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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	ReAlnet08_cornet	1.0
2	v1-pyr-nodown	1.0
3	ReAlnet04_ALL	1.000
4	efficientnet_b1_imagenet_full	1.0
5	cornet_s	1.000
6	convnext_femto_ols:d1_in1k	1.0
7	ReAlnet08	1.000
8	0.5x_resnet-18_LC_w_sh_10_iter	1.0
9	resnet34_imagenet_full	1.0
10	yudixie_resnet18_translation_reg_0_240719	1.000
11	CORnetZ_CIFAR10_bs32_20_04	1.0
12	vonealexnet_gaussian_noise_std4_fixed	1.000
13	resnet-18-LC_w_sh_100_iter_conv_init_m	1.000
14	resnet-18-LC_w_sh_10_iter_conv_init_m	1.000
15	yudixie_resnet18_translation_rotation_0_240719	1.000
16	yudixie_resnet18_distance_rotation_0_240719	.999
17	ReAlnet10	.999
18	ReAlnet01	1.000
19	ReAlnet03	.999
20	ReAlnet07_cornet	.999
21	ReAlnet03_cornet	.999
22	ReAlnet10_cornet	.999
23	voneresnet-50-non_stochastic	.999
24	ReAlnet07	.999
25	ReAlnet04	.999
26	ReAlnet04_cornet	.999
27	ReAlnet02	.999
28	resnet50_ecoset_full	.999
29	ReAlnet01_cornet	.999
30	convnext_tiny_imagenet_full_seed-0	.999
31	ReAlnet01_ALL	.999
32	yudixie_resnet50_distance_reg_0_240908	.999
33	ReAlnet09_ALL	.999
34	ReAlnet02_cornet	.999
35	CORnet-S	.999
36	ReAlnet06	.998
37	ReAlnet02_ALL	.998
38	alexnet_reduced_aliasing_early_checkpoint	.998
39	ReAlnet06_cornet	.999
40	ReAlnet05	.998
41	ReAlnet05_cornet	.999
42	efficientnet-b7	.998
43	yudixie_resnet50_distance_translation_0_240908	.998
44	resnet-18-LC_1st_conv_m	.998
45	yudixie_resnet18_distance_reg_0_240719	.997
46	yudixie_resnet50_rotation_reg_0_240908	.997
47	resnet18_imagenet_full	.997
48	resnet34_ecoset_full	.996
49	convnext_small_imagenet_100_seed-0	.996
50	alexnet	.996
51	resnet-18-LC_w_sh_100_iter_m	.996
52	vgg_19	.996
53	0.5x_resnet-18	.996
54	omnivore_swinB	.996
55	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.996
56	yudixie_resnet18_category_class_0_240719	.996
57	ReAlnet08_ALL	.995
58	resnet152_imagenet_full	.995
59	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.996
60	yudixie_resnet50_translation_rotation_0_240908	.995
61	ReAlnet09_cornet	.995
62	ReAlnet09	.995
63	resnet-18_test_m	.995
64	resnet-50x2_untrained	.995
65	mobilenet_v2_1.0_224-tf	.995
66	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.994
67	yudixie_resnet50_distance_translation_rotation_0_240908	.995
68	AdvProp_efficientnet-b6	.994
69	Res2Net50_26w_4s	.994
70	resnet-18-LC_w_sh_1_iter_conv_init_m	.994
71	alexnet_training_seed_01	.993
72	focalnet_tiny_lrf_in1k	.993
73	ReAlnet03_ALL	.992
74	ReAlnet05_ALL	.992
75	yudixie_resnet50_translation_reg_0_240908	.992
76	ReAlnet10_ALL	.992
77	ReAlnet06_ALL	.991
78	resnet-18_untrained	.992
79	CORnet-Z	.991
80	ReAlnet07_ALL	.991
81	yudixie_resnet18_rotation_reg_0_240719	.991
82	yudixie_resnet50_distance_rotation_0_240908	.991
83	vonegrcnn_62e_nobn	.990
84	convnext_large:fb_in22k_ft_in1k	.990
85	AdvProp_efficientnet-b8	.989
86	resnet-50_untrained	.988
87	0.5x_resnet-18_LC_w_sh_1_iter	.988
88	cvt_cvt-21-384-in1k_4_LucyV4	.986
89	AdvProp_efficientnet-b0	.986
90	hmax	.986
91	mobilenet_v2_1.3_224-tf	.986
92	mobilenet_v2_0.75_192-tf	.986
93	mobilenet_v2_0.75_160-tf	.986
94	mobilenet_v2_1.0_192-tf	.986
