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	yudixie_resnet18_category_class_0_240719	.955
14	mobilenet_v2_1.0_224-tf	.951
15	resnet-152_v2-tf	.949
16	yudixie_resnet18_translation_rotation_0_240719	.946
17	efficientnet_b1_imagenet_full	.947
18	resnet-18-LC_d_w_sh_1x1_conv_init_m	.946
19	texture_shape_alexnet_trained_on_SIN	.944
20	convnext_large:fb_in22k_ft_in1k	.942
21	vgg_16	.942
22	resnet50_imagenet_100_seed-0	.942
23	briaai_rmbg_1_4	.941
24	inception_v1	.938
25	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.936
26	yudixie_resnet50_translation_rotation_0_240908	.935
27	efficientnet-b7	.935
28	alexnet_random_l2_3_perturb	.934
29	AdvProp_efficientnet-b6	.930
30	vgg_19	.929
31	alexnet	.926
32	yudixie_resnet50_distance_rotation_0_240908	.925
33	yudixie_resnet50_distance_reg_0_240908	.924
34	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
35	0.5x_resnet-18_LC	.923
36	resnet-18-LC_m	.922
37	alexnet_random_linf8_perturb	.921
38	grcnn_robust_v1	.921
39	resnet-18-LC_w_sh_1_iter_m	.919
40	resnet18_ecoset_full	.918
41	cvt_cvt-21-384-in1k_4_LucyV4	.917
42	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
43	AdvProp_efficientnet-b8	.915
44	vgg-16-keras	.916
45	yudixie_resnet50_distance_translation_0_240908	.912
46	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
47	inception_v3-tf	.912
48	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
49	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
50	resnet-50_v1-tf	.909
51	grcnn	.908
52	mobilenet_v2_1.0_96	.906
53	blt_vs	.907
54	alexnet_robust_correct	.905
55	resnext101_32x8d_wsl	.903
56	grcnn_109	.902
57	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
58	alexnet_early_checkpoint	.899
59	BiT-S-R50x3	.897
60	grcnn_v2_text_noise	.898
61	BiT-S-R101x3	.895
62	nasnet_large-tf	.896
63	resnet18_imagenet21kP	.896
64	densenet-201-keras	.893
65	mobilenet_v2_1.3_224-tf	.893
66	mobilenet_v2_1.0_160-tf	.892
67	yudixie_resnet50_translation_reg_0_240908	.892
68	resnet50_byol	.892
69	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
70	0.5x_resnet-18_LC_w_sh_10_iter	.890
71	yudixie_resnet50_object_class_0_240908	.889
72	alexnet_reduced_aliasing_early_checkpoint	.889
73	mobilenet_v2_0_75_192	.887
74	resnet50_imagenet_10_seed-0	.884
75	convnext_tiny_sup	.885
76	AdvProp_efficientnet-b7	.884
77	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
78	alexnet_l2_3_robust	.882
79	yudixie_resnet18_distance_rotation_0_240719	.882
80	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
81	resnet101	.878
82	yudixie_resnet18_object_class_0_240719	.878
83	squeezenet1_1	.877
84	densenet-201	.876
85	mobilenet_v1_1.0_128	.875
86	focalnet_tiny_lrf_in1k	.875
87	alexnet_linf_8_robust	.873
88	efficientnet_b0	.874
89	antialias-resnet152	.873
90	resnet_50_v2	.872
91	ReAlnet02	.872
92	ReAlnet02_cornet	.871
93	yudixie_resnet18_distance_translation_0_240719	.871
94	ReAlnet04	.871
95	ReAlnet03	.870
96	ReAlnet03_cornet	.867
97	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
98	ReAlnet04_cornet	.868
99	alexnet	.866
100	alexnet-baseline	.864
