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

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: max_dc