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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	alexnet	.926
36	yudixie_resnet50_distance_rotation_0_240908	.925
37	yudixie_resnet50_distance_reg_0_240908	.924
38	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
39	0.5x_resnet-18_LC	.923
40	resnet-18-LC_m	.922
41	alexnet_random_linf8_perturb	.921
42	grcnn_robust_v1	.921
43	resnet-18-LC_w_sh_1_iter_m	.919
44	resnet50_primary_visual_cortex	.919
45	resnet18_ecoset_full	.918
46	cvt_cvt-21-384-in1k_4_LucyV4	.917
47	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
48	AdvProp_efficientnet-b8	.915
49	vgg-16-keras	.916
50	yudixie_resnet50_distance_translation_0_240908	.912
51	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
52	inception_v3-tf	.912
53	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
54	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
55	compact_cornets_V4	.909
56	resnet-50_v1-tf	.909
57	grcnn	.908
58	mobilenet_v2_1.0_96	.906
59	blt_vs	.907
60	alexnet_robust_correct	.905
61	resnext101_32x8d_wsl	.903
62	grcnn_109	.902
63	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
64	BiT-S-R50x3	.897
65	alexnet_early_checkpoint	.899
66	grcnn_v2_text_noise	.898
67	BiT-S-R101x3	.895
68	nasnet_large-tf	.896
69	compact_resnet50_IT	.895
70	resnet18_imagenet21kP	.896
71	densenet-201-keras	.893
72	mobilenet_v2_1.3_224-tf	.893
73	mobilenet_v2_1.0_160-tf	.892
74	yudixie_resnet50_translation_reg_0_240908	.892
75	resnet50_byol	.892
76	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
77	0.5x_resnet-18_LC_w_sh_10_iter	.890
78	yudixie_resnet50_object_class_0_240908	.889
79	alexnet_reduced_aliasing_early_checkpoint	.889
80	resnet50_ewconplus_wzc	.889
81	mobilenet_v2_0_75_192	.887
82	resnet50_imagenet_10_seed-0	.884
83	convnext_tiny_sup	.885
84	AdvProp_efficientnet-b7	.884
85	compact_resnet50_robust_V4	.883
86	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
87	alexnet_l2_3_robust	.882
88	ReAlnet01_cornet_fov16	.882
89	yudixie_resnet18_distance_rotation_0_240719	.882
90	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
91	compact_resnet50_robust_IT	.879
92	resnet101	.878
93	yudixie_resnet18_object_class_0_240719	.878
94	AlexNet_SIN_fov4	.877
95	squeezenet1_1	.877
96	densenet-201	.876
97	mobilenet_v1_1.0_128	.875
98	focalnet_tiny_lrf_in1k	.875
99	alexnet_linf_8_robust	.873
100	efficientnet_b0	.874
101	antialias-resnet152	.873
102	resnet_50_v2	.872
103	ReAlnet02	.872
104	ReAlnet02_cornet	.871
105	yudixie_resnet18_distance_translation_0_240719	.871
106	ReAlnet04	.871
107	ReAlnet03	.870
108	ReAlnet03_cornet	.867
109	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
110	ReAlnet04_cornet	.868
111	alexnet	.866
112	alexnet-baseline	.864
113	alexnet	.865
114	alexnet	.865
115	alexnet	.864
116	alexnet	.865
117	alexnet	.865
118	alexnet	.865
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	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
132	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
133	omnivore_swinS	.862
134	resnet50-simclr-vissl	.861
135	ReAlnet01	.861
136	squeezenet1_0	.859
137	alexnet_fov16	.858
138	ReAlnet01_cornet	.858
139	AdvProp_efficientnet-b4	.858
140	mobilenet_v2_0_5_224	.858
141	mobilenet_v1_0.5_128	.857
142	ReAlnet08	.857
143	ReAlnet08_cornet	.857
144	ReAlnet07_cornet	.857
145	ReAlnet07	.857
146	resnet_50_v1_spiking_l4a	.855
147	ReAlnet09	.856
148	resnet_50_v1	.856
149	resnet_50_v1_spiking_l4	.856
150	resnet50-sup	.856
151	yudixie_resnet50_imagenet1kpret_0_240908	.855
152	ReAlnet09_cornet	.855
153	resnet50_tutorial	.855
154	resnet_50_v1_spiking_l3	.854
155	imagenet_l2_3_0	.855
156	ReAlnet10_cornet	.854
157	resnet_50_v1_spiking	.854
158	ReAlnet10	.852
159	alexnet_fov4	.852
160	resnet50-moclr8deg	.850
161	resnet50-vicregl0p9	.850
162	convnext_base_imagenet_full_seed-0	.848
163	convnext_tiny_imagenet_full_seed-0	.847
164	mobilenet_v2_1_0_128	.847
165	ReAlnet06_cornet	.845
166	ReAlnet06	.845
167	mobilenet_v2_0.35_192	.843
168	inception_v4-tf	.843
169	inception_v2-tf	.843
170	CLIP-RN50	.840
171	vonegrcnn_62e_nobn	.840
172	resnet50_random_linf8_perturb	.838
173	resnet-50-robust	.838
174	resnet50_robust_l2_eps1	.837
175	0.5x_resnet-18	.836
176	mobilenet_v1_0.5_160	.835
177	resnet50-vicregl0p75	.835
178	BiT-M-R101x1	.835
179	convnext_small_imagenet_100_seed-0	.835
180	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
181	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
182	resnet_SIN_IN_FT_IN	.832
183	mobilenet_v2_1_3_224	.832
184	mobilenet_v2_0.75_192-tf	.830
185	mobilenet_v2_1_4_224	.831
186	imagenet_l2_10_0	.831
187	resnet-18-LC_w_sh_10_iter_m	.830
188	Res2Net50_26w_4s	.830
189	CORnet-Z	.828
190	resnet101_imagenet_full	.826
191	omnivore_swinB	.825
192	resnet50_l2_3_robust	.825
193	resnet50	.822
194	antialiased-r50	.820
195	resnet18-supervised	.819
196	vgg-19-keras	.818
197	convnext_large_imagenet_full_seed-0	.818
198	alexnet_fov12	.818
199	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
200	resnet50_linf_8_robust	.817
201	AlexNet_SIN_fov12	.816
202	mobilenet_v2_0.5_96	.814
203	0.5x_resnet-18_LC_w_sh_1_iter	.813
204	resnet50-SIN_IN	.814
205	vit_base_patch16_clip_224:openai_ft_in1k	.813
206	resnet50-SIN_IN_IN	.813
207	resnet50_robust_l2_eps3	.812
208	mobilenet_v2_1.4_224-tf	.811
209	RN50	.812
210	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
211	resnet50_random_l2_perturb	.810
212	cornet_s	.808
213	CORnet-S	.806
214	vonealexnet_gaussian_noise_std4_fixed	.806
215	BiT-S-R152x2	.803
216	ReAlnet07_ALL	.802
217	resnet50_linf_4_robust	.800
218	ReAlnet08_ALL	.800
219	densenet-169	.799
220	ReAlnet04_ALL	.798
221	convnext_small_imagenet_full_seed-0	.797
222	resnet-50x2_untrained	.797
223	AdvProp_efficientnet-b0	.796
224	ReAlnet06_ALL	.793
225	resnet50-SIN	.792
226	ReAlnet03_ALL	.792
227	ReAlnet02_ALL	.791
228	resnet-50_untrained	.791
229	ReAlnet10_ALL	.791
230	texture_shape_resnet50_trained_on_SIN	.791
231	resnet-101_v2-tf	.790
232	ReAlnet05_ALL	.789
233	ReAlnet01_ALL	.788
234	ReAlnet01_cornet_fov12	.787
235	resnet-18_untrained	.788
236	CLIP_resnet50_float32	.788
237	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
238	r3m_resnet34_nocrop	.787
239	CLIP_resnet50	.785
240	resnet-50_v2-tf	.786
241	compact_vgg19_IT	.786
242	ReAlnet09_ALL	.785
243	resnet34_imagenet_full	.777
244	yudixie_resnet18_imagenet1kpret_0_240719	.777
245	SWSL_resnet50	.773
246	resnet50-vicreg	.773
247	resnet-101_v1-tf	.771
248	mobilenet_v2_0.35_96	.769
249	resnet-18_test_m	.766
250	densenet-121	.765
251	convnext_tiny:in12k_ft_in1k	.763
252	resnet152_imagenet_full	.761
253	resnet50_imagenet_full	.760
254	alexnet_training_seed_01_fov16	.760
255	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
256	voneresnet-50-non_stochastic	.759
257	resnet18_imagenet_full	.758
258	deit_small_imagenet_full_seed-0	.757
259	pnasnet_large-tf	.757
260	efficientnet_b0_imagenet_full	.756
261	mobilenet_v2_1.0_192-tf	.754
262	mobilenet_v2_1_0_192	.754
263	resnet34_ecoset_full	.754
264	resnet101_ecoset_full	.749
265	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
266	resnet-152_v1-tf	.745
267	mobilenet_v1_0.5_224	.744
268	alexnet_training_seed_01_fov12	.744
269	alexnet_training_seed_07	.743
270	yudixie_resnet18_distance_reg_0_240719	.742
271	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
272	mobilenet_v1_0.75_192	.739
273	shufflenet_v2_x1_0	.740
274	cvt_cvt-13-384-in1k_4_LucyV4	.739
275	mobilenet_v2_0_75_224	.738
276	BiT-S-R101x1	.736
277	BiT-M-R101x3	.732
278	AlexNet_SIN_fov16	.732
279	alexnet_training_seed_02	.730
280	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
281	FrankRobWobv0	.727
282	voneresnet-50-robust	.727
283	vggface	.727
284	mobilenet_v2_0.5_192-tf	.726
285	yudixie_resnet18_rotation_reg_0_240719	.725
286	resnet50-cifar	.722
287	BiT-M-R152x4	.721
288	antialiased-rnext101_32x8d	.717
289	BiT-S-R152x4	.716
290	resnet50-VITO-8deg-cc	.715
291	voneresnet-50	.714
292	resnet152_ecoset_full	.709
293	mobilenet_v1_0.25_224	.709
294	VOneCORnet-S	.708
295	yolos_tiny	.707
296	densenet-121-keras	.703
297	resnet50_FractalDB	.703
298	mobilenet_v1_0.75_224	.701
299	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
300	alexnet_training_seed_04	.700
301	mobilenet_v2_0.75_128	.700
302	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
303	mobilenet_v1_0.25_160	.696
304	SWSL_resnext101_32x8d	.695
305	v1-pyr-nodown	.695
306	resnet-18-LC_w_sh_100_iter_m	.694
307	CLIP_ViT-B_32	.693
308	alexnet_training_seed_01	.693
309	mobilenet_v1_1.0_224	.691
310	resnet50_ecoset_full	.691
311	omnivore_swinT	.690
312	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
313	densenet-169-keras	.687
314	my-model	.687
315	konkle_alexnetgn_ipcl_ref01_primary_model	.686
316	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
317	mobilenet_v2_1-4_224_pytorch	.684
318	alexnet_training_seed_09	.682
319	nasnet_mobile-tf	.681
320	mobilenet_v2_0.35_224	.680
321	mobilenet_v2_0_75_160	.680
322	effnetv2m_custom384	.676
323	resnet50-barlow	.675
324	mobilenet_v2_1.0_128-tf	.674
325	vision_transformer_vit_large_patch16_224	.670
326	mobilenet_v1_0.25_128	.668
327	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
328	mobilenet_v2_1_0_160	.667
329	cv_18_dagger_408_pretrained	.665
330	deit_small_imagenet_100_seed-0	.662
331	mobilenet_v1_0.5_192	.660
332	resnet50	.658
333	resnet50_moco_v2	.658
334	resnet50_simclr	.657
335	custom_model_cv_18_dagger_408	.656
336	artResNet18_1	.655
337	nasnet_mobile	.654
338	mobilenet_v2_1_0_224	.649
339	mobilenet_v1_1.0_192	.648
340	yudixie_resnet50_random_0_240908	.646
341	effnetb1_272x240	.645
342	resnet-18-LC_conv_init_m	.644
343	alexnet_training_seed_10	.645
344	BiT-M-R152x2	.641
345	AdvProp_efficientnet-b2	.627
346	mobilenet_v2_0.75_160-tf	.624
347	AT_efficientnet-b2	.625
348	vonegrcnn_52e_full	.623
349	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
350	vit_large_patch14_clip_224:openai_ft_in1k	.621
351	mobilenet_v2_0_5_192	.619
352	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
353	resnet-152_v2_pytorch	.615
354	convnext_small_imagenet_10_seed-0	.615
355	BiT-M-R50x1	.613
356	yudixie_resnet18_random_0_240719	.610
357	CORnetZ_CIFAR10_bs32_20_04	.605
358	vonegrcnn_47e	.604
359	inception_v1-tf	.600
360	mobilenet_v2_0.5_224-tf	.597
361	mobilenet_v1_1.0_160	.597
362	alexnet_training_seed_03	.596
363	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
364	deit_base_imagenet_full_seed-0	.589
365	r3m_resnet34	.590
366	vonegrcnn_47e	.581
367	deit_large_imagenet_full_seed-0	.577
368	mobilenet_v1_0.75_128	.570
369	mobilenet_v1_0.75_160	.565
370	mobilenet_v1_0.25_192	.560
371	mobilenet_v2_0.75_96	.557
372	inception_resnet_v2	.554
373	alexnet_training_seed_01_fov4	.554
374	efficientnet_b2_imagenet_full	.550
375	r3m_resnet50_nocrop	.550
376	hmax	.535
377	r3m_resnet50	.519
378	r3m_resnet18	.516
379	resnet50_pretrained_with_retinal_waves	.515
380	my-model	.493
381	mobilenet_v2_0.75_224-tf	.490
382	alexnet_training_seed_08	.462
383	convnext_small_imagenet_1_seed-0	.459
384	CORnetZ_CIFAR10	.447
385	ViT-B/32	.385
386	mobilenet_v2_0.35_128	.375
387	deit_small_imagenet_10_seed-0	.375
388	resnet50_imagenet_1_seed-0	.355
389	alexnet_training_seed_05	.271
390	mobilenet_v2_0.5_160	.271
391	alexnet_training_seed_06	.215
392	resnet-18-LC_untrained	.170
393	resnet50-meshes-lt-100-original-pretrained	.169
394	resnet50-meshes-lt-100-original-scratch	.081
395	mobilenet_v2_0.5_128	.028
396	unet_entire
397	mobilenet_v2_0.35_160
398	fitvid_trained_on_physion
399	openclip
400	resnext101_32x32d_wsl
401	resnext101_32x48d_wsl
402	resnet50_ImageNet
403	resnet_101_v1
404	resnet_152_v2
405	regnet_y_400mf
406	tv_efficientnet-b1
407	alexnet_ks_torevert
408	yudixie_resnet50_imagenet1kpret_0_240312
409	resnet_152_v1
410	ViT_L_32_imagenet1k
411	resnext101_32x16d_wsl
412	densenet_201_pytorch
413	inception_v3_pytorch
414	pnasnet_large_pytorch
415	mobilevit_small
416	inception_v4
417	nasnet_large
418	deit_small_imagenet_1_seed-0
419	pnasnet_large
420	vonegrcnn_62e_nobn
421	resnet_101_v2
422	vonegrcnn_52e_full

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance