vit_large_patch14_clip_224:openai_ft_in1k	.720
318	densenet-121-keras	.720
319	resnet50-SIN_IN	.719
320	densenet-169-keras	.715
321	resnet_101_v2	.714
322	CLIP_ViT-B_32	.713
323	mobilenet_v2_1_0_160	.712
324	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.710
325	inception_v1-tf	.708
326	CORnetZ_CIFAR10	.703
327	resnet50	.702
328	mobilenet_v2_1_0_192	.700
329	mobilenet_v2_0.5_160	.694
330	efficientnet_b0_imagenet_full	.693
331	inception_resnet_v2	.683
332	vit_relpos_base_patch16_clsgap_224:sw_in1k	.680
333	resnet-18-LC_conv_init_m	.676
334	yolos_tiny	.668
335	mobilenet_v2_0_5_224	.663
336	resnet50_pretrained_with_retinal_waves	.661
337	AdvProp_efficientnet-b2	.635
338	AT_efficientnet-b2	.633
339	my-model	.629
340	efficientnet_b0	.604
341	alexnet_training_seed_06	.563
342	CORnetZ_CIFAR10_bs32_20_04	.547
343	alexnet_training_seed_05	.546
344	ViT-B/32	.532
345	mobilenet_v2_0.75_128	.521
346	resnet50_imagenet_1_seed-0	.492
347	resnet-18-LC_untrained	.487
348	mobilenet_v2_0.75_224-tf	.437
349	v1-pyr-nodown	.419
350	hmax	.405
351	mobilenet_v2_0.5_128	.398
352	resnet50-meshes-lt-100-original-pretrained	.367
353	mobilenet_v1_0.25_128	.349
354	deit_small_imagenet_10_seed-0	.320
355	resnet50-meshes-lt-100-original-scratch	.265
356	mobilenet_v2_0.35_160
357	resnet18-supervised
358	fitvid_trained_on_physion
359	openclip
360	resnext101_32x32d_wsl
361	resnext101_32x48d_wsl
362	resnet50_ImageNet
363	regnet_y_400mf
364	tv_efficientnet-b1
365	alexnet_ks_torevert
366	yudixie_resnet50_imagenet1kpret_0_240312
367	resnet_152_v1
368	resnext101_32x16d_wsl
369	densenet_201_pytorch
370	pnasnet_large_pytorch
371	inception_v3_pytorch
372	mobilevit_small
373	inception_v4
374	nasnet_large
375	deit_small_imagenet_1_seed-0
376	pnasnet_large
377	vonegrcnn_62e_nobn
378	vonegrcnn_52e_full
379	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: opr_cv_diff