95	mobilenet_v2_1.0_160-tf	.986
96	mobilenet_v2_0.5_224-tf	.986
97	mobilenet_v2_0.75_128	.986
98	mobilenet_v2_0.5_160	.986
99	mobilenet_v2_1.0_128-tf	.986
100	mobilenet_v2_0.5_128	.986
101	mobilenet_v2_0.75_96	.986
102	inception_v1-tf	.986
103	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.986
104	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.986
105	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.986
106	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.986
107	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.986
108	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.986
109	omnivore_swinS	.986
110	mobilenet_v1_0.25_128	.986
111	convnext_tiny_sup	.986
112	mobilenet_v2_1_0_128	.986
113	deit_small_imagenet_10_seed-0	.986
114	deit_small_imagenet_full_seed-0	.986
115	convnext_small_imagenet_full_seed-0	.986
116	mobilenet_v2_1_0_224	.986
117	0.5x_resnet-18_LC_w_sh_100_iter	.986
118	resnet101	.985
119	resnet-18-LC_w_sh_10_iter_m	.984
120	resnet50-vicregl0p9	.984
121	mobilenet_v2_1.4_224-tf	.984
122	alexnet_random_l2_3_perturb	.984
123	barlow-twins-resnet50	.983
124	BiT-M-R50x3	.982
125	yudixie_resnet18_distance_translation_0_240719	.982
126	yudixie_resnet18_distance_translation_rotation_0_240719	.981
127	resnet152_ecoset_full	.981
128	texture_shape_alexnet_trained_on_SIN	.981
129	BiT-M-R101x1	.981
130	mobilenet_v2_1-4_224_pytorch	.980
131	resnet50_primary_visual_cortex	.979
132	mobilenet_v2_1_4_224	.978
133	resnet-18-LC_w_sh_1_iter_m	.977
134	yudixie_resnet18_object_class_0_240719	.975
135	resnet50-simclr-vissl	.975
136	resnet50-vitoimagevidnet8	.975
137	resnet-18-LC_m	.975
138	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.974
139	vggface	.974
140	cvt_cvt-13-224-in1k_4_LucyV4	.971
141	alexnet_training_seed_09	.971
142	alexnet_early_checkpoint	.970
143	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.970
144	resnet-18-LC_d_w_sh_1x1_conv_init_m	.968
145	vgg_16	.966
146	convnext_base:clip_laiona_augreg_ft_in1k_384	.966
147	yudixie_resnet50_random_0_240908	.965
148	alexnet_training_seed_07	.965
149	blt_vs	.963
150	resnet-152_v2-tf	.964
151	resnet101_ecoset_full	.964
152	cvt_cvt-21-224-in1k_4_LucyV4	.963
153	yudixie_resnet50_category_class_0_240908	.962
154	yudixie_resnet18_random_0_240719	.958
155	resnet50_imagenet_100_seed-0	.958
156	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.956
157	resnext101_32x8d_wsl	.954
158	alexnet_training_seed_04	.953
159	alexnet_robust_correct	.952
160	convnext_tiny:in12k_ft_in1k	.951
161	BiT-S-R50x1	.949
162	vgg-16-keras	.948
163	yudixie_resnet18_imagenet1kpret_0_240719	.946
164	xception	.946
165	inception_v3-tf	.945
166	resnet50_imagenet_10_seed-0	.945
167	resnet18_ecoset_full	.942
168	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.941
169	resnet101_imagenet_full	.941
170	resnet50-SIN_IN	.940
171	AlexNet_SIN	.939
172	convnext_large_imagenet_full_seed-0	.939
173	0.5x_resnet-18_LC	.939
174	mobilenet_v2_0_75_192	.939
175	inception_v3	.937
176	resnet-152_v2_pytorch	.937
177	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.936
178	CLIP-RN50	.935
179	resnet50_byol	.935
180	alexnet_training_seed_10	.933