101	alexnet	.865
102	alexnet	.865
103	alexnet	.864
104	alexnet	.865
105	alexnet	.865
106	alexnet	.865
107	yudixie_resnet18_distance_translation_rotation_0_240719	.864
108	0.5x_resnet-18_LC_w_sh_100_iter	.865
109	inception_v3	.863
110	AlexNet_SIN	.863
111	resnet50-vitoimagevidnet8	.863
112	ReAlnet05	.863
113	ReAlnet05_cornet	.862
114	convnext_xlarge:fb_in22k_ft_in1k	.862
115	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
116	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
117	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
118	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
119	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
120	omnivore_swinS	.862
121	resnet50-simclr-vissl	.861
122	ReAlnet01	.861
123	ReAlnet_incorrect	.860
124	squeezenet1_0	.859
125	ReAlnet01_cornet	.858
126	AdvProp_efficientnet-b4	.858
127	mobilenet_v2_0_5_224	.858
128	mobilenet_v1_0.5_128	.857
129	ReAlnet08	.857
130	ReAlnet08_cornet	.857
131	ReAlnet07_cornet	.857
132	ReAlnet07	.857
133	ReAlnet09	.856
134	resnet_50_v1	.856
135	resnet50-sup	.856
136	yudixie_resnet50_imagenet1kpret_0_240908	.855
137	ReAlnet09_cornet	.855
138	resnet50_tutorial	.855
139	imagenet_l2_3_0	.855
140	ReAlnet10_cornet	.854
141	ReAlnet10	.852
142	resnet50-moclr8deg	.850
143	resnet50-vicregl0p9	.850
144	convnext_base_imagenet_full_seed-0	.848
145	convnext_tiny_imagenet_full_seed-0	.847
146	mobilenet_v2_1_0_128	.847
147	ReAlnet06_cornet	.845
148	ReAlnet06	.845
149	mobilenet_v2_0.35_192	.843
150	inception_v4-tf	.843
151	inception_v2-tf	.843
152	CLIP-RN50	.840
153	vonegrcnn_62e_nobn	.840
154	resnet50_random_linf8_perturb	.838
155	resnet-50-robust	.838
156	resnet50_robust_l2_eps1	.837
157	0.5x_resnet-18	.836
158	mobilenet_v1_0.5_160	.835
159	resnet50-vicregl0p75	.835
160	BiT-M-R101x1	.835
161	convnext_small_imagenet_100_seed-0	.835
162	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
163	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
164	resnet_SIN_IN_FT_IN	.832
165	mobilenet_v2_1_3_224	.832
166	mobilenet_v2_0.75_192-tf	.830
167	mobilenet_v2_1_4_224	.831
168	imagenet_l2_10_0	.831
169	resnet-18-LC_w_sh_10_iter_m	.830
170	Res2Net50_26w_4s	.830
171	CORnet-Z	.828
172	resnet101_imagenet_full	.826
173	omnivore_swinB	.825
174	resnet50_l2_3_robust	.825
175	resnet50	.822
176	antialiased-r50	.820
177	resnet18-supervised	.819
178	vgg-19-keras	.818
179	convnext_large_imagenet_full_seed-0	.818
180	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
181	resnet50_linf_8_robust	.817
182	mobilenet_v2_0.5_96	.814
183	0.5x_resnet-18_LC_w_sh_1_iter	.813
184	resnet50-SIN_IN	.814
185	vit_base_patch16_clip_224:openai_ft_in1k	.813
186	resnet50-SIN_IN_IN	.813
187	resnet50_robust_l2_eps3	.812
188	mobilenet_v2_1.4_224-tf	.811
189	RN50	.812
190	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
191	resnet50_random_l2_perturb	.810
192	cornet_s	.808
193	CORnet-S	.806
194	vonealexnet_gaussian_noise_std4_fixed	.806
195	BiT-S-R152x2	.803
196	resnet50_linf_4_robust	.800
197	densenet-169	.799
198	convnext_small_imagenet_full_seed-0	.797
199	resnet-50x2_untrained	.797
200	AdvProp_efficientnet-b0	.796
201	resnet50-SIN	.792
202	resnet-50_untrained	.791
203	texture_shape_resnet50_trained_on_SIN	.791
204	resnet-101_v2-tf	.790
205	resnet-18_untrained	.788
206	CLIP_resnet50_float32	.788
207	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
208	r3m_resnet34_nocrop	.787
209	CLIP_resnet50	.785
210	resnet-50_v2-tf	.786
211	resnet34_imagenet_full	.777
212	yudixie_resnet18_imagenet1kpret_0_240719	.777
213	SWSL_resnet50	.773
214	resnet50-vicreg	.773
215	resnet-101_v1-tf	.771
216	mobilenet_v2_0.35_96	.769
217	resnet-18_test_m	.766
218	densenet-121	.765
219	convnext_tiny:in12k_ft_in1k	.763
220	resnet152_imagenet_full	.761
221	resnet50_imagenet_full	.760
222	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
223	voneresnet-50-non_stochastic	.759
224	resnet18_imagenet_full	.758
225	deit_small_imagenet_full_seed-0	.757
226	pnasnet_large-tf	.757
227	efficientnet_b0_imagenet_full	.756
228	mobilenet_v2_1.0_192-tf	.754
229	mobilenet_v2_1_0_192	.754
230	resnet34_ecoset_full	.754
231	resnet101_ecoset_full	.749
232	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
233	resnet-152_v1-tf	.745
234	mobilenet_v1_0.5_224	.744
235	alexnet_training_seed_07	.743
236	yudixie_resnet18_distance_reg_0_240719	.742
237	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
238	mobilenet_v1_0.75_192	.739
239	shufflenet_v2_x1_0	.740
240	cvt_cvt-13-384-in1k_4_LucyV4	.739
241	mobilenet_v2_0_75_224	.738
242	BiT-S-R101x1	.736
243	BiT-M-R101x3	.732
244	alexnet_training_seed_02	.730
245	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
246	FrankRobWobv0	.727
247	voneresnet-50-robust	.727
248	vggface	.727
249	mobilenet_v2_0.5_192-tf	.726
250	yudixie_resnet18_rotation_reg_0_240719	.725
251	resnet50-cifar	.722
252	BiT-M-R152x4	.721
253	antialiased-rnext101_32x8d	.717
254	BiT-S-R152x4	.716
255	resnet50-VITO-8deg-cc	.715
256	voneresnet-50	.714
257	resnet152_ecoset_full	.709
258	mobilenet_v1_0.25_224	.709
259	VOneCORnet-S	.708
260	yolos_tiny	.707
261	densenet-121-keras	.703
262	resnet50_FractalDB	.703
263	mobilenet_v1_0.75_224	.701
264	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
265	alexnet_training_seed_04	.700
266	mobilenet_v2_0.75_128	.700
267	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
268	mobilenet_v1_0.25_160	.696
269	SWSL_resnext101_32x8d	.695
270	v1-pyr-nodown	.695
271	resnet-18-LC_w_sh_100_iter_m	.694
272	CLIP_ViT-B_32	.693
273	alexnet_training_seed_01	.693
274	mobilenet_v1_1.0_224	.691
275	resnet50_ecoset_full	.691
276	omnivore_swinT	.690
277	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
278	densenet-169-keras	.687
279	my-model	.687
280	konkle_alexnetgn_ipcl_ref01_primary_model	.686
281	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
282	mobilenet_v2_1-4_224_pytorch	.684
283	alexnet_training_seed_09	.682
284	nasnet_mobile-tf	.681
285	mobilenet_v2_0.35_224	.680
286	mobilenet_v2_0_75_160	.680
287	effnetv2m_custom384	.676
288	resnet50-barlow	.675
289	mobilenet_v2_1.0_128-tf	.674
290	vision_transformer_vit_large_patch16_224	.670
291	mobilenet_v1_0.25_128	.668
292	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
293	mobilenet_v2_1_0_160	.667
294	cv_18_dagger_408_pretrained	.665
295	deit_small_imagenet_100_seed-0	.662
296	mobilenet_v1_0.5_192	.660
297	resnet50	.658
298	resnet50_moco_v2	.658
299	resnet50_simclr	.657
300	custom_model_cv_18_dagger_408	.656
301	artResNet18_1	.655
302	nasnet_mobile	.654
303	mobilenet_v2_1_0_224	.649
304	mobilenet_v1_1.0_192	.648
305	yudixie_resnet50_random_0_240908	.646
306	effnetb1_272x240	.645
307	resnet-18-LC_conv_init_m	.644
308	alexnet_training_seed_10	.645
309	BiT-M-R152x2	.641
310	AdvProp_efficientnet-b2	.627
311	mobilenet_v2_0.75_160-tf	.624
312	AT_efficientnet-b2	.625
313	vonegrcnn_52e_full	.623
314	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
315	vit_large_patch14_clip_224:openai_ft_in1k	.621
316	mobilenet_v2_0_5_192	.619
317	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
318	resnet-152_v2_pytorch	.615
319	convnext_small_imagenet_10_seed-0	.615
320	BiT-M-R50x1	.613
321	yudixie_resnet18_random_0_240719	.610
322	CORnetZ_CIFAR10_bs32_20_04	.605
323	vonegrcnn_47e	.604
324	inception_v1-tf	.600
325	mobilenet_v2_0.5_224-tf	.597
326	mobilenet_v1_1.0_160	.597
327	alexnet_training_seed_03	.596
328	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
329	deit_base_imagenet_full_seed-0	.589
330	r3m_resnet34	.590
331	vonegrcnn_47e	.581
332	deit_large_imagenet_full_seed-0	.577
333	mobilenet_v1_0.75_128	.570
334	mobilenet_v1_0.75_160	.565
335	mobilenet_v1_0.25_192	.560
336	mobilenet_v2_0.75_96	.557
337	inception_resnet_v2	.554
338	efficientnet_b2_imagenet_full	.550
339	r3m_resnet50_nocrop	.550
340	hmax	.535
341	r3m_resnet50	.519
342	r3m_resnet18	.516
343	resnet50_pretrained_with_retinal_waves	.515
344	my-model	.493
345	mobilenet_v2_0.75_224-tf	.490
346	alexnet_training_seed_08	.462
347	convnext_small_imagenet_1_seed-0	.459
348	CORnetZ_CIFAR10	.447
349	ViT-B/32	.385
350	mobilenet_v2_0.35_128	.375
351	deit_small_imagenet_10_seed-0	.375
352	resnet50_imagenet_1_seed-0	.355
353	alexnet_training_seed_05	.271
354	mobilenet_v2_0.5_160	.271
355	alexnet_training_seed_06	.215
356	resnet-18-LC_untrained	.170
357	resnet50-meshes-lt-100-original-pretrained	.169
358	resnet50-meshes-lt-100-original-scratch	.081
359	mobilenet_v2_0.5_128	.028
360	resnext101_32x32d_wsl	X
361	densenet_201_pytorch	X
362	inception_v3_pytorch	X
363	pnasnet_large	X
364	vonegrcnn_52e_full	X
365	inception_v4	X
366	pnasnet_large_pytorch	X
367	alexnet_ks_torevert	X
368	mobilevit_small	X
369	resnet_101_v1	X
370	resnet_152_v2	X
371	mobilenet_v2_0.35_160	X
372	regnet_y_400mf	X
373	openclip	X
374	tv_efficientnet-b1	X
375	fitvid_trained_on_physion	X
376	unet_entire	X
377	deit_small_imagenet_1_seed-0	X
378	resnet50_ImageNet	X
379	yudixie_resnet50_imagenet1kpret_0_240312	X
380	nasnet_large	X
381	resnet_152_v1	X
382	vonegrcnn_62e_nobn	X
383	ViT_L_32_imagenet1k	X
384	resnet_101_v2	X
385	resnext101_32x16d_wsl	X
386	resnext101_32x48d_wsl	X

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance