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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	alexnet_training_seed_01_fov16	.982
52	resnet50-moclr8deg	.982
53	cv_18_dagger_408_pretrained	.983
54	r3m_resnet34	.982
55	BiT-S-R50x3	.982
56	alexnet_training_seed_01_fov12	.981
57	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.981
58	densenet-121-keras	.980
59	resnet101_ecoset_full	.980
60	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.981
61	xception	.980
62	omnivore_swinT	.980
63	resnet152_imagenet_full	.979
64	grcnn_v2_text_noise	.979
65	SWSL_resnet50	.979
66	alexnet_training_seed_09	.979
67	yudixie_resnet50_translation_rotation_0_240908	.979
68	yudixie_resnet18_distance_rotation_0_240719	.978
69	resnet50_primary_visual_cortex	.978
70	resnet-50_untrained	.978
71	alexnet_training_seed_04	.977
72	resnet50-vicregl0p9	.977
73	yudixie_resnet18_rotation_reg_0_240719	.976
74	BiT-S-R50x1	.976
75	resnet-18_untrained	.977
76	resnet50-SIN_IN_IN	.976
77	yudixie_resnet50_distance_reg_0_240908	.976
78	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.976
79	resnet50_simclr	.976
80	vonegrcnn_62e_nobn	.976
81	barlow-twins-resnet50	.976
82	effnetb1_272x240	.976
83	grcnn_robust_v1	.975
84	alexnet	.974
85	ReAlnet01_cornet_fov4	.975
86	imagenet_l2_3_0	.975
87	convnext_large_imagenet_full_seed-0	.974
88	resnet-50_v1-tf	.975
89	densenet-121	.974
90	inception_v4-tf	.974
91	antialias-resnet152	.975
92	resnet34_ecoset_full	.974
93	vgg-16-keras	.973
94	resnet50_linf_8_robust	.974
95	yudixie_resnet18_translation_reg_0_240719	.974
96	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.974
97	alexnet_linf_8_robust	.973
98	0.5x_resnet-18_LC_w_sh_100_iter	.973
99	convnext_base:clip_laiona_augreg_ft_in1k_384	.973
100	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.972
101	resnet-18_test_m	.973
102	BiT-S-R152x2	.972
103	pnasnet_large-tf	.973
104	yudixie_resnet18_translation_rotation_0_240719	.972
105	resnet50-vicreg	.973
106	custom_model_cv_18_dagger_408	.972
107	resnet-50x2_untrained	.971
108	resnet-18-LC_w_sh_10_iter_m	.971
109	cvt_cvt-21-224-in1k_4_LucyV4	.972
110	SWSL_resnext101_32x8d	.971
111	resnet50	.971
112	vit_large_patch14_clip_336:laion2b_ft_in1k	.970
113	resnet18_ecoset_full	.970
114	vgg_16	.971
115	resnet-18-LC_conv_init_m	.969
116	r3m_resnet50_nocrop	.968
117	resnet_50_v1_spiking_l4a	.968
118	convnext_femto_ols:d1_in1k	.969
119	resnet50_tutorial	.968
120	imagenet_l2_10_0	.969
121	resnet_50_v1_spiking	.968
122	yudixie_resnet50_imagenet1kpret_0_240908	.969
123	resnet_50_v1	.969
124	resnet50-sup	.968
125	yudixie_resnet50_rotation_reg_0_240908	.969
126	resnet_50_v1_spiking_l3	.969
127	resnet_50_v1_spiking_l4	.968
128	resnet50_robust_l2_eps3	.968
129	resnet50-SIN	.968
130	deit_base_imagenet_full_seed-0	.967
131	CLIP_resnet50	.967
132	CORnetZ_CIFAR10_bs32_20_04	.968
133	texture_shape_resnet50_trained_on_SIN	.967
134	resnet-152_v1-tf	.968
135	0.5x_resnet-18_LC	.967
136	CLIP_resnet50_float32	.967
137	cvt_cvt-13-384-in1k_4_LucyV4	.967
138	vonealexnet_gaussian_noise_std4_fixed	.966
139	0.5x_resnet-18_LC_w_sh_1_iter	.965
140	inception_v2-tf	.965
141	grcnn_109	.964
142	resnet50-barlow	.963
143	vonegrcnn_47e	.963
144	resnet-18-LC_w_sh_100_iter_conv_init_m	.963
145	efficientnet_b1_imagenet_full	.963
146	nasnet_mobile	.964
147	resnet50-vicregl0p75	.962
148	alexnet_random_l2_3_perturb	.962
149	focalnet_tiny_lrf_in1k	.962
150	resnet50_ecoset_full	.961
151	convnext_base_imagenet_full_seed-0	.961
152	yudixie_resnet18_random_0_240719	.960
153	AdvProp_efficientnet-b8	.960
154	yudixie_resnet18_imagenet1kpret_0_240719	.960
155	yudixie_resnet18_distance_translation_rotation_0_240719	.960
156	resnet18_imagenet21kP	.960
157	yudixie_resnet18_category_class_0_240719	.959
158	ReAlnet01_cornet_fov12	.958
159	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.957
160	mobilenet_v2_0.75_192-tf	.958
161	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.957
162	AlexNet_SIN_fov4	.956
163	resnet50_imagenet_10_seed-0	.955
164	effnetv2m_custom384	.954
165	resnet-18-LC_w_sh_100_iter_m	.954
166	mobilenet_v2_0_5_224	.954
167	convnext_xlarge:fb_in22k_ft_in1k	.952
168	CLIP_ViT-B_32	.953
169	RN50	.953
170	mobilenet_v1_0.25_128	.952
171	resnet_50_v2	.952
172	resnet-18-LC_untrained	.952
173	blt_vs	.952
174	0.5x_resnet-18	.951
175	densenet-201	.951
176	vonegrcnn_52e_full	.951
177	resnet50-VITO-8deg-cc	.950
178	resnet50-cifar	.950
179	inception_v3-tf	.950
180	BiT-M-R50x1	.949
181	ReAlnet01_cornet_fov16	.948
182	ReAlnet06	.948
183	ReAlnet06_cornet	.947
184	vggface	.948
185	CORnetZ_CIFAR10	.947
186	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.947
187	ReAlnet09_cornet	.948
188	convnext_small_imagenet_100_seed-0	.947
189	vit_base_patch16_clip_224:openai_ft_in1k	.947
190	ReAlnet09	.946
191	AdvProp_efficientnet-b6	.946
192	resnet-18-LC_m	.946
193	vgg-19-keras	.944
194	CORnet-Z	.944
195	alexnet_fov4	.944
196	vonegrcnn_47e	.943
197	resnet50-SIN_IN	.943
198	resnext101_32x8d_wsl	.943
199	densenet-201-keras	.943
200	ReAlnet04_ALL	.944
201	ViT_L_32_imagenet1k	.942
202	alexnet_training_seed_02	.943
203	Res2Net50_26w_4s	.943
204	compact_resnet50_robust_V4	.942
205	CLIP-RN50	.942
206	yudixie_resnet50_category_class_0_240908	.942
207	alexnet_training_seed_07	.942
208	r3m_resnet18	.941
209	mobilenet_v2_0_75_192	.940
210	mobilenet_v2_0.75_224-tf	.940
211	resnet-50_v2-tf	.940
212	ReAlnet09_ALL	.939
213	compact_cornets_IT	.938
214	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.939
215	mobilenet_v2_0_75_160	.938
216	densenet-169	.939
217	inception_v3	.938
218	ReAlnet10	.938
219	ReAlnet10_cornet	.937
220	ReAlnet07	.936
221	deit_large_imagenet_full_seed-0	.937
222	ReAlnet07_cornet	.937
223	ReAlnet08_ALL	.936
224	FrankRobWobv0	.936
225	alexnet_l2_3_robust	.935
226	resnet101_imagenet_full	.936
227	efficientnet_b0	.935
228	AlexNet_SIN	.935
229	yudixie_resnet18_distance_translation_0_240719	.935
230	resnet152_ecoset_full	.935
231	resnet-101_v1-tf	.935
232	resnet_SIN_IN_FT_IN	.935
233	cvt_cvt-13-224-in1k_4_LucyV4	.935
234	compact_vgg19_IT	.934
235	konkle_alexnetgn_ipcl_ref01_primary_model	.934
236	ReAlnet03	.933
237	ReAlnet03_cornet	.933
238	ReAlnet05_cornet	.933
239	convnext_tiny_sup	.933
240	alexnet-baseline	.933
241	alexnet	.933
242	alexnet	.933
243	alexnet	.933
244	AdvProp_efficientnet-b7	.933
245	ReAlnet05	.932
246	ReAlnet02_ALL	.933
247	alexnet	.932
248	alexnet	.932
249	alexnet	.931
250	r3m_resnet50	.931
251	mobilenet_v2_1.0_128-tf	.931
252	ReAlnet06_ALL	.931
253	alexnet	.931
254	ReAlnet01_ALL	.931
255	alexnet	.930
256	ReAlnet10_ALL	.930
257	mobilenet_v2_0_5_192	.929
258	BiT-S-R152x4	.929
259	resnet50_imagenet_full	.929
260	my-model	.929
261	BiT-S-R101x3	.928
262	mobilenet_v2_0_75_224	.927
263	BiT-M-R152x4	.927
264	resnet-18-LC_w_sh_1_iter_m	.926
265	alexnet_training_seed_01	.926
266	grcnn	.925
267	alexnet_training_seed_10	.924
268	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.924
269	ReAlnet01	.924
270	convnext_tiny_imagenet_full_seed-0	.924
271	ReAlnet08	.924
272	ReAlnet01_cornet	.924
273	ReAlnet08_cornet	.923
274	ReAlnet03_ALL	.923
275	compact_resnet50_V4	.923
276	mobilenet_v2_1.4_224-tf	.923
277	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.922
278	ReAlnet04	.922
279	efficientnet_b0_imagenet_full	.921
280	resnet-152_v2_pytorch	.922
281	resnet101	.921
282	ReAlnet05_ALL	.920
283	ReAlnet04_cornet	.921
284	ReAlnet02	.919
285	alexnet_fov16	.919
286	ReAlnet02_cornet	.919
287	compact_cornets_V4	.917
288	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.917
289	alexnet_reduced_aliasing_early_checkpoint	.917
290	resnet50_pretrained_with_retinal_waves	.918
291	compact_vgg19_V4	.916
292	alexnet_robust_correct	.918
293	ReAlnet07_ALL	.915
294	mobilenet_v2_1_0_128	.916
295	mobilenet_v2_1_0_160	.915
296	inception_v1	.914
297	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.914
298	BiT-M-R101x1	.914
299	alexnet_early_checkpoint	.913
300	inception_resnet_v2	.914
301	BiT-M-R101x3	.911
302	deit_small_imagenet_100_seed-0	.911
303	cornet_s	.911
304	convnext_small_imagenet_full_seed-0	.910
305	cvt_cvt-21-384-in1k_4_LucyV4	.909
306	densenet-169-keras	.907
307	convnext_small_imagenet_10_seed-0	.901
308	AlexNet_SIN_fov16	.897
309	alexnet_training_seed_03	.897
310	mobilenet_v2_1.3_224-tf	.894
311	CORnet-S	.894
312	omnivore_swinS	.893
313	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.893
314	0.5x_resnet-18_LC_w_sh_10_iter	.893
315	mobilenet_v2_1_0_192	.893
316	efficientnet-b7	.892
317	efficientnet_b2_imagenet_full	.891
318	compact_resnet50_IT	.891
319	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.890
320	mobilenet_v2_1.0_160-tf	.889
321	mobilenet_v2_1_3_224	.883
322	convnext_tiny:in12k_ft_in1k	.882
323	yudixie_resnet18_distance_reg_0_240719	.882
324	resnet50_imagenet_100_seed-0	.882
325	compact_resnet50_robust_IT	.882
326	mobilenet_v2_1.0_224-tf	.881
327	shufflenet_v2_x1_0	.877
328	alexnet_training_seed_01_fov4	.877
329	mobilenet_v2_1_4_224	.877
330	mobilenet_v2_1-4_224_pytorch	.876
331	mobilenet_v2_0.5_192-tf	.875
332	v1-pyr-nodown	.872
333	mobilenet_v2_1.0_192-tf	.872
334	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.867
335	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.868
336	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.867
337	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.867
338	alexnet_random_linf8_perturb	.867
339	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.866
340	mobilenet_v2_0.5_224-tf	.864
341	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.863
342	mobilenet_v2_0.35_224	.860
343	convnext_small_imagenet_1_seed-0	.859
344	omnivore_swinB	.854
345	BiT-S-R101x1	.848
346	vit_large_patch14_clip_224:laion2b_ft_in1k	.847
347	yolos_tiny	.845
348	BiT-M-R152x2	.843
349	mobilenet_v2_1.0_96	.838
350	resnet50	.837
351	resnet50_ewconplus_wzc	.827
352	alexnet_training_seed_08	.824
353	voneresnet-50-non_stochastic	.819
354	alexnet_training_seed_06	.817
355	mobilenet_v2_0.75_160-tf	.811
356	mobilenet_v2_0.5_160	.810
357	artResNet18_1	.801
358	ViT-B/32	.796
359	inception_v1-tf	.795
360	mobilenet_v2_1_0_224	.794
361	AlexNet_SIN_fov12	.790
362	mobilenet_v2_0.75_96	.783
363	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.780
364	alexnet_training_seed_05	.781
365	AdvProp_efficientnet-b0	.775
366	alexnet_fov12	.756
367	mobilenet_v2_0.75_128	.730
368	hmax	.689
369	mobilenet_v2_0.5_128	.689
370	my-model	.690
371	deit_small_imagenet_full_seed-0	.686
372	AdvProp_efficientnet-b4	.654
373	deit_small_imagenet_10_seed-0	.343
374	resnet50-meshes-lt-100-original-pretrained	.172
375	resnet50-meshes-lt-100-original-scratch	.116
376	mobilenet_v2_0.35_160
377	resnet18-supervised
378	fitvid_trained_on_physion
379	openclip
380	resnext101_32x32d_wsl
381	resnext101_32x48d_wsl
382	resnet50_ImageNet
383	regnet_y_400mf
384	tv_efficientnet-b1
385	alexnet_ks_torevert
386	yudixie_resnet50_imagenet1kpret_0_240312
387	resnet_152_v1
388	resnext101_32x16d_wsl
389	densenet_201_pytorch
390	pnasnet_large_pytorch
391	inception_v3_pytorch
392	inception_v4
393	nasnet_large
394	deit_small_imagenet_1_seed-0
395	pnasnet_large
396	vonegrcnn_62e_nobn
397	resnet_101_v2
398	resnet_152_v2
399	vonegrcnn_52e_full
400	resnet_101_v1

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: max_dc