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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	1.0
4	efficientnet_b1_imagenet_full	1.0
5	cornet_s	1.0
6	convnext_femto_ols:d1_in1k	1.0
7	ReAlnet08	1.0
8	compact_resnet50_V4	1.0
9	0.5x_resnet-18_LC_w_sh_10_iter	1.0
10	resnet34_imagenet_full	1.0
11	yudixie_wbh_object_class_scaling_0415_run_1	1.0
12	yudixie_resnet18_translation_reg_0_240719	1.0
13	CORnetZ_CIFAR10_bs32_20_04	1.0
14	vonealexnet_gaussian_noise_std4_fixed	1.0
15	resnet-18-LC_w_sh_100_iter_conv_init_m	1.0
16	resnet-18-LC_w_sh_10_iter_conv_init_m	1.0
17	yudixie_resnet18_translation_rotation_0_240719	1.0
18	yudixie_wbh_object_class_scaling_0415_run_3	1.0
19	ReAlnet01_cornet_fov12	.999
20	yudixie_resnet18_distance_rotation_0_240719	.999
21	ReAlnet10	.999
22	ReAlnet01	1.0
23	ReAlnet03	.999
24	ReAlnet07_cornet	.999
25	ReAlnet03_cornet	.999
26	ReAlnet10_cornet	.999
27	voneresnet-50-non_stochastic	.999
28	ReAlnet07	.999
29	ReAlnet04	.999
30	ReAlnet04_cornet	.999
31	ReAlnet02	.999
32	resnet50_ecoset_full	.999
33	ReAlnet01_cornet	.999
34	convnext_tiny_imagenet_full_seed-0	.999
35	ReAlnet01_ALL	.999
36	yudixie_resnet50_distance_reg_0_240908	.999
37	ReAlnet09_ALL	.999
38	ReAlnet02_cornet	.999
39	CORnet-S	.999
40	ReAlnet06	.998
41	ReAlnet02_ALL	.998
42	alexnet_reduced_aliasing_early_checkpoint	.998
43	ReAlnet06_cornet	.999
44	ReAlnet05	.998
45	ReAlnet05_cornet	.999
46	compact_resnet50_robust_IT	.998
47	efficientnet-b7	.998
48	compact_cornets_IT	.998
49	yudixie_resnet50_distance_translation_0_240908	.998
50	resnet-18-LC_1st_conv_m	.998
51	resnet50_st_wzc_2	.998
52	yudixie_resnet18_distance_reg_0_240719	.997
53	yudixie_resnet50_rotation_reg_0_240908	.997
54	resnet18_imagenet_full	.997
55	yudixie_wbh_object_class_scaling_0415_run_0	.997
56	alexnet_training_seed_01_fov12	.997
57	compact_cornets_V4	.997
58	resnet34_ecoset_full	.996
59	convnext_small_imagenet_100_seed-0	.996
60	resnet-18-LC_w_sh_100_iter_m	.996
61	vgg_19	.996
62	0.5x_resnet-18	.996
63	omnivore_swinB	.996
64	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.996
65	yudixie_resnet18_category_class_0_240719	.996
66	ReAlnet08_ALL	.995
67	resnet152_imagenet_full	.995
68	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.996
69	yudixie_resnet50_translation_rotation_0_240908	.995
70	ReAlnet09_cornet	.995
71	ReAlnet09	.995
72	resnet-18_test_m	.995
73	resnet-50x2_untrained	.995
74	mobilenet_v2_1.0_224-tf	.995
75	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.994
76	yudixie_resnet50_distance_translation_rotation_0_240908	.995
77	AdvProp_efficientnet-b6	.994
78	yudixie_wbh_object_class_scaling_0415_run_2	.994
79	Res2Net50_26w_4s	.994
80	resnet-18-LC_w_sh_1_iter_conv_init_m	.994
81	alexnet_training_seed_01	.993
82	AlexNet_SIN_fov12	.993
83	focalnet_tiny_lrf_in1k	.993
84	alexnet_fov12	.993
85	ReAlnet03_ALL	.992
86	ReAlnet05_ALL	.992
87	yudixie_resnet50_translation_reg_0_240908	.992
88	ReAlnet10_ALL	.992
89	ReAlnet06_ALL	.991
90	resnet-18_untrained	.992
91	CORnet-Z	.991
92	ReAlnet07_ALL	.991
93	yudixie_resnet18_rotation_reg_0_240719	.991
94	yudixie_resnet50_distance_rotation_0_240908	.991
95	vonegrcnn_62e_nobn	.990
96	convnext_large:fb_in22k_ft_in1k	.990
97	AdvProp_efficientnet-b8	.989
98	resnet-50_untrained	.988
99	0.5x_resnet-18_LC_w_sh_1_iter	.988
100	ReAlnet01_cornet_fov4	.987
101	cvt_cvt-21-384-in1k_4_LucyV4	.986
102	AdvProp_efficientnet-b0	.986
103	hmax	.986
104	mobilenet_v2_1.3_224-tf	.986
105	mobilenet_v2_0.75_192-tf	.986
106	mobilenet_v2_0.75_160-tf	.986
107	mobilenet_v2_1.0_192-tf	.986
108	mobilenet_v2_1.0_160-tf	.986
109	mobilenet_v2_0.5_224-tf	.986
110	mobilenet_v2_0.75_128	.986
111	mobilenet_v2_0.5_160	.986
112	mobilenet_v2_1.0_128-tf	.986
113	mobilenet_v2_0.5_128	.986
114	mobilenet_v2_0.75_96	.986
115	inception_v1-tf	.986
116	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.986
117	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.986
118	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.986
119	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.986
120	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.986
121	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.986
122	omnivore_swinS	.986
123	mobilenet_v1_0.25_128	.986
124	convnext_tiny_sup	.986
125	mobilenet_v2_1_0_128	.986
126	deit_small_imagenet_10_seed-0	.986
127	deit_small_imagenet_full_seed-0	.986
128	convnext_small_imagenet_full_seed-0	.986
129	compact_resnet50_robust_V4	.986
130	ReAlnet01_cornet_fov16	.986
131	mobilenet_v2_1_0_224	.986
132	compact_vgg19_IT	.986
133	deepeisnn_ei_cifar10_resnet18	.986
134	0.5x_resnet-18_LC_w_sh_100_iter	.986
135	resnet101	.985
136	resnet-18-LC_w_sh_10_iter_m	.984
137	resnet50-vicregl0p9	.984
138	mobilenet_v2_1.4_224-tf	.984
139	alexnet_random_l2_3_perturb	.984
140	barlow-twins-resnet50	.983
141	BiT-M-R50x3	.982
142	yudixie_resnet18_distance_translation_0_240719	.982
143	compact_resnet50_IT	.982
144	yudixie_resnet18_distance_translation_rotation_0_240719	.981
145	resnet152_ecoset_full	.981
146	texture_shape_alexnet_trained_on_SIN	.981
147	BiT-M-R101x1	.981
148	mobilenet_v2_1-4_224_pytorch	.980
149	compact_vgg19_V4	.979
150	resnet50_primary_visual_cortex	.979
151	alexnet_fov16	.979
152	mobilenet_v2_1_4_224	.978
153	resnet-18-LC_w_sh_1_iter_m	.977
154	resnet50_st_wzc_2_323	.977
155	yudixie_resnet18_object_class_0_240719	.975
156	resnet50-simclr-vissl	.975
157	convnext_base_fb_in1k	.975
158	resnet50-vitoimagevidnet8	.975
159	resnet-18-LC_m	.975
160	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.974
161	vggface	.974
162	alexnet_training_seed_01_fov16	.972
163	cvt_cvt-13-224-in1k_4_LucyV4	.971
164	alexnet_training_seed_09	.971
165	alexnet_early_checkpoint	.970
166	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.970
167	resnet50_st_wzc_seed4_2_323	.969
168	resnet-18-LC_d_w_sh_1x1_conv_init_m	.968
169	vgg_16	.966
170	resnet50_ewconplus_wzc	.966
171	convnext_base:clip_laiona_augreg_ft_in1k_384	.966
172	resnet50_ewconplus_wzc_seed5_2__323	.965
173	yudixie_resnet50_random_0_240908	.965
174	alexnet_training_seed_07	.965
175	convnext_base_fb_in22k_ft_in1k	.965
176	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.964
177	blt_vs	.963
178	resnet-152_v2-tf	.964
179	resnet101_ecoset_full	.964
180	cvt_cvt-21-224-in1k_4_LucyV4	.963
181	yudixie_resnet50_category_class_0_240908	.962
182	yudixie_resnet18_random_0_240719	.958
183	resnet50_imagenet_100_seed-0	.958
184	resnet50_ewconplus_wzc_seed4_2_323	.956
185	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.956
186	resnet50_st_wzc_seed5_2_323	.955
187	resnext101_32x8d_wsl	.954
188	deepeisnn_ei_cifar10_vgg19	.953
189	alexnet_training_seed_04	.953
190	resnet50_ewconplus_wzc_seed7_2_323	.952
191	alexnet_robust_correct	.952
192	convnext_tiny:in12k_ft_in1k	.951
193	resnet50_ewconplus_wzc_2_323	.950
194	BiT-S-R50x1	.949
195	resnet50_ewconplus_wzc_seed6_2_323	.949
196	resnet50_ewconplus_wzc_seed2_2__323	.948
197	vgg-16-keras	.948
198	resnet50_st_wzc_noseed_2_323	.947
199	resnet50_ewconplus_wzc_seed3_2_323	.948
200	yudixie_resnet18_imagenet1kpret_0_240719	.946
201	yudixie_wbh_object_class_scaling_0415_imagenet	.946
202	xception	.946
203	inception_v3-tf	.945
204	resnet50_imagenet_10_seed-0	.945
205	resnet18_ecoset_full	.942
206	resnet50_st_wzc_seed7_2_323	.941
207	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.941
208	resnet101_imagenet_full	.941
209	resnet50-SIN_IN	.940
210	AlexNet_SIN	.939
211	convnext_large_imagenet_full_seed-0	.939
212	0.5x_resnet-18_LC	.939
213	mobilenet_v2_0_75_192	.939
214	inception_v3	.937
215	resnet-152_v2_pytorch	.937
216	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.936
217	CLIP-RN50	.935
218	resnet50_byol	.935
219	alexnet_training_seed_10	.933
220	resnet50-cifar	.933
221	mobilenet_v2_0.5_192-tf	.933
222	mobilenet_v2_0_5_224	.931
223	convnext_base_imagenet_full_seed-0	.931
224	resnet18_imagenet21kP	.931
225	resnet50_st_wzc_seed3_2_323	.930
226	voneresnet-50	.929
227	resnet-50_v1-tf	.928
228	BiT-S-R152x2	.927
229	convnext_xlarge:fb_in22k_ft_in1k	.927
230	briaai_rmbg_1_4	.927
231	alexnet_fov4	.926
232	vit_base_patch14_reg4_dinov2-lvd142m	.926
233	resnet50_st_wzc_seed6_2_323	.926
234	CLIP_resnet50_float32	.925
235	CLIP_resnet50	.925
236	resnet50-vicregl0p75	.925
237	RN50	.925
238	VOneCORnet-S	.924
239	voneresnet-50-robust	.923
240	grcnn	.921
241	resnet50_ewconplus_noseed_2_323	.921
242	grcnn_robust_v1	.919
243	mobilenet_v2_1.0_96	.919
244	BiT-S-R101x3	.917
245	convnext_base_fb_in1k_gram_aligned_dinov3	.916
246	alexnet_training_seed_02	.915
247	yudixie_resnet50_object_class_0_240908	.914
248	grcnn_109	.913
249	resnet18_fair	.913
250	grcnn_v2_text_noise	.912
251	r3m_resnet34_nocrop	.911
252	inception_v2-tf	.911
253	BiT-S-R50x3	.909
254	AlexNet_SIN_fov4	.909
255	cvt_cvt-13-384-in1k_4_LucyV4	.909
256	resnet50_robust_l2_eps1	.908
257	alexnet_l2_3_robust	.907
258	resnet-50-robust	.907
259	resnet50-moclr8deg	.906
260	BiT-S-R152x4	.905
261	alexnet_random_linf8_perturb	.905
262	nasnet_large-tf	.905
263	alexnet	.901
264	resnet50_random_l2_perturb	.901
265	resnet50_random_linf8_perturb	.900
266	resnet-50_v2-tf	.898
267	resnet50_tutorial	.898
268	resnet50-sup	.897
269	resnet_50_v1_spiking	.897
270	resnet_SIN_IN_FT_IN	.897
271	yudixie_resnet50_imagenet1kpret_0_240908	.897
272	resnet_50_v1	.897
273	resnet_50_v1_spiking_l4a	.896
274	resnet50-SIN	.896
275	resnet_50_v1_spiking_l3	.896
276	resnet_50_v1_spiking_l4	.896
277	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.895
278	vit_base_patch14_dinov2-lvd142m	.895
279	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.895
280	BiT-S-R101x1	.894
281	inception_v1	.893
282	antialias-resnet152	.893
283	densenet-201-keras	.892
284	my-model	.891
285	imagenet_l2_10_0	.890
286	alexnet_linf_8_robust	.889
287	efficientnet_b2_imagenet_full	.889
288	mobilenet_v2_1_3_224	.888
289	densenet-201	.886
290	resnet-18-LC_conv_init_m	.885
291	SWSL_resnet50	.884
292	efficientnet_b0	.884
293	densenet-169	.883
294	SWSL_resnext101_32x8d	.883
295	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.880
296	AdvProp_efficientnet-b4	.880
297	resnet50-vicreg	.879
298	resnet50-SIN_IN_IN	.878
299	ViT_L_32_imagenet1k	.877
300	resnet50	.877
301	resnet_50_v2	.876
302	resnet-152_v1-tf	.876
303	vgg-19-keras	.873
304	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.873
305	texture_shape_resnet50_trained_on_SIN	.871
306	imagenet_l2_3_0	.871
307	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.870
308	antialiased-r50	.868
309	alexnet_training_seed_03	.868
310	inception_v4-tf	.865
311	AdvProp_efficientnet-b7	.862
312	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.860
313	effnetv2m_custom384	.860
314	BiT-M-R152x4	.857
315	mobilevit_small	.855
316	shufflenet_v2_x1_0	.848
317	resnet50-VITO-8deg-cc	.846
318	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.846
319	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.846
320	densenet-121-keras	.845
321	densenet-121	.844
322	resnet50_robust_l2_eps3	.839
323	nasnet_mobile	.839
324	resnet-101_v1-tf	.838
325	mobilenet_v2_0_75_160	.838
326	r3m_resnet50	.838
327	resnet50_l2_3_robust	.835
328	artResNet18_1	.834
329	resnet50-barlow	.834
330	efficientnet_b0_imagenet_full	.828
331	resnet50_linf_8_robust	.828
332	resnet50_FractalDB	.828
333	resnet-101_v2-tf	.827
334	resnet50_imagenet_full	.826
335	vision_transformer_vit_large_patch16_224	.826
336	vonegrcnn_47e	.823
337	densenet-169-keras	.821
338	BiT-M-R50x1	.820
339	aughost_fair_resnet18	.820
340	deit_small_imagenet_100_seed-0	.820
341	resnet50_linf_4_robust	.813
342	mobilenet_v2_0_5_192	.813
343	nasnet_mobile-tf	.812
344	konkle_alexnetgn_ipcl_ref01_primary_model	.805
345	eBarlow_lmda_02_1000ep	.803
346	pnasnet_large-tf	.800
347	pnasnet_large_halfPrecision	.799
348	r3m_resnet50_nocrop	.797
349	vit_base_patch16_clip_224:openai_ft_in1k	.797
350	mobilenet_v2_0_75_224	.797
351	AT_efficientnet-b2	.795
352	mobilenet_v2_1_0_192	.795
353	vonegrcnn_52e_full	.795
354	vit_large_patch14_clip_336:laion2b_ft_in1k	.795
355	AdvProp_efficientnet-b2	.795
356	convnext_small_imagenet_1_seed-0	.793
357	vonegrcnn_47e	.793
358	deepeisnn_ei_imagenet_resnet18	.789
359	effnetb1_272x240	.787
360	BiT-M-R101x3	.786
361	resnet50_moco_v2	.782
362	vonegrcnn_52e_full	.781
363	antialiased-rnext101_32x8d	.780
364	resnet50_simclr	.774
365	mobilenet_v2_0.35_224	.771
366	mobilenet_v2_1_0_160	.765
367	r3m_resnet18	.754
368	cv_18_dagger_408_pretrained	.754
369	deit_large_imagenet_full_seed-0	.748
370	alexnet_training_seed_08	.748
371	custom_model_cv_18_dagger_408	.747
372	vit_large_patch14_clip_224:laion2b_ft_in1k	.742
373	omnivore_swinT	.736
374	FrankRobWobv0	.735
375	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.734
376	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.733
377	alexnet_training_seed_01_fov4	.732
378	r3m_resnet34	.718
379	convnext_small_imagenet_10_seed-0	.718
380	BiT-M-R152x2	.711
381	vit_relpos_base_patch16_clsgap_224:sw_in1k	.694
382	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.692
383	CLIP_ViT-B_32	.686
384	AlexNet_SIN_fov16	.684
385	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.681
386	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.679
387	deit3_base_patch16_224_fb_in22k_ft_in1k	.679
388	vit_large_patch14_clip_224:openai_ft_in1k	.676
389	vit_base_patch16_dinov3-lvd1689m	.673
390	yolos_tiny	.672
391	inception_resnet_v2	.662
392	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.648
393	mobilenet_v2_0.75_224-tf	.643
394	deit_base_imagenet_full_seed-0	.628
395	resnet50	.607
396	CORnetZ_CIFAR10	.601
397	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.578
398	deit3_base_patch16_224_fb_in1k	.578
399	my-model	.557
400	alexnet_training_seed_05	.513
401	resnet50_pretrained_with_retinal_waves	.481
402	ViT-B/32	.370
403	resnet50_imagenet_1_seed-0	.322
404	alexnet_training_seed_06	.321
405	resnet-18-LC_untrained	.274
406	resnet50-meshes-lt-100-original-pretrained	.138
407	resnet50-meshes-lt-100-original-scratch	.052
408	mobilenet_v2_0.35_160
409	resnet18-supervised
410	fitvid_trained_on_physion
411	openclip
412	resnext101_32x32d_wsl
413	resnext101_32x48d_wsl
414	resnet50_ImageNet
415	regnet_y_400mf
416	tv_efficientnet-b1
417	resnet_101_v1
418	alexnet_ks_torevert
419	yudixie_resnet50_imagenet1kpret_0_240312
420	resnet_152_v1
421	resnext101_32x16d_wsl
422	densenet_201_pytorch
423	inception_v3_pytorch
424	pnasnet_large_pytorch
425	inception_v4
426	nasnet_large
427	deit_small_imagenet_1_seed-0
428	pnasnet_large
429	resnet_101_v2
430	vonegrcnn_62e_nobn
431	resnet_152_v2
432	pr1_stl10_disentangled_alpha04
433	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.99.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_selective