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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	yudixie_resnet50_rotation_reg_0_240908	.984
2	cvt_cvt-13-224-in1k_4_LucyV4	.982
3	resnet-18-LC_1st_conv_m	.975
4	BiT-S-R50x1	.973
5	convnext_femto_ols:d1_in1k	.973
6	cvt_cvt-21-224-in1k_4_LucyV4	.971
7	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.969
8	yudixie_resnet18_translation_reg_0_240719	.966
9	ReAlnet01_cornet_fov4	.962
10	BiT-M-R50x3	.961
11	xception	.962
12	yudixie_resnet50_distance_translation_rotation_0_240908	.958
13	yudixie_resnet50_category_class_0_240908	.958
14	compact_vgg19_V4	.958
15	compact_cornets_IT	.957
16	yudixie_resnet18_category_class_0_240719	.955
17	mobilenet_v2_1.0_224-tf	.951
18	resnet-152_v2-tf	.949
19	compact_resnet50_V4	.949
20	yudixie_resnet18_translation_rotation_0_240719	.946
21	efficientnet_b1_imagenet_full	.947
22	resnet-18-LC_d_w_sh_1x1_conv_init_m	.946
23	texture_shape_alexnet_trained_on_SIN	.944
24	convnext_large:fb_in22k_ft_in1k	.942
25	vgg_16	.942
26	resnet50_imagenet_100_seed-0	.942
27	briaai_rmbg_1_4	.941
28	inception_v1	.938
29	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.936
30	yudixie_resnet50_translation_rotation_0_240908	.935
31	efficientnet-b7	.935
32	alexnet_random_l2_3_perturb	.934
33	AdvProp_efficientnet-b6	.930
34	vgg_19	.929
35	yudixie_resnet50_distance_rotation_0_240908	.925
36	yudixie_resnet50_distance_reg_0_240908	.924
37	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
38	0.5x_resnet-18_LC	.923
39	resnet-18-LC_m	.922
40	alexnet_random_linf8_perturb	.921
41	grcnn_robust_v1	.921
42	resnet-18-LC_w_sh_1_iter_m	.919
43	resnet50_primary_visual_cortex	.919
44	resnet18_ecoset_full	.918
45	cvt_cvt-21-384-in1k_4_LucyV4	.917
46	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
47	AdvProp_efficientnet-b8	.915
48	vgg-16-keras	.916
49	yudixie_resnet50_distance_translation_0_240908	.912
50	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
51	inception_v3-tf	.912
52	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
53	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
54	compact_cornets_V4	.909
55	resnet-50_v1-tf	.909
56	grcnn	.908
57	mobilenet_v2_1.0_96	.906
58	blt_vs	.907
59	deepeisnn_ei_cifar10_vgg19	.906
60	alexnet_robust_correct	.905
61	resnext101_32x8d_wsl	.903
62	resnet18_fair	.902
63	grcnn_109	.902
64	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
65	resnet50_hvs_wzc	.901
66	BiT-S-R50x3	.897
67	alexnet_early_checkpoint	.899
68	grcnn_v2_text_noise	.898
69	BiT-S-R101x3	.895
70	nasnet_large-tf	.896
71	compact_resnet50_IT	.895
72	resnet18_imagenet21kP	.896
73	densenet-201-keras	.893
74	mobilenet_v2_1.3_224-tf	.893
75	mobilenet_v2_1.0_160-tf	.892
76	yudixie_resnet50_translation_reg_0_240908	.892
77	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.892
78	convnext_base_fb_in22k_ft_in1k	.891
79	resnet50_byol	.892
80	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
81	0.5x_resnet-18_LC_w_sh_10_iter	.890
82	yudixie_resnet50_object_class_0_240908	.889
83	alexnet_reduced_aliasing_early_checkpoint	.889
84	resnet50_ewconplus_wzc	.889
85	mobilenet_v2_0_75_192	.887
86	resnet50_imagenet_10_seed-0	.884
87	convnext_tiny_sup	.885
88	AdvProp_efficientnet-b7	.884
89	compact_resnet50_robust_V4	.883
90	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
91	alexnet_l2_3_robust	.882
92	ReAlnet01_cornet_fov16	.882
93	yudixie_resnet18_distance_rotation_0_240719	.882
94	yudixie_wbh_object_class_scaling_0415_run_3	.881
95	yudixie_wbh_object_class_scaling_0415_run_0	.881
96	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
97	compact_resnet50_robust_IT	.879
98	resnet101	.878
99	yudixie_resnet18_object_class_0_240719	.878
100	AlexNet_SIN_fov4	.877
101	squeezenet1_1	.877
102	densenet-201	.876
103	resnet50_st_wzc_seed6_2_323	.875
104	mobilenet_v1_1.0_128	.875
105	convnext_large_clip_laion2b_finelayers	.876
106	focalnet_tiny_lrf_in1k	.875
107	alexnet_linf_8_robust	.873
108	efficientnet_b0	.874
109	antialias-resnet152	.873
110	resnet_50_v2	.872
111	ReAlnet02	.872
112	ReAlnet02_cornet	.871
113	yudixie_resnet18_distance_translation_0_240719	.871
114	ReAlnet04	.871
115	ReAlnet03	.870
116	ReAlnet03_cornet	.867
117	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
118	ReAlnet04_cornet	.868
119	alexnet	.865
120	yudixie_resnet18_distance_translation_rotation_0_240719	.864
121	0.5x_resnet-18_LC_w_sh_100_iter	.865
122	inception_v3	.863
123	AlexNet_SIN	.863
124	resnet50-vitoimagevidnet8	.863
125	ReAlnet05	.863
126	ReAlnet05_cornet	.862
127	convnext_xlarge:fb_in22k_ft_in1k	.862
128	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
129	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
130	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
131	yudixie_wbh_object_class_scaling_0415_run_1	.861
132	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
133	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
134	omnivore_swinS	.862
135	resnet50-simclr-vissl	.861
136	ReAlnet01	.861
137	squeezenet1_0	.859
138	alexnet_fov16	.858
139	ReAlnet01_cornet	.858
140	AdvProp_efficientnet-b4	.858
141	convnext_xxlarge_clip	.858
142	mobilenet_v2_0_5_224	.858
143	mobilenet_v1_0.5_128	.857
144	ReAlnet08	.857
145	ReAlnet08_cornet	.857
146	ReAlnet07_cornet	.857
147	ReAlnet07	.857
148	resnet_50_v1_spiking_l4a	.855
149	ReAlnet09	.856
150	resnet_50_v1	.856
151	resnet_50_v1_spiking_l4	.856
152	resnet50-sup	.856
153	yudixie_resnet50_imagenet1kpret_0_240908	.855
154	ReAlnet09_cornet	.855
155	resnet50_tutorial	.855
156	resnet_50_v1_spiking_l3	.854
157	imagenet_l2_3_0	.855
158	ReAlnet10_cornet	.854
159	resnet_50_v1_spiking	.854
160	resnet50_st_wzc_seed7_2_323	.854
161	resnet50_ewconplus_wzc_seed5_2__323	.852
162	resnet50_ewconplus_wzc_seed2_2__323	.853
163	ReAlnet10	.852
164	alexnet_fov4	.852
165	resnet50-moclr8deg	.850
166	resnet50-vicregl0p9	.850
167	convnext_base_imagenet_full_seed-0	.848
168	convnext_tiny_imagenet_full_seed-0	.847
169	mobilenet_v2_1_0_128	.847
170	yudixie_wbh_object_class_scaling_0415_run_2	.845
171	ReAlnet06_cornet	.845
172	ReAlnet06	.845
173	mobilenet_v2_0.35_192	.843
174	inception_v4-tf	.843
175	convnext_base_fb_in1k	.842
176	inception_v2-tf	.843
177	convnext_large_in22k_supervised	.842
178	CLIP-RN50	.840
179	vonegrcnn_62e_nobn	.840
180	resnet50_random_linf8_perturb	.838
181	resnet-50-robust	.838
182	resnet50_robust_l2_eps1	.837
183	0.5x_resnet-18	.836
184	mobilenet_v1_0.5_160	.835
185	resnet50-vicregl0p75	.835
186	BiT-M-R101x1	.835
187	convnext_small_imagenet_100_seed-0	.835
188	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
189	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
190	resnet_SIN_IN_FT_IN	.832
191	mobilenet_v2_1_3_224	.832
192	mobilenet_v2_0.75_192-tf	.830
193	mobilenet_v2_1_4_224	.831
194	imagenet_l2_10_0	.831
195	resnet-18-LC_w_sh_10_iter_m	.830
196	Res2Net50_26w_4s	.830
197	CORnet-Z	.828
198	resnet101_imagenet_full	.826
199	omnivore_swinB	.825
200	resnet50_l2_3_robust	.825
201	resnet50	.822
202	antialiased-r50	.820
203	resnet18-supervised	.819
204	vgg-19-keras	.818
205	convnext_large_imagenet_full_seed-0	.818
206	alexnet_fov12	.818
207	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
208	resnet50_ewconplus_wzc_seed6_2_323	.817
209	resnet50_linf_8_robust	.817
210	AlexNet_SIN_fov12	.816
211	mobilenet_v2_0.5_96	.814
212	0.5x_resnet-18_LC_w_sh_1_iter	.813
213	resnet50-SIN_IN	.814
214	vit_base_patch16_clip_224:openai_ft_in1k	.813
215	resnet50-SIN_IN_IN	.813
216	resnet50_robust_l2_eps3	.812
217	resnet50_st_wzc_2	.813
218	mobilenet_v2_1.4_224-tf	.811
219	RN50	.812
220	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
221	resnet50_random_l2_perturb	.810
222	cornet_s	.808
223	CORnet-S	.806
224	vonealexnet_gaussian_noise_std4_fixed	.806
225	BiT-S-R152x2	.803
226	ReAlnet07_ALL	.802
227	resnet50_linf_4_robust	.800
228	ReAlnet08_ALL	.800
229	densenet-169	.799
230	ReAlnet04_ALL	.798
231	convnext_small_imagenet_full_seed-0	.797
232	resnet50_st_wzc_seed3_2_323	.796
233	deepeisnn_ei_imagenet_resnet18	.796
234	resnet-50x2_untrained	.797
235	AdvProp_efficientnet-b0	.796
236	ReAlnet06_ALL	.793
237	resnet50-SIN	.792
238	ReAlnet03_ALL	.792
239	ReAlnet02_ALL	.791
240	resnet-50_untrained	.791
241	ReAlnet10_ALL	.791
242	texture_shape_resnet50_trained_on_SIN	.791
243	resnet-101_v2-tf	.790
244	ReAlnet05_ALL	.789
245	ReAlnet01_ALL	.788
246	ReAlnet01_cornet_fov12	.787
247	resnet-18_untrained	.788
248	CLIP_resnet50_float32	.788
249	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
250	r3m_resnet34_nocrop	.787
251	CLIP_resnet50	.785
252	resnet-50_v2-tf	.786
253	compact_vgg19_IT	.786
254	ReAlnet09_ALL	.785
255	resnet34_imagenet_full	.777
256	yudixie_resnet18_imagenet1kpret_0_240719	.777
257	yudixie_wbh_object_class_scaling_0415_imagenet	.774
258	SWSL_resnet50	.773
259	resnet50-vicreg	.773
260	resnet-101_v1-tf	.771
261	mobilenet_v2_0.35_96	.769
262	resnet-18_test_m	.766
263	densenet-121	.765
264	convnext_tiny:in12k_ft_in1k	.763
265	dinov2_vitl14_lc_res336	.762
266	resnet152_imagenet_full	.761
267	resnet50_imagenet_full	.760
268	alexnet_training_seed_01_fov16	.760
269	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
270	voneresnet-50-non_stochastic	.759
271	resnet18_imagenet_full	.758
272	deit_small_imagenet_full_seed-0	.757
273	pnasnet_large-tf	.757
274	pnasnet_large_halfPrecision	.757
275	efficientnet_b0_imagenet_full	.756
276	mobilenet_v2_1.0_192-tf	.754
277	mobilenet_v2_1_0_192	.754
278	resnet34_ecoset_full	.754
279	resnet101_ecoset_full	.749
280	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
281	resnet-152_v1-tf	.745
282	mobilenet_v1_0.5_224	.744
283	alexnet_training_seed_01_fov12	.744
284	alexnet_training_seed_07	.743
285	yudixie_resnet18_distance_reg_0_240719	.742
286	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
287	mobilenet_v1_0.75_192	.739
288	shufflenet_v2_x1_0	.740
289	cvt_cvt-13-384-in1k_4_LucyV4	.739
290	mobilenet_v2_0_75_224	.738
291	BiT-S-R101x1	.736
292	BiT-M-R101x3	.732
293	AlexNet_SIN_fov16	.732
294	alexnet_training_seed_02	.730
295	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
296	FrankRobWobv0	.727
297	voneresnet-50-robust	.727
298	vggface	.727
299	mobilenet_v2_0.5_192-tf	.726
300	yudixie_resnet18_rotation_reg_0_240719	.725
301	resnet50-cifar	.722
302	BiT-M-R152x4	.721
303	antialiased-rnext101_32x8d	.717
304	BiT-S-R152x4	.716
305	vit_base_patch14_reg4_dinov2-lvd142m	.716
306	resnet50-VITO-8deg-cc	.715
307	voneresnet-50	.714
308	resnet152_ecoset_full	.709
309	mobilenet_v1_0.25_224	.709
310	VOneCORnet-S	.708
311	yolos_tiny	.707
312	densenet-121-keras	.703
313	resnet50_FractalDB	.703
314	mobilenet_v1_0.75_224	.701
315	vit_huge_clip336_laion	.702
316	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
317	alexnet_training_seed_04	.700
318	mobilenet_v2_0.75_128	.700
319	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
320	mobilenet_v1_0.25_160	.696
321	SWSL_resnext101_32x8d	.695
322	v1-pyr-nodown	.695
323	resnet-18-LC_w_sh_100_iter_m	.694
324	CLIP_ViT-B_32	.693
325	alexnet_training_seed_01	.693
326	deepeisnn_ei_cifar10_resnet18	.692
327	mobilenet_v1_1.0_224	.691
328	resnet50_ecoset_full	.691
329	omnivore_swinT	.690
330	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
331	densenet-169-keras	.687
332	my-model	.687
333	konkle_alexnetgn_ipcl_ref01_primary_model	.686
334	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
335	mobilenet_v2_1-4_224_pytorch	.684
336	alexnet_training_seed_09	.682
337	nasnet_mobile-tf	.681
338	mobilenet_v2_0.35_224	.680
339	mobilenet_v2_0_75_160	.680
340	effnetv2m_custom384	.676
341	eBarlow_lmda_02_1000ep	.676
342	resnet50-barlow	.675
343	mobilenet_v2_1.0_128-tf	.674
344	vision_transformer_vit_large_patch16_224	.670
345	mobilenet_v1_0.25_128	.668
346	convnext_base_fb_in1k_gram_aligned_dinov3	.667
347	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
348	vit_base_patch14_dinov2-lvd142m	.666
349	mobilenet_v2_1_0_160	.667
350	cv_18_dagger_408_pretrained	.665
351	dinov2_vitg14_reg_lc	.663
352	deit_small_imagenet_100_seed-0	.662
353	mobilenet_v1_0.5_192	.660
354	deit3_base_patch16_224_fb_in22k_ft_in1k	.661
355	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.660
356	resnet50_moco_v2	.658
357	resnet50_simclr	.657
358	custom_model_cv_18_dagger_408	.656
359	artResNet18_1	.655
360	nasnet_mobile	.654
361	eva02_large_in22k	.654
362	mobilenet_v2_1_0_224	.649
363	mobilenet_v1_1.0_192	.648
364	dinov2_vitl14_reg_lc_featread	.647
365	dinov2_vitl14_reg_lc	.647
366	yudixie_resnet50_random_0_240908	.646
367	effnetb1_272x240	.645
368	resnet-18-LC_conv_init_m	.644
369	alexnet_training_seed_10	.645
370	BiT-M-R152x2	.641
371	vit_large_clip336_openai	.635
372	AdvProp_efficientnet-b2	.627
373	mobilenet_v2_0.75_160-tf	.624
374	AT_efficientnet-b2	.625
375	vonegrcnn_52e_full	.623
376	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
377	vit_large_patch14_clip_224:openai_ft_in1k	.621
378	mobilenet_v2_0_5_192	.619
379	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
380	resnet-152_v2_pytorch	.615
381	convnext_small_imagenet_10_seed-0	.615
382	dinov2_vitl14_lc	.614
383	BiT-M-R50x1	.613
384	yudixie_resnet18_random_0_240719	.610
385	CORnetZ_CIFAR10_bs32_20_04	.605
386	vonegrcnn_47e	.604
387	inception_v1-tf	.600
388	mobilenet_v2_0.5_224-tf	.597
389	mobilenet_v1_1.0_160	.597
390	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.597
391	deit3_base_patch16_224_fb_in1k	.597
392	alexnet_training_seed_03	.596
393	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
394	deit_base_imagenet_full_seed-0	.589
395	r3m_resnet34	.590
396	vonegrcnn_47e	.581
397	deit_large_imagenet_full_seed-0	.577
398	mobilenet_v1_0.75_128	.570
399	mobilenet_v1_0.75_160	.565
400	mobilenet_v1_0.25_192	.560
401	mobilenet_v2_0.75_96	.557
402	inception_resnet_v2	.554
403	alexnet_training_seed_01_fov4	.554
404	efficientnet_b2_imagenet_full	.550
405	r3m_resnet50_nocrop	.550
406	hmax	.535
407	r3m_resnet50	.519
408	r3m_resnet18	.516
409	resnet50_pretrained_with_retinal_waves	.515
410	my-model	.493
411	mobilenet_v2_0.75_224-tf	.490
412	alexnet_training_seed_08	.462
413	convnext_small_imagenet_1_seed-0	.459
414	CORnetZ_CIFAR10	.447
415	vit_base_patch16_dinov3-lvd1689m	.445
416	ViT-B/32	.385
417	mobilenet_v2_0.35_128	.375
418	deit_small_imagenet_10_seed-0	.375
419	resnet50_imagenet_1_seed-0	.355
420	alexnet_training_seed_05	.271
421	mobilenet_v2_0.5_160	.271
422	alexnet_training_seed_06	.215
423	resnet-18-LC_untrained	.170
424	mobilenet_v2_0.5_128	.028
425	unet_entire
426	mobilenet_v2_0.35_160
427	fitvid_trained_on_physion
428	openclip
429	resnext101_32x32d_wsl
430	resnext101_32x48d_wsl
431	resnet50_ImageNet
432	resnet_101_v1
433	resnet_152_v2
434	regnet_y_400mf
435	tv_efficientnet-b1
436	alexnet_ks_torevert
437	yudixie_resnet50_imagenet1kpret_0_240312
438	resnet_152_v1
439	ViT_L_32_imagenet1k
440	resnext101_32x16d_wsl
441	densenet_201_pytorch
442	inception_v3_pytorch
443	pnasnet_large_pytorch
444	mobilevit_small
445	inception_v4
446	nasnet_large
447	deit_small_imagenet_1_seed-0
448	pnasnet_large
449	vonegrcnn_62e_nobn
450	resnet_101_v2
451	vonegrcnn_52e_full
452	pr1_stl10_disentangled_alpha04
453	predictive_coding_pc
454	dinov2_vitg14_lc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance