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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	resnet50_linf_4_robust	.992
12	resnet34_imagenet_full	.990
13	resnet50_byol	.990
14	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.990
15	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.990
16	resnet50_moco_v2	.990
17	yudixie_resnet50_object_class_0_240908	.989
18	briaai_rmbg_1_4	.989
19	resnet18_imagenet_full	.989
20	yudixie_resnet50_distance_translation_0_240908	.989
21	resnet-152_v2-tf	.989
22	antialiased-rnext101_32x8d	.988
23	vit_relpos_base_patch16_clsgap_224:sw_in1k	.987
24	resnet-18-LC_w_sh_10_iter_conv_init_m	.987
25	nasnet_mobile-tf	.988
26	texture_shape_alexnet_trained_on_SIN	.988
27	vision_transformer_vit_large_patch16_224	.988
28	nasnet_large-tf	.987
29	resnet-18-LC_d_w_sh_1x1_conv_init_m	.987
30	AT_efficientnet-b2	.987
31	voneresnet-50-robust	.987
32	mobilevit_small	.986
33	resnet-50-robust	.986
34	vgg_19	.986
35	resnet50-vitoimagevidnet8	.987
36	resnet50_robust_l2_eps1	.986
37	yudixie_resnet18_object_class_0_240719	.987
38	resnet-18-LC_w_sh_1_iter_conv_init_m	.986
39	resnet50_random_linf8_perturb	.986
40	resnet50_l2_3_robust	.986
41	AdvProp_efficientnet-b2	.985
42	vit_large_patch14_clip_224:openai_ft_in1k	.985
43	resnet50_random_l2_perturb	.985
44	yudixie_resnet50_distance_translation_rotation_0_240908	.985
45	yudixie_resnet50_translation_reg_0_240908	.984
46	yudixie_resnet50_random_0_240908	.983
47	voneresnet-50	.984
48	antialiased-r50	.983
49	resnet50-simclr-vissl	.982
50	resnet50_FractalDB	.984
51	resnet50-moclr8deg	.982
52	cv_18_dagger_408_pretrained	.983
53	r3m_resnet34	.982
54	BiT-S-R50x3	.982
55	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.981
56	densenet-121-keras	.980
57	resnet101_ecoset_full	.980
58	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.981
59	xception	.980
60	omnivore_swinT	.980
61	resnet152_imagenet_full	.979
62	grcnn_v2_text_noise	.979
63	SWSL_resnet50	.979
64	alexnet_training_seed_09	.979
65	yudixie_resnet50_translation_rotation_0_240908	.979
66	yudixie_resnet18_distance_rotation_0_240719	.978
67	resnet50_primary_visual_cortex	.978
68	resnet-50_untrained	.978
69	alexnet_training_seed_04	.977
70	resnet50-vicregl0p9	.977
71	yudixie_resnet18_rotation_reg_0_240719	.976
72	BiT-S-R50x1	.976
73	resnet-18_untrained	.977
74	resnet50-SIN_IN_IN	.976
75	yudixie_resnet50_distance_reg_0_240908	.976
76	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.976
77	resnet50_simclr	.976
78	vonegrcnn_62e_nobn	.976
79	barlow-twins-resnet50	.976
80	effnetb1_272x240	.976
81	grcnn_robust_v1	.975
82	alexnet	.974
83	imagenet_l2_3_0	.975
84	convnext_large_imagenet_full_seed-0	.974
85	resnet-50_v1-tf	.975
86	densenet-121	.974
87	inception_v4-tf	.974
88	antialias-resnet152	.975
89	resnet34_ecoset_full	.974
90	vgg-16-keras	.973
91	resnet50_linf_8_robust	.974
92	yudixie_resnet18_translation_reg_0_240719	.974
93	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.974
94	alexnet_linf_8_robust	.973