181	resnet50-cifar	.933
182	mobilenet_v2_0.5_192-tf	.933
183	mobilenet_v2_0_5_224	.931
184	convnext_base_imagenet_full_seed-0	.931
185	resnet18_imagenet21kP	.931
186	voneresnet-50	.929
187	resnet-50_v1-tf	.928
188	BiT-S-R152x2	.927
189	convnext_xlarge:fb_in22k_ft_in1k	.927
190	briaai_rmbg_1_4	.927
191	CLIP_resnet50_float32	.925
192	CLIP_resnet50	.925
193	resnet50-vicregl0p75	.925
194	RN50	.925
195	VOneCORnet-S	.924
196	voneresnet-50-robust	.923
197	grcnn	.921
198	grcnn_robust_v1	.919
199	mobilenet_v2_1.0_96	.919
200	BiT-S-R101x3	.917
201	alexnet_training_seed_02	.915
202	yudixie_resnet50_object_class_0_240908	.914
203	grcnn_109	.913
204	grcnn_v2_text_noise	.912
205	r3m_resnet34_nocrop	.911
206	inception_v2-tf	.911
207	BiT-S-R50x3	.909
208	cvt_cvt-13-384-in1k_4_LucyV4	.909
209	resnet50_robust_l2_eps1	.908
210	alexnet_l2_3_robust	.907
211	resnet-50-robust	.907
212	resnet50-moclr8deg	.906
213	BiT-S-R152x4	.905
214	alexnet_random_linf8_perturb	.905
215	nasnet_large-tf	.905
216	alexnet	.901
217	resnet50_random_l2_perturb	.901
218	alexnet	.901
219	alexnet	.900
220	alexnet-baseline	.900
221	alexnet	.900
222	resnet50_random_linf8_perturb	.900
223	alexnet	.900
224	alexnet	.900
225	alexnet	.900
226	resnet-50_v2-tf	.898
227	resnet50_tutorial	.898
228	resnet50-sup	.897
229	resnet_50_v1_spiking	.897
230	resnet_SIN_IN_FT_IN	.897
231	yudixie_resnet50_imagenet1kpret_0_240908	.897
232	resnet_50_v1	.897
233	resnet_50_v1_spiking_l4a	.896
234	resnet50-SIN	.896
235	resnet_50_v1_spiking_l3	.896
236	resnet_50_v1_spiking_l4	.896
237	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.895
238	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.895
239	BiT-S-R101x1	.894
240	inception_v1	.893
241	antialias-resnet152	.893
242	densenet-201-keras	.892
243	my-model	.891
244	imagenet_l2_10_0	.890
245	alexnet_linf_8_robust	.889
246	efficientnet_b2_imagenet_full	.889
247	mobilenet_v2_1_3_224	.888
248	densenet-201	.886
249	resnet-18-LC_conv_init_m	.885
250	SWSL_resnet50	.884
251	efficientnet_b0	.884
252	densenet-169	.883
253	SWSL_resnext101_32x8d	.883
254	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.880
255	AdvProp_efficientnet-b4	.880
256	resnet50-vicreg	.879
257	resnet50-SIN_IN_IN	.878
258	ViT_L_32_imagenet1k	.877
259	resnet50	.877
260	resnet_50_v2	.876
261	resnet-152_v1-tf	.876
262	vgg-19-keras	.873
263	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.873
264	texture_shape_resnet50_trained_on_SIN	.871
265	imagenet_l2_3_0	.871
266	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.870
267	antialiased-r50	.868
268	alexnet_training_seed_03	.868
269	inception_v4-tf	.865
270	AdvProp_efficientnet-b7	.862
271	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.860
272	effnetv2m_custom384	.860
273	BiT-M-R152x4	.857
274	mobilevit_small	.855
275	shufflenet_v2_x1_0	.848
276	resnet50-VITO-8deg-cc	.846
277	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.846
278	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.846
279	densenet-121-keras	.845
280	densenet-121	.844
281	resnet50_robust_l2_eps3	.839
282	nasnet_mobile	.839
283	resnet-101_v1-tf	.838
284	mobilenet_v2_0_75_160	.838
285	r3m_resnet50	.838
286	resnet50_l2_3_robust	.835
287	artResNet18_1	.834
288	resnet50-barlow	.834
289	efficientnet_b0_imagenet_full	.828
290	resnet50_linf_8_robust	.828
291	resnet50_FractalDB	.828
292	resnet-101_v2-tf	.827
293	resnet50_imagenet_full	.826
294	vision_transformer_vit_large_patch16_224	.826
295	vonegrcnn_47e	.823
296	densenet-169-keras	.821
297	BiT-M-R50x1	.820
298	deit_small_imagenet_100_seed-0	.820
299	resnet50_linf_4_robust	.813
300	mobilenet_v2_0_5_192	.813
301	nasnet_mobile-tf	.812
302	konkle_alexnetgn_ipcl_ref01_primary_model	.805
303	pnasnet_large-tf	.800
304	r3m_resnet50_nocrop	.797
305	vit_base_patch16_clip_224:openai_ft_in1k	.797
306	mobilenet_v2_0_75_224	.797
307	AT_efficientnet-b2	.795
308	mobilenet_v2_1_0_192	.795
309	vonegrcnn_52e_full	.795
310	vit_large_patch14_clip_336:laion2b_ft_in1k	.795
311	AdvProp_efficientnet-b2	.795
312	convnext_small_imagenet_1_seed-0	.793
313	vonegrcnn_47e	.793
314	effnetb1_272x240	.787
315	BiT-M-R101x3	.786
316	resnet50_moco_v2	.782
317	vonegrcnn_52e_full	.781
318	antialiased-rnext101_32x8d	.780
319	resnet50_simclr	.774
320	mobilenet_v2_0.35_224	.771
321	mobilenet_v2_1_0_160	.765
322	r3m_resnet18	.754
323	cv_18_dagger_408_pretrained	.754
324	deit_large_imagenet_full_seed-0	.748
325	alexnet_training_seed_08	.748
326	custom_model_cv_18_dagger_408	.747
327	vit_large_patch14_clip_224:laion2b_ft_in1k	.742
328	omnivore_swinT	.736
329	FrankRobWobv0	.735
330	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.734
331	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.733
332	r3m_resnet34	.718
333	convnext_small_imagenet_10_seed-0	.718
334	BiT-M-R152x2	.711
335	vit_relpos_base_patch16_clsgap_224:sw_in1k	.694
336	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.692
337	CLIP_ViT-B_32	.686
338	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.681
339	vit_large_patch14_clip_224:openai_ft_in1k	.676
340	yolos_tiny	.672
341	inception_resnet_v2	.662
342	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.648
343	mobilenet_v2_0.75_224-tf	.643
344	deit_base_imagenet_full_seed-0	.628
345	resnet50	.607
346	CORnetZ_CIFAR10	.601
347	my-model	.557
348	alexnet_training_seed_05	.513
349	resnet50_pretrained_with_retinal_waves	.481
350	ViT-B/32	.370
351	resnet50_imagenet_1_seed-0	.322
352	alexnet_training_seed_06	.321
353	resnet-18-LC_untrained	.274
354	resnet50-meshes-lt-100-original-pretrained	.138
355	resnet50-meshes-lt-100-original-scratch	.052
356	mobilenet_v2_0.35_160
357	resnet18-supervised
358	fitvid_trained_on_physion
359	openclip
360	resnext101_32x32d_wsl
361	resnext101_32x48d_wsl
362	resnet50_ImageNet
363	regnet_y_400mf
364	tv_efficientnet-b1
365	resnet_101_v1
366	alexnet_ks_torevert
367	yudixie_resnet50_imagenet1kpret_0_240312
368	resnet_152_v1
369	resnext101_32x16d_wsl
370	densenet_201_pytorch
371	inception_v3_pytorch
372	pnasnet_large_pytorch
373	inception_v4
374	nasnet_large
375	deit_small_imagenet_1_seed-0
376	pnasnet_large
377	resnet_101_v2
378	vonegrcnn_62e_nobn
379	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.99.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_selective