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

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: opr_cv_diff