95	0.5x_resnet-18_LC_w_sh_100_iter	.973
96	convnext_base:clip_laiona_augreg_ft_in1k_384	.973
97	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.972
98	resnet-18_test_m	.973
99	BiT-S-R152x2	.972
100	pnasnet_large-tf	.973
101	yudixie_resnet18_translation_rotation_0_240719	.972
102	resnet50-vicreg	.973
103	custom_model_cv_18_dagger_408	.972
104	resnet-50x2_untrained	.971
105	resnet-18-LC_w_sh_10_iter_m	.971
106	cvt_cvt-21-224-in1k_4_LucyV4	.972
107	SWSL_resnext101_32x8d	.971
108	resnet50	.971
109	vit_large_patch14_clip_336:laion2b_ft_in1k	.970
110	resnet18_ecoset_full	.970
111	vgg_16	.971
112	resnet-18-LC_conv_init_m	.969
113	r3m_resnet50_nocrop	.968
114	resnet_50_v1_spiking_l4a	.968
115	convnext_femto_ols:d1_in1k	.969
116	resnet50_tutorial	.968
117	imagenet_l2_10_0	.969
118	resnet_50_v1_spiking	.968
119	yudixie_resnet50_imagenet1kpret_0_240908	.969
120	resnet_50_v1	.969
121	resnet50-sup	.968
122	yudixie_resnet50_rotation_reg_0_240908	.969
123	resnet_50_v1_spiking_l3	.969
124	resnet_50_v1_spiking_l4	.968
125	resnet50_robust_l2_eps3	.968
126	resnet50-SIN	.968
127	deit_base_imagenet_full_seed-0	.967
128	CLIP_resnet50	.967
129	CORnetZ_CIFAR10_bs32_20_04	.968
130	texture_shape_resnet50_trained_on_SIN	.967
131	resnet-152_v1-tf	.968
132	0.5x_resnet-18_LC	.967
133	CLIP_resnet50_float32	.967
134	cvt_cvt-13-384-in1k_4_LucyV4	.967
135	vonealexnet_gaussian_noise_std4_fixed	.966
136	0.5x_resnet-18_LC_w_sh_1_iter	.965
137	inception_v2-tf	.965
138	grcnn_109	.964
139	resnet50-barlow	.963
140	vonegrcnn_47e	.963
141	resnet-18-LC_w_sh_100_iter_conv_init_m	.963
142	efficientnet_b1_imagenet_full	.963
143	nasnet_mobile	.964
144	resnet50-vicregl0p75	.962
145	alexnet_random_l2_3_perturb	.962
146	focalnet_tiny_lrf_in1k	.962
147	resnet50_ecoset_full	.961
148	convnext_base_imagenet_full_seed-0	.961
149	yudixie_resnet18_random_0_240719	.960
150	AdvProp_efficientnet-b8	.960
151	yudixie_resnet18_imagenet1kpret_0_240719	.960
152	yudixie_resnet18_distance_translation_rotation_0_240719	.960
153	resnet18_imagenet21kP	.960
154	yudixie_resnet18_category_class_0_240719	.959
155	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.957
156	mobilenet_v2_0.75_192-tf	.958
157	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.957
158	resnet50_imagenet_10_seed-0	.955
159	effnetv2m_custom384	.954
160	resnet-18-LC_w_sh_100_iter_m	.954
161	mobilenet_v2_0_5_224	.954
162	convnext_xlarge:fb_in22k_ft_in1k	.952
163	CLIP_ViT-B_32	.953
164	RN50	.953
165	mobilenet_v1_0.25_128	.952
166	resnet_50_v2	.952
167	resnet-18-LC_untrained	.952
168	blt_vs	.952
169	0.5x_resnet-18	.951
170	densenet-201	.951
171	vonegrcnn_52e_full	.951
172	resnet50-VITO-8deg-cc	.950
173	resnet50-cifar	.950
174	inception_v3-tf	.950
175	BiT-M-R50x1	.949
176	ReAlnet06	.948
177	ReAlnet06_cornet	.947
178	vggface	.948
179	CORnetZ_CIFAR10	.947
180	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.947
181	ReAlnet09_cornet	.948
182	convnext_small_imagenet_100_seed-0	.947
183	vit_base_patch16_clip_224:openai_ft_in1k	.947
184	ReAlnet09	.946
