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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	BiT-M-R50x3	.961
10	xception	.962
11	yudixie_resnet50_distance_translation_rotation_0_240908	.958
12	yudixie_resnet50_category_class_0_240908	.958
13	compact_vgg19_V4	.958
14	compact_cornets_IT	.957
15	yudixie_resnet18_category_class_0_240719	.955
16	mobilenet_v2_1.0_224-tf	.951
17	resnet-152_v2-tf	.949
18	compact_resnet50_V4	.949
19	yudixie_resnet18_translation_rotation_0_240719	.946
20	efficientnet_b1_imagenet_full	.947
21	resnet-18-LC_d_w_sh_1x1_conv_init_m	.946
22	texture_shape_alexnet_trained_on_SIN	.944
23	convnext_large:fb_in22k_ft_in1k	.942
24	vgg_16	.942
25	resnet50_imagenet_100_seed-0	.942
26	briaai_rmbg_1_4	.941
27	inception_v1	.938
28	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.936
29	yudixie_resnet50_translation_rotation_0_240908	.935
30	efficientnet-b7	.935
31	alexnet_random_l2_3_perturb	.934
32	AdvProp_efficientnet-b6	.930
33	vgg_19	.929
34	alexnet	.926
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	alexnet_robust_correct	.905
60	resnext101_32x8d_wsl	.903
61	grcnn_109	.902
62	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
63	BiT-S-R50x3	.897
64	alexnet_early_checkpoint	.899
65	grcnn_v2_text_noise	.898
66	BiT-S-R101x3	.895
67	nasnet_large-tf	.896
68	compact_resnet50_IT	.895
69	resnet18_imagenet21kP	.896
70	densenet-201-keras	.893
71	mobilenet_v2_1.3_224-tf	.893
72	mobilenet_v2_1.0_160-tf	.892
73	yudixie_resnet50_translation_reg_0_240908	.892
74	resnet50_byol	.892
75	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
76	0.5x_resnet-18_LC_w_sh_10_iter	.890
77	yudixie_resnet50_object_class_0_240908	.889
78	alexnet_reduced_aliasing_early_checkpoint	.889
79	resnet50_ewconplus_wzc	.889
80	mobilenet_v2_0_75_192	.887
81	resnet50_imagenet_10_seed-0	.884
82	convnext_tiny_sup	.885
83	AdvProp_efficientnet-b7	.884
84	compact_resnet50_robust_V4	.883
85	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
86	alexnet_l2_3_robust	.882
87	yudixie_resnet18_distance_rotation_0_240719	.882
88	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
89	compact_resnet50_robust_IT	.879
90	resnet101	.878
91	yudixie_resnet18_object_class_0_240719	.878
92	squeezenet1_1	.877
93	densenet-201	.876
94	mobilenet_v1_1.0_128	.875
95	focalnet_tiny_lrf_in1k	.875
96	alexnet_linf_8_robust	.873
97	efficientnet_b0	.874
98	antialias-resnet152	.873
99	resnet_50_v2	.872
100	ReAlnet02	.872
101	ReAlnet02_cornet	.871
102	yudixie_resnet18_distance_translation_0_240719	.871
103	ReAlnet04	.871
104	ReAlnet03	.870
105	ReAlnet03_cornet	.867
106	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
107	ReAlnet04_cornet	.868
108	alexnet	.866
109	alexnet-baseline	.864
110	alexnet	.865
111	alexnet	.865
112	alexnet	.864
113	alexnet	.865
114	alexnet	.865
115	alexnet	.865
116	yudixie_resnet18_distance_translation_rotation_0_240719	.864
117	0.5x_resnet-18_LC_w_sh_100_iter	.865
118	inception_v3	.863
119	AlexNet_SIN	.863
120	resnet50-vitoimagevidnet8	.863
121	ReAlnet05	.863
122	ReAlnet05_cornet	.862
123	convnext_xlarge:fb_in22k_ft_in1k	.862
124	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
125	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
126	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
127	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
128	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
129	omnivore_swinS	.862
130	resnet50-simclr-vissl	.861
131	ReAlnet01	.861
132	squeezenet1_0	.859
133	ReAlnet01_cornet	.858
134	AdvProp_efficientnet-b4	.858
135	mobilenet_v2_0_5_224	.858
136	mobilenet_v1_0.5_128	.857
137	ReAlnet08	.857
138	ReAlnet08_cornet	.857
139	ReAlnet07_cornet	.857
140	ReAlnet07	.857
141	resnet_50_v1_spiking_l4a	.855
142	ReAlnet09	.856
143	resnet_50_v1	.856
144	resnet_50_v1_spiking_l4	.856
145	resnet50-sup	.856
146	yudixie_resnet50_imagenet1kpret_0_240908	.855
147	ReAlnet09_cornet	.855
148	resnet50_tutorial	.855
149	resnet_50_v1_spiking_l3	.854
150	imagenet_l2_3_0	.855
151	ReAlnet10_cornet	.854
152	resnet_50_v1_spiking	.854
153	ReAlnet10	.852
154	resnet50-moclr8deg	.850
155	resnet50-vicregl0p9	.850
156	convnext_base_imagenet_full_seed-0	.848
157	convnext_tiny_imagenet_full_seed-0	.847
158	mobilenet_v2_1_0_128	.847
159	ReAlnet06_cornet	.845
160	ReAlnet06	.845
161	mobilenet_v2_0.35_192	.843
162	inception_v4-tf	.843
163	inception_v2-tf	.843
164	CLIP-RN50	.840
165	vonegrcnn_62e_nobn	.840
166	resnet50_random_linf8_perturb	.838
167	resnet-50-robust	.838
168	resnet50_robust_l2_eps1	.837
169	0.5x_resnet-18	.836
170	mobilenet_v1_0.5_160	.835
171	resnet50-vicregl0p75	.835
172	BiT-M-R101x1	.835
173	convnext_small_imagenet_100_seed-0	.835
174	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
175	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
176	resnet_SIN_IN_FT_IN	.832
177	mobilenet_v2_1_3_224	.832
178	mobilenet_v2_0.75_192-tf	.830
179	mobilenet_v2_1_4_224	.831
180	imagenet_l2_10_0	.831
181	resnet-18-LC_w_sh_10_iter_m	.830
182	Res2Net50_26w_4s	.830
183	CORnet-Z	.828
184	resnet101_imagenet_full	.826
185	omnivore_swinB	.825
186	resnet50_l2_3_robust	.825
187	resnet50	.822
188	antialiased-r50	.820
189	resnet18-supervised	.819
190	vgg-19-keras	.818
191	convnext_large_imagenet_full_seed-0	.818
192	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
193	resnet50_linf_8_robust	.817
194	mobilenet_v2_0.5_96	.814
195	0.5x_resnet-18_LC_w_sh_1_iter	.813
196	resnet50-SIN_IN	.814
197	vit_base_patch16_clip_224:openai_ft_in1k	.813
198	resnet50-SIN_IN_IN	.813
199	resnet50_robust_l2_eps3	.812
200	mobilenet_v2_1.4_224-tf	.811
201	RN50	.812
202	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
203	resnet50_random_l2_perturb	.810
204	cornet_s	.808
205	CORnet-S	.806
206	vonealexnet_gaussian_noise_std4_fixed	.806
207	BiT-S-R152x2	.803
208	ReAlnet07_ALL	.802
209	resnet50_linf_4_robust	.800
210	ReAlnet08_ALL	.800
211	densenet-169	.799
212	ReAlnet04_ALL	.798
213	convnext_small_imagenet_full_seed-0	.797
214	resnet-50x2_untrained	.797
215	AdvProp_efficientnet-b0	.796
216	ReAlnet06_ALL	.793
217	resnet50-SIN	.792
218	ReAlnet03_ALL	.792
