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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_1st_conv_m	.998
2	resnet50_imagenet_1_seed-0	.997
3	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.996
4	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.995
5	BiT-M-R50x3	.993
6	VOneCORnet-S	.993
7	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.992
8	resnet-101_v2-tf	.992
9	yudixie_resnet50_distance_rotation_0_240908	.993
10	convnext_large:fb_in22k_ft_in1k	.992
11	vit_base_patch14_reg4_dinov2-lvd142m	.992
12	resnet50_linf_4_robust	.992
13	resnet34_imagenet_full	.990
14	resnet50_byol	.990
15	vit_base_patch14_dinov2-lvd142m	.991
16	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.990
17	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.990
18	resnet50_moco_v2	.990
19	yudixie_resnet50_object_class_0_240908	.989
20	briaai_rmbg_1_4	.989
21	resnet18_imagenet_full	.989
22	yudixie_resnet50_distance_translation_0_240908	.989
23	resnet-152_v2-tf	.989
24	antialiased-rnext101_32x8d	.988
25	vit_relpos_base_patch16_clsgap_224:sw_in1k	.987
26	resnet-18-LC_w_sh_10_iter_conv_init_m	.987
27	nasnet_mobile-tf	.988
28	texture_shape_alexnet_trained_on_SIN	.988
29	vision_transformer_vit_large_patch16_224	.988
30	nasnet_large-tf	.987
31	resnet-18-LC_d_w_sh_1x1_conv_init_m	.987
32	AT_efficientnet-b2	.987
33	voneresnet-50-robust	.987
34	mobilevit_small	.986
35	resnet-50-robust	.986
36	vgg_19	.986
37	resnet50-vitoimagevidnet8	.987
38	resnet50_robust_l2_eps1	.986
39	yudixie_resnet18_object_class_0_240719	.987
40	resnet-18-LC_w_sh_1_iter_conv_init_m	.986
41	resnet50_random_linf8_perturb	.986
42	resnet50_l2_3_robust	.986
43	AdvProp_efficientnet-b2	.985
44	vit_large_patch14_clip_224:openai_ft_in1k	.985
45	resnet50_random_l2_perturb	.985
46	yudixie_resnet50_distance_translation_rotation_0_240908	.985
47	yudixie_resnet50_translation_reg_0_240908	.984
48	yudixie_resnet50_random_0_240908	.983
49	voneresnet-50	.984
50	antialiased-r50	.983
51	resnet50-simclr-vissl	.982
52	resnet50_FractalDB	.984
53	alexnet_training_seed_01_fov16	.982
54	resnet50-moclr8deg	.982
55	cv_18_dagger_408_pretrained	.983
56	r3m_resnet34	.982
57	BiT-S-R50x3	.982
58	alexnet_training_seed_01_fov12	.981
59	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.981
60	densenet-121-keras	.980
61	resnet101_ecoset_full	.980
62	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.981
63	xception	.980
64	omnivore_swinT	.980
65	resnet152_imagenet_full	.979
66	grcnn_v2_text_noise	.979
67	SWSL_resnet50	.979
68	alexnet_training_seed_09	.979
69	yudixie_resnet50_translation_rotation_0_240908	.979
70	yudixie_resnet18_distance_rotation_0_240719	.978
71	resnet50_primary_visual_cortex	.978
72	resnet-50_untrained	.978
73	alexnet_training_seed_04	.977
74	resnet50-vicregl0p9	.977
75	yudixie_resnet18_rotation_reg_0_240719	.976
76	BiT-S-R50x1	.976
77	resnet-18_untrained	.977
78	resnet50-SIN_IN_IN	.976
79	yudixie_resnet50_distance_reg_0_240908	.976
80	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.976
81	resnet50_simclr	.976
82	vonegrcnn_62e_nobn	.976
83	barlow-twins-resnet50	.976
84	effnetb1_272x240	.976
85	grcnn_robust_v1	.975
86	ReAlnet01_cornet_fov4	.975
87	imagenet_l2_3_0	.975
88	convnext_large_imagenet_full_seed-0	.974
89	resnet-50_v1-tf	.975
90	densenet-121	.974
91	inception_v4-tf	.974
92	antialias-resnet152	.975
93	resnet34_ecoset_full	.974
94	vgg-16-keras	.973
95	resnet50_linf_8_robust	.974
96	yudixie_resnet18_translation_reg_0_240719	.974
97	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.974
98	alexnet_linf_8_robust	.973
99	0.5x_resnet-18_LC_w_sh_100_iter	.973
100	convnext_base:clip_laiona_augreg_ft_in1k_384	.973
101	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.972
102	resnet-18_test_m	.973
103	BiT-S-R152x2	.972
104	yudixie_wbh_object_class_scaling_0415_run_3	.973
105	pnasnet_large-tf	.973
106	pnasnet_large_halfPrecision	.972
107	yudixie_resnet18_translation_rotation_0_240719	.972
108	resnet50-vicreg	.973
109	custom_model_cv_18_dagger_408	.972
110	resnet-50x2_untrained	.971
111	resnet-18-LC_w_sh_10_iter_m	.971
112	cvt_cvt-21-224-in1k_4_LucyV4	.972
113	SWSL_resnext101_32x8d	.971
114	resnet50	.971
115	vit_large_patch14_clip_336:laion2b_ft_in1k	.970
116	resnet18_ecoset_full	.970
117	resnet50_st_wzc_seed6_2_323	.970
118	vgg_16	.971
119	resnet-18-LC_conv_init_m	.969
120	r3m_resnet50_nocrop	.968
121	resnet_50_v1_spiking_l4a	.968
122	convnext_femto_ols:d1_in1k	.969
123	resnet50_tutorial	.968
124	imagenet_l2_10_0	.969
125	resnet_50_v1_spiking	.968
126	yudixie_wbh_object_class_scaling_0415_run_1	.969
127	yudixie_resnet50_imagenet1kpret_0_240908	.969
128	resnet_50_v1	.969
129	resnet50-sup	.968
130	yudixie_resnet50_rotation_reg_0_240908	.969
131	resnet_50_v1_spiking_l3	.969
132	resnet_50_v1_spiking_l4	.968
133	resnet50_robust_l2_eps3	.968
134	resnet50-SIN	.968
135	deit_base_imagenet_full_seed-0	.967
136	CLIP_resnet50	.967
137	CORnetZ_CIFAR10_bs32_20_04	.968
138	texture_shape_resnet50_trained_on_SIN	.967
139	resnet-152_v1-tf	.968
140	0.5x_resnet-18_LC	.967
141	CLIP_resnet50_float32	.967
142	cvt_cvt-13-384-in1k_4_LucyV4	.967
143	vonealexnet_gaussian_noise_std4_fixed	.966
144	0.5x_resnet-18_LC_w_sh_1_iter	.965
145	inception_v2-tf	.965
146	grcnn_109	.964
147	resnet50-barlow	.963
148	vonegrcnn_47e	.963
149	resnet-18-LC_w_sh_100_iter_conv_init_m	.963
150	efficientnet_b1_imagenet_full	.963
151	nasnet_mobile	.964
152	resnet50-vicregl0p75	.962
153	alexnet_random_l2_3_perturb	.962
154	focalnet_tiny_lrf_in1k	.962
155	resnet50_ecoset_full	.961
156	convnext_base_fb_in22k_ft_in1k	.961
157	convnext_base_imagenet_full_seed-0	.961
158	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.960
159	yudixie_resnet18_random_0_240719	.960
160	AdvProp_efficientnet-b8	.960
161	yudixie_resnet18_imagenet1kpret_0_240719	.960
162	yudixie_resnet18_distance_translation_rotation_0_240719	.960
163	yudixie_wbh_object_class_scaling_0415_imagenet	.960
164	resnet18_imagenet21kP	.960
165	yudixie_resnet18_category_class_0_240719	.959
166	ReAlnet01_cornet_fov12	.958
167	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.957
168	mobilenet_v2_0.75_192-tf	.958
169	yudixie_wbh_object_class_scaling_0415_run_0	.957
170	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.957
171	resnet50_st_wzc_noseed_2_323	.955
172	AlexNet_SIN_fov4	.956
173	resnet50_imagenet_10_seed-0	.955
174	effnetv2m_custom384	.954
175	yudixie_wbh_object_class_scaling_0415_run_2	.954
176	resnet-18-LC_w_sh_100_iter_m	.954
177	eBarlow_lmda_02_1000ep	.954
178	mobilenet_v2_0_5_224	.954
179	convnext_xlarge:fb_in22k_ft_in1k	.952
180	CLIP_ViT-B_32	.953
181	RN50	.953
182	mobilenet_v1_0.25_128	.952
183	resnet_50_v2	.952
184	resnet-18-LC_untrained	.952
185	blt_vs	.952
186	0.5x_resnet-18	.951
187	densenet-201	.951
188	vonegrcnn_52e_full	.951
189	resnet50-VITO-8deg-cc	.950
190	resnet50-cifar	.950
191	inception_v3-tf	.950
192	BiT-M-R50x1	.949
193	ReAlnet01_cornet_fov16	.948
194	ReAlnet06	.948
195	ReAlnet06_cornet	.947
196	vggface	.948
197	CORnetZ_CIFAR10	.947
198	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.947
199	ReAlnet09_cornet	.948
200	convnext_small_imagenet_100_seed-0	.947
201	vit_base_patch16_clip_224:openai_ft_in1k	.947
202	ReAlnet09	.946
203	AdvProp_efficientnet-b6	.946
204	resnet18_fair	.946
205	resnet-18-LC_m	.946
206	vgg-19-keras	.944
207	CORnet-Z	.944
208	alexnet_fov4	.944
209	vonegrcnn_47e	.943
210	resnet50_st_wzc_seed3_2_323	.943
211	resnet50-SIN_IN	.943
212	resnext101_32x8d_wsl	.943
213	densenet-201-keras	.943
214	ReAlnet04_ALL	.944
215	ViT_L_32_imagenet1k	.942
216	alexnet_training_seed_02	.943
217	Res2Net50_26w_4s	.943
218	compact_resnet50_robust_V4	.942
219	CLIP-RN50	.942
220	resnet50_st_wzc_seed7_2_323	.941
221	yudixie_resnet50_category_class_0_240908	.942
222	alexnet_training_seed_07	.942
223	r3m_resnet18	.941
224	mobilenet_v2_0_75_192	.940
225	mobilenet_v2_0.75_224-tf	.940
226	resnet-50_v2-tf	.940
227	ReAlnet09_ALL	.939
228	compact_cornets_IT	.938
229	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.939
230	mobilenet_v2_0_75_160	.938
231	densenet-169	.939
232	inception_v3	.938
233	ReAlnet10	.938
234	ReAlnet10_cornet	.937
235	ReAlnet07	.936
236	deit_large_imagenet_full_seed-0	.937
237	ReAlnet07_cornet	.937
238	ReAlnet08_ALL	.936
239	FrankRobWobv0	.936
240	alexnet_l2_3_robust	.935
241	resnet101_imagenet_full	.936
242	efficientnet_b0	.935
243	AlexNet_SIN	.935
244	yudixie_resnet18_distance_translation_0_240719	.935
245	resnet152_ecoset_full	.935
246	resnet-101_v1-tf	.935
247	resnet_SIN_IN_FT_IN	.935
248	cvt_cvt-13-224-in1k_4_LucyV4	.935
249	compact_vgg19_IT	.934
250	konkle_alexnetgn_ipcl_ref01_primary_model	.934
251	ReAlnet03	.933
252	ReAlnet03_cornet	.933
253	ReAlnet05_cornet	.933
254	convnext_tiny_sup	.933
255	convnext_base_fb_in1k_gram_aligned_dinov3	.933
256	alexnet	.933
257	AdvProp_efficientnet-b7	.933
258	ReAlnet05	.932
259	ReAlnet02_ALL	.933
260	convnext_base_fb_in1k	.932
261	r3m_resnet50	.931
262	mobilenet_v2_1.0_128-tf	.931
263	ReAlnet06_ALL	.931
264	ReAlnet01_ALL	.931
265	ReAlnet10_ALL	.930
266	mobilenet_v2_0_5_192	.929
267	BiT-S-R152x4	.929
268	resnet50_imagenet_full	.929
269	my-model	.929
270	BiT-S-R101x3	.928
271	mobilenet_v2_0_75_224	.927
272	BiT-M-R152x4	.927
273	resnet-18-LC_w_sh_1_iter_m	.926
274	resnet50_st_wzc_seed5_2_323	.927
275	alexnet_training_seed_01	.926
276	grcnn	.925
277	alexnet_training_seed_10	.924
278	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.924
279	ReAlnet01	.924
280	convnext_tiny_imagenet_full_seed-0	.924
281	ReAlnet08	.924
282	ReAlnet01_cornet	.924
283	resnet50_st_wzc_seed4_2_323	.924
284	ReAlnet08_cornet	.923
285	ReAlnet03_ALL	.923
286	compact_resnet50_V4	.923
287	mobilenet_v2_1.4_224-tf	.923
288	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.922
289	ReAlnet04	.922
290	efficientnet_b0_imagenet_full	.921
291	resnet-152_v2_pytorch	.922
292	resnet101	.921
293	ReAlnet05_ALL	.920
294	ReAlnet04_cornet	.921
295	ReAlnet02	.919
296	alexnet_fov16	.919
297	ReAlnet02_cornet	.919
298	compact_cornets_V4	.917
299	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.917
300	alexnet_reduced_aliasing_early_checkpoint	.917
301	resnet50_pretrained_with_retinal_waves	.918
302	compact_vgg19_V4	.916
303	alexnet_robust_correct	.918
304	ReAlnet07_ALL	.915
305	mobilenet_v2_1_0_128	.916
306	mobilenet_v2_1_0_160	.915
307	inception_v1	.914
308	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.914
309	BiT-M-R101x1	.914
310	alexnet_early_checkpoint	.913
311	inception_resnet_v2	.914
312	BiT-M-R101x3	.911
313	deit_small_imagenet_100_seed-0	.911
314	cornet_s	.911
315	convnext_small_imagenet_full_seed-0	.910
316	cvt_cvt-21-384-in1k_4_LucyV4	.909
317	densenet-169-keras	.907
318	resnet50_st_wzc_2_323	.906
319	convnext_small_imagenet_10_seed-0	.901
320	AlexNet_SIN_fov16	.897
321	alexnet_training_seed_03	.897
322	resnet50_st_wzc_2	.896
323	mobilenet_v2_1.3_224-tf	.894
324	CORnet-S	.894
325	omnivore_swinS	.893
326	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.893
327	0.5x_resnet-18_LC_w_sh_10_iter	.893
328	mobilenet_v2_1_0_192	.893
329	deit3_base_patch16_224_fb_in22k_ft_in1k	.892
330	efficientnet-b7	.892
331	efficientnet_b2_imagenet_full	.891
332	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.890
333	compact_resnet50_IT	.891
334	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.890
335	mobilenet_v2_1.0_160-tf	.889
336	mobilenet_v2_1_3_224	.883
337	convnext_tiny:in12k_ft_in1k	.882
338	yudixie_resnet18_distance_reg_0_240719	.882
339	resnet50_imagenet_100_seed-0	.882
340	compact_resnet50_robust_IT	.882
341	mobilenet_v2_1.0_224-tf	.881
342	shufflenet_v2_x1_0	.877
343	alexnet_training_seed_01_fov4	.877
344	mobilenet_v2_1_4_224	.877
345	mobilenet_v2_1-4_224_pytorch	.876
346	mobilenet_v2_0.5_192-tf	.875
347	v1-pyr-nodown	.872
348	mobilenet_v2_1.0_192-tf	.872
349	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.867
350	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.868
351	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.867
352	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.867
353	alexnet_random_linf8_perturb	.867
354	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.866
355	mobilenet_v2_0.5_224-tf	.864
356	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.863
357	mobilenet_v2_0.35_224	.860
358	convnext_small_imagenet_1_seed-0	.859
359	omnivore_swinB	.854
360	BiT-S-R101x1	.848
361	resnet50_ewconplus_noseed_2_323	.848
362	vit_large_patch14_clip_224:laion2b_ft_in1k	.847
363	resnet50_ewconplus_wzc_seed2_2__323	.847
364	yolos_tiny	.845
365	BiT-M-R152x2	.843
366	mobilenet_v2_1.0_96	.838
367	resnet50	.837
368	resnet50_ewconplus_wzc	.827
369	resnet50_ewconplus_wzc_2_323	.824
370	alexnet_training_seed_08	.824
371	aughost_fair_resnet18	.820
372	voneresnet-50-non_stochastic	.819
373	alexnet_training_seed_06	.817
374	resnet50_ewconplus_wzc_seed3_2_323	.816
375	mobilenet_v2_0.75_160-tf	.811
376	resnet50_ewconplus_wzc_seed4_2_323	.810
377	mobilenet_v2_0.5_160	.810
378	artResNet18_1	.801
379	ViT-B/32	.796
380	inception_v1-tf	.795
381	mobilenet_v2_1_0_224	.794
382	resnet50_ewconplus_wzc_seed5_2__323	.792
383	AlexNet_SIN_fov12	.790
384	mobilenet_v2_0.75_96	.783
385	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.780
386	alexnet_training_seed_05	.781
387	AdvProp_efficientnet-b0	.775
388	resnet50_ewconplus_wzc_seed6_2_323	.767
389	vit_base_patch16_dinov3-lvd1689m	.756
390	alexnet_fov12	.756
391	resnet50_ewconplus_wzc_seed7_2_323	.753
392	deit3_base_patch16_224_fb_in1k	.751
393	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.751
394	mobilenet_v2_0.75_128	.730
395	hmax	.689
396	mobilenet_v2_0.5_128	.689
397	my-model	.690
398	deepeisnn_ei_cifar10_vgg19	.689
399	deepeisnn_ei_cifar10_resnet18	.690
400	deepeisnn_ei_imagenet_resnet18	.689
401	deit_small_imagenet_full_seed-0	.686
402	AdvProp_efficientnet-b4	.654
403	deit_small_imagenet_10_seed-0	.343
404	resnet50-meshes-lt-100-original-pretrained	.172
405	resnet50-meshes-lt-100-original-scratch	.116
406	mobilenet_v2_0.35_160
407	resnet18-supervised
408	fitvid_trained_on_physion
409	openclip
410	resnext101_32x32d_wsl
411	resnext101_32x48d_wsl
412	resnet50_ImageNet
413	regnet_y_400mf
414	tv_efficientnet-b1
415	alexnet_ks_torevert
416	yudixie_resnet50_imagenet1kpret_0_240312
417	resnet_152_v1
418	resnext101_32x16d_wsl
419	densenet_201_pytorch
420	pnasnet_large_pytorch
421	inception_v3_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	resnet_152_v2
429	vonegrcnn_52e_full
430	resnet_101_v1
431	pr1_stl10_disentangled_alpha04
432	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: max_dc