185	AdvProp_efficientnet-b6	.946
186	resnet-18-LC_m	.946
187	vgg-19-keras	.944
188	CORnet-Z	.944
189	vonegrcnn_47e	.943
190	resnet50-SIN_IN	.943
191	resnext101_32x8d_wsl	.943
192	densenet-201-keras	.943
193	ReAlnet04_ALL	.944
194	ViT_L_32_imagenet1k	.942
195	alexnet_training_seed_02	.943
196	Res2Net50_26w_4s	.943
197	CLIP-RN50	.942
198	yudixie_resnet50_category_class_0_240908	.942
199	alexnet_training_seed_07	.942
200	r3m_resnet18	.941
201	mobilenet_v2_0_75_192	.940
202	mobilenet_v2_0.75_224-tf	.940
203	resnet-50_v2-tf	.940
204	ReAlnet09_ALL	.939
205	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.939
206	mobilenet_v2_0_75_160	.938
207	densenet-169	.939
208	inception_v3	.938
209	ReAlnet10	.938
210	ReAlnet10_cornet	.937
211	ReAlnet07	.936
212	deit_large_imagenet_full_seed-0	.937
213	ReAlnet07_cornet	.937
214	ReAlnet08_ALL	.936
215	FrankRobWobv0	.936
216	alexnet_l2_3_robust	.935
217	resnet101_imagenet_full	.936
218	efficientnet_b0	.935
219	AlexNet_SIN	.935
220	yudixie_resnet18_distance_translation_0_240719	.935
221	resnet152_ecoset_full	.935
222	resnet-101_v1-tf	.935
223	resnet_SIN_IN_FT_IN	.935
224	cvt_cvt-13-224-in1k_4_LucyV4	.935
225	konkle_alexnetgn_ipcl_ref01_primary_model	.934
226	ReAlnet03	.933
227	ReAlnet03_cornet	.933
228	ReAlnet05_cornet	.933
229	convnext_tiny_sup	.933
230	alexnet-baseline	.933
231	alexnet	.933
232	alexnet	.933
233	AdvProp_efficientnet-b7	.933
234	ReAlnet05	.932
235	ReAlnet02_ALL	.933
236	alexnet	.932
237	alexnet	.932
238	alexnet	.931
239	r3m_resnet50	.931
240	mobilenet_v2_1.0_128-tf	.931
241	ReAlnet06_ALL	.931
242	alexnet	.931
243	ReAlnet01_ALL	.931
244	alexnet	.930
245	ReAlnet10_ALL	.930
246	mobilenet_v2_0_5_192	.929
247	BiT-S-R152x4	.929
248	resnet50_imagenet_full	.929
249	my-model	.929
250	BiT-S-R101x3	.928
251	mobilenet_v2_0_75_224	.927
252	BiT-M-R152x4	.927
253	resnet-18-LC_w_sh_1_iter_m	.926
254	alexnet_training_seed_01	.926
255	grcnn	.925
256	alexnet_training_seed_10	.924
257	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.924
258	ReAlnet01	.924
259	convnext_tiny_imagenet_full_seed-0	.924
260	ReAlnet08	.924
261	ReAlnet01_cornet	.924
262	ReAlnet08_cornet	.923
263	ReAlnet03_ALL	.923
264	mobilenet_v2_1.4_224-tf	.923
265	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.922
266	ReAlnet04	.922
267	efficientnet_b0_imagenet_full	.921
268	resnet-152_v2_pytorch	.922
269	resnet101	.921
270	ReAlnet05_ALL	.920
271	ReAlnet04_cornet	.921
272	ReAlnet02	.919
273	ReAlnet02_cornet	.919
274	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.917
275	alexnet_reduced_aliasing_early_checkpoint	.917
276	resnet50_pretrained_with_retinal_waves	.918
277	alexnet_robust_correct	.918
278	ReAlnet07_ALL	.915
279	mobilenet_v2_1_0_128	.916
280	mobilenet_v2_1_0_160	.915
281	inception_v1	.914
282	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.914
283	BiT-M-R101x1	.914
284	alexnet_early_checkpoint	.913
285	inception_resnet_v2	.914
286	BiT-M-R101x3	.911
287	deit_small_imagenet_100_seed-0	.911
288	cornet_s	.911
289	convnext_small_imagenet_full_seed-0	.910
290	cvt_cvt-21-384-in1k_4_LucyV4	.909
291	densenet-169-keras	.907
292	convnext_small_imagenet_10_seed-0	.901
293	alexnet_training_seed_03	.897
294	mobilenet_v2_1.3_224-tf	.894
295	CORnet-S	.894
296	omnivore_swinS	.893
297	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.893
298	0.5x_resnet-18_LC_w_sh_10_iter	.893
299	mobilenet_v2_1_0_192	.893
300	efficientnet-b7	.892
301	efficientnet_b2_imagenet_full	.891
302	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.890
303	mobilenet_v2_1.0_160-tf	.889
304	mobilenet_v2_1_3_224	.883
305	convnext_tiny:in12k_ft_in1k	.882
306	yudixie_resnet18_distance_reg_0_240719	.882
307	resnet50_imagenet_100_seed-0	.882
308	mobilenet_v2_1.0_224-tf	.881
309	shufflenet_v2_x1_0	.877
310	mobilenet_v2_1_4_224	.877
311	mobilenet_v2_1-4_224_pytorch	.876
312	mobilenet_v2_0.5_192-tf	.875
313	v1-pyr-nodown	.872
314	mobilenet_v2_1.0_192-tf	.872
315	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.867
316	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.868
317	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.867
318	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.867
319	alexnet_random_linf8_perturb	.867
320	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.866
321	mobilenet_v2_0.5_224-tf	.864
322	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.863
323	mobilenet_v2_0.35_224	.860
324	convnext_small_imagenet_1_seed-0	.859
325	omnivore_swinB	.854
326	BiT-S-R101x1	.848
327	vit_large_patch14_clip_224:laion2b_ft_in1k	.847
328	yolos_tiny	.845
329	BiT-M-R152x2	.843
330	mobilenet_v2_1.0_96	.838
331	resnet50	.837
332	alexnet_training_seed_08	.824
333	voneresnet-50-non_stochastic	.819
334	alexnet_training_seed_06	.817
335	mobilenet_v2_0.75_160-tf	.811
336	mobilenet_v2_0.5_160	.810
337	artResNet18_1	.801
338	ViT-B/32	.796
339	inception_v1-tf	.795
340	mobilenet_v2_1_0_224	.794
341	mobilenet_v2_0.75_96	.783
342	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.780
343	alexnet_training_seed_05	.781
344	AdvProp_efficientnet-b0	.775
345	mobilenet_v2_0.75_128	.730
346	hmax	.689
347	mobilenet_v2_0.5_128	.689
348	my-model	.690
349	deit_small_imagenet_full_seed-0	.686
350	AdvProp_efficientnet-b4	.654
351	deit_small_imagenet_10_seed-0	.343
352	resnet50-meshes-lt-100-original-pretrained	.172
353	resnet50-meshes-lt-100-original-scratch	.116
354	mobilenet_v2_0.35_160
355	resnet18-supervised
356	fitvid_trained_on_physion
357	openclip
358	resnext101_32x32d_wsl
359	resnext101_32x48d_wsl
360	resnet50_ImageNet
361	regnet_y_400mf
362	tv_efficientnet-b1
363	alexnet_ks_torevert
364	yudixie_resnet50_imagenet1kpret_0_240312
365	resnet_152_v1
366	resnext101_32x16d_wsl
367	densenet_201_pytorch
368	pnasnet_large_pytorch
369	inception_v3_pytorch
370	inception_v4
371	nasnet_large
372	deit_small_imagenet_1_seed-0
373	pnasnet_large
374	vonegrcnn_62e_nobn
375	resnet_101_v2
376	resnet_152_v2
377	vonegrcnn_52e_full
378	resnet_101_v1

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: max_dc