219	ReAlnet02_ALL	.791
220	resnet-50_untrained	.791
221	ReAlnet10_ALL	.791
222	texture_shape_resnet50_trained_on_SIN	.791
223	resnet-101_v2-tf	.790
224	ReAlnet05_ALL	.789
225	ReAlnet01_ALL	.788
226	resnet-18_untrained	.788
227	CLIP_resnet50_float32	.788
228	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
229	r3m_resnet34_nocrop	.787
230	CLIP_resnet50	.785
231	resnet-50_v2-tf	.786
232	compact_vgg19_IT	.786
233	ReAlnet09_ALL	.785
234	resnet34_imagenet_full	.777
235	yudixie_resnet18_imagenet1kpret_0_240719	.777
236	SWSL_resnet50	.773
237	resnet50-vicreg	.773
238	resnet-101_v1-tf	.771
239	mobilenet_v2_0.35_96	.769
240	resnet-18_test_m	.766
241	densenet-121	.765
242	convnext_tiny:in12k_ft_in1k	.763
243	resnet152_imagenet_full	.761
244	resnet50_imagenet_full	.760
245	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
246	voneresnet-50-non_stochastic	.759
247	resnet18_imagenet_full	.758
248	deit_small_imagenet_full_seed-0	.757
249	pnasnet_large-tf	.757
250	efficientnet_b0_imagenet_full	.756
251	mobilenet_v2_1.0_192-tf	.754
252	mobilenet_v2_1_0_192	.754
253	resnet34_ecoset_full	.754
254	resnet101_ecoset_full	.749
255	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
256	resnet-152_v1-tf	.745
257	mobilenet_v1_0.5_224	.744
258	alexnet_training_seed_07	.743
259	yudixie_resnet18_distance_reg_0_240719	.742
260	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
261	mobilenet_v1_0.75_192	.739
262	shufflenet_v2_x1_0	.740
263	cvt_cvt-13-384-in1k_4_LucyV4	.739
264	mobilenet_v2_0_75_224	.738
265	BiT-S-R101x1	.736
266	BiT-M-R101x3	.732
267	alexnet_training_seed_02	.730
268	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
269	FrankRobWobv0	.727
270	voneresnet-50-robust	.727
271	vggface	.727
272	mobilenet_v2_0.5_192-tf	.726
273	yudixie_resnet18_rotation_reg_0_240719	.725
274	resnet50-cifar	.722
275	BiT-M-R152x4	.721
276	antialiased-rnext101_32x8d	.717
277	BiT-S-R152x4	.716
278	resnet50-VITO-8deg-cc	.715
279	voneresnet-50	.714
280	resnet152_ecoset_full	.709
281	mobilenet_v1_0.25_224	.709
282	VOneCORnet-S	.708
283	yolos_tiny	.707
284	densenet-121-keras	.703
285	resnet50_FractalDB	.703
286	mobilenet_v1_0.75_224	.701
287	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
288	alexnet_training_seed_04	.700
289	mobilenet_v2_0.75_128	.700
290	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
291	mobilenet_v1_0.25_160	.696
292	SWSL_resnext101_32x8d	.695
293	v1-pyr-nodown	.695
294	resnet-18-LC_w_sh_100_iter_m	.694
295	CLIP_ViT-B_32	.693
296	alexnet_training_seed_01	.693
297	mobilenet_v1_1.0_224	.691
298	resnet50_ecoset_full	.691
299	omnivore_swinT	.690
300	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
301	densenet-169-keras	.687
302	my-model	.687
303	konkle_alexnetgn_ipcl_ref01_primary_model	.686
304	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
305	mobilenet_v2_1-4_224_pytorch	.684
306	alexnet_training_seed_09	.682
307	nasnet_mobile-tf	.681
308	mobilenet_v2_0.35_224	.680
309	mobilenet_v2_0_75_160	.680
310	effnetv2m_custom384	.676
311	resnet50-barlow	.675
312	mobilenet_v2_1.0_128-tf	.674
313	vision_transformer_vit_large_patch16_224	.670
314	mobilenet_v1_0.25_128	.668
315	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
316	mobilenet_v2_1_0_160	.667
317	cv_18_dagger_408_pretrained	.665
318	deit_small_imagenet_100_seed-0	.662
319	mobilenet_v1_0.5_192	.660
320	resnet50	.658
321	resnet50_moco_v2	.658
322	resnet50_simclr	.657
323	custom_model_cv_18_dagger_408	.656
324	artResNet18_1	.655
325	nasnet_mobile	.654
326	mobilenet_v2_1_0_224	.649
327	mobilenet_v1_1.0_192	.648
328	yudixie_resnet50_random_0_240908	.646
329	effnetb1_272x240	.645
330	resnet-18-LC_conv_init_m	.644
331	alexnet_training_seed_10	.645
332	BiT-M-R152x2	.641
333	AdvProp_efficientnet-b2	.627
334	mobilenet_v2_0.75_160-tf	.624
335	AT_efficientnet-b2	.625
336	vonegrcnn_52e_full	.623
337	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
338	vit_large_patch14_clip_224:openai_ft_in1k	.621
339	mobilenet_v2_0_5_192	.619
340	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
341	resnet-152_v2_pytorch	.615
342	convnext_small_imagenet_10_seed-0	.615
343	BiT-M-R50x1	.613
344	yudixie_resnet18_random_0_240719	.610
345	CORnetZ_CIFAR10_bs32_20_04	.605
346	vonegrcnn_47e	.604
347	inception_v1-tf	.600
348	mobilenet_v2_0.5_224-tf	.597
349	mobilenet_v1_1.0_160	.597
350	alexnet_training_seed_03	.596
351	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
352	deit_base_imagenet_full_seed-0	.589
353	r3m_resnet34	.590
354	vonegrcnn_47e	.581
355	deit_large_imagenet_full_seed-0	.577
356	mobilenet_v1_0.75_128	.570
357	mobilenet_v1_0.75_160	.565
358	mobilenet_v1_0.25_192	.560
359	mobilenet_v2_0.75_96	.557
360	inception_resnet_v2	.554
361	efficientnet_b2_imagenet_full	.550
362	r3m_resnet50_nocrop	.550
363	hmax	.535
364	r3m_resnet50	.519
365	r3m_resnet18	.516
366	resnet50_pretrained_with_retinal_waves	.515
367	my-model	.493
368	mobilenet_v2_0.75_224-tf	.490
369	alexnet_training_seed_08	.462
370	convnext_small_imagenet_1_seed-0	.459
371	CORnetZ_CIFAR10	.447
372	ViT-B/32	.385
373	mobilenet_v2_0.35_128	.375
374	deit_small_imagenet_10_seed-0	.375
375	resnet50_imagenet_1_seed-0	.355
376	alexnet_training_seed_05	.271
377	mobilenet_v2_0.5_160	.271
378	alexnet_training_seed_06	.215
379	resnet-18-LC_untrained	.170
380	resnet50-meshes-lt-100-original-pretrained	.169
381	resnet50-meshes-lt-100-original-scratch	.081
382	mobilenet_v2_0.5_128	.028
383	unet_entire
384	mobilenet_v2_0.35_160
385	fitvid_trained_on_physion
386	openclip
387	resnext101_32x32d_wsl
388	resnext101_32x48d_wsl
389	resnet50_ImageNet
390	resnet_101_v1
391	resnet_152_v2
392	regnet_y_400mf
393	tv_efficientnet-b1
394	alexnet_ks_torevert
395	yudixie_resnet50_imagenet1kpret_0_240312
396	resnet_152_v1
397	ViT_L_32_imagenet1k
398	resnext101_32x16d_wsl
399	densenet_201_pytorch
400	inception_v3_pytorch
401	pnasnet_large_pytorch
402	mobilevit_small
403	inception_v4
404	nasnet_large
405	deit_small_imagenet_1_seed-0
406	pnasnet_large
407	vonegrcnn_62e_nobn
408	resnet_101_v2
409	vonegrcnn_52e_full

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance