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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	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	resnet50_primary_visual_cortex	.919
41	resnet18_ecoset_full	.918
42	cvt_cvt-21-384-in1k_4_LucyV4	.917
43	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
44	AdvProp_efficientnet-b8	.915
45	vgg-16-keras	.916
46	yudixie_resnet50_distance_translation_0_240908	.912
47	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
48	inception_v3-tf	.912
49	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
50	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
51	resnet-50_v1-tf	.909
52	grcnn	.908
53	mobilenet_v2_1.0_96	.906
54	blt_vs	.907
55	alexnet_robust_correct	.905
56	resnext101_32x8d_wsl	.903
57	grcnn_109	.902
58	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
59	BiT-S-R50x3	.897
60	alexnet_early_checkpoint	.899
61	grcnn_v2_text_noise	.898
62	BiT-S-R101x3	.895
63	nasnet_large-tf	.896
64	resnet18_imagenet21kP	.896
65	densenet-201-keras	.893
66	mobilenet_v2_1.3_224-tf	.893
67	mobilenet_v2_1.0_160-tf	.892
68	yudixie_resnet50_translation_reg_0_240908	.892
69	resnet50_byol	.892
70	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
71	0.5x_resnet-18_LC_w_sh_10_iter	.890
72	yudixie_resnet50_object_class_0_240908	.889
73	alexnet_reduced_aliasing_early_checkpoint	.889
74	mobilenet_v2_0_75_192	.887
75	resnet50_imagenet_10_seed-0	.884
76	convnext_tiny_sup	.885
77	AdvProp_efficientnet-b7	.884
78	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
79	alexnet_l2_3_robust	.882
80	yudixie_resnet18_distance_rotation_0_240719	.882
81	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
82	resnet101	.878
83	yudixie_resnet18_object_class_0_240719	.878
84	squeezenet1_1	.877
85	densenet-201	.876
86	mobilenet_v1_1.0_128	.875
87	focalnet_tiny_lrf_in1k	.875
88	alexnet_linf_8_robust	.873
89	efficientnet_b0	.874
90	antialias-resnet152	.873
91	resnet_50_v2	.872
92	ReAlnet02	.872
93	ReAlnet02_cornet	.871
94	yudixie_resnet18_distance_translation_0_240719	.871
95	ReAlnet04	.871
96	ReAlnet03	.870
97	ReAlnet03_cornet	.867
98	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
99	ReAlnet04_cornet	.868
100	alexnet	.866
101	alexnet-baseline	.864
102	alexnet	.865
103	alexnet	.865
104	alexnet	.864
105	alexnet	.865
106	alexnet	.865
107	alexnet	.865
108	yudixie_resnet18_distance_translation_rotation_0_240719	.864
109	0.5x_resnet-18_LC_w_sh_100_iter	.865
110	inception_v3	.863
111	AlexNet_SIN	.863
112	resnet50-vitoimagevidnet8	.863
113	ReAlnet05	.863
114	ReAlnet05_cornet	.862
115	convnext_xlarge:fb_in22k_ft_in1k	.862
116	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
117	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
118	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
119	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
120	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
121	omnivore_swinS	.862
122	resnet50-simclr-vissl	.861
123	ReAlnet01	.861
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	resnet_50_v1_spiking_l4a	.855
134	ReAlnet09	.856
135	resnet_50_v1	.856
136	resnet_50_v1_spiking_l4	.856
137	resnet50-sup	.856
138	yudixie_resnet50_imagenet1kpret_0_240908	.855
139	ReAlnet09_cornet	.855
140	resnet50_tutorial	.855
141	resnet_50_v1_spiking_l3	.854
142	imagenet_l2_3_0	.855
143	ReAlnet10_cornet	.854
144	resnet_50_v1_spiking	.854
145	ReAlnet10	.852
146	resnet50-moclr8deg	.850
147	resnet50-vicregl0p9	.850
148	convnext_base_imagenet_full_seed-0	.848
149	convnext_tiny_imagenet_full_seed-0	.847
150	mobilenet_v2_1_0_128	.847
151	ReAlnet06_cornet	.845
152	ReAlnet06	.845
153	mobilenet_v2_0.35_192	.843
154	inception_v4-tf	.843
155	inception_v2-tf	.843
156	CLIP-RN50	.840
157	vonegrcnn_62e_nobn	.840
158	resnet50_random_linf8_perturb	.838
159	resnet-50-robust	.838
160	resnet50_robust_l2_eps1	.837
161	0.5x_resnet-18	.836
162	mobilenet_v1_0.5_160	.835
163	resnet50-vicregl0p75	.835
164	BiT-M-R101x1	.835
165	convnext_small_imagenet_100_seed-0	.835
166	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
167	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
168	resnet_SIN_IN_FT_IN	.832
169	mobilenet_v2_1_3_224	.832
170	mobilenet_v2_0.75_192-tf	.830
171	mobilenet_v2_1_4_224	.831
172	imagenet_l2_10_0	.831
173	resnet-18-LC_w_sh_10_iter_m	.830
174	Res2Net50_26w_4s	.830
175	CORnet-Z	.828
176	resnet101_imagenet_full	.826
177	omnivore_swinB	.825
178	resnet50_l2_3_robust	.825
179	resnet50	.822
180	antialiased-r50	.820
181	resnet18-supervised	.819
182	vgg-19-keras	.818
183	convnext_large_imagenet_full_seed-0	.818
184	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
185	resnet50_linf_8_robust	.817
186	mobilenet_v2_0.5_96	.814
187	0.5x_resnet-18_LC_w_sh_1_iter	.813
188	resnet50-SIN_IN	.814
189	vit_base_patch16_clip_224:openai_ft_in1k	.813
190	resnet50-SIN_IN_IN	.813
191	resnet50_robust_l2_eps3	.812
192	mobilenet_v2_1.4_224-tf	.811
193	RN50	.812
194	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
195	resnet50_random_l2_perturb	.810
196	cornet_s	.808
197	CORnet-S	.806
198	vonealexnet_gaussian_noise_std4_fixed	.806
199	BiT-S-R152x2	.803
200	ReAlnet07_ALL	.802
201	resnet50_linf_4_robust	.800
202	ReAlnet08_ALL	.800
203	densenet-169	.799
204	ReAlnet04_ALL	.798
205	convnext_small_imagenet_full_seed-0	.797
206	resnet-50x2_untrained	.797
207	AdvProp_efficientnet-b0	.796
208	ReAlnet06_ALL	.793
209	resnet50-SIN	.792
210	ReAlnet03_ALL	.792
211	ReAlnet02_ALL	.791
212	resnet-50_untrained	.791
213	ReAlnet10_ALL	.791
214	texture_shape_resnet50_trained_on_SIN	.791
215	resnet-101_v2-tf	.790
216	ReAlnet05_ALL	.789
217	ReAlnet01_ALL	.788
218	resnet-18_untrained	.788
219	CLIP_resnet50_float32	.788
220	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
221	r3m_resnet34_nocrop	.787
222	CLIP_resnet50	.785
223	resnet-50_v2-tf	.786
224	ReAlnet09_ALL	.785
225	resnet34_imagenet_full	.777
226	yudixie_resnet18_imagenet1kpret_0_240719	.777
227	SWSL_resnet50	.773
228	resnet50-vicreg	.773
229	resnet-101_v1-tf	.771
230	mobilenet_v2_0.35_96	.769
231	resnet-18_test_m	.766
232	densenet-121	.765
233	convnext_tiny:in12k_ft_in1k	.763
234	resnet152_imagenet_full	.761
235	resnet50_imagenet_full	.760
236	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
237	voneresnet-50-non_stochastic	.759
238	resnet18_imagenet_full	.758
239	deit_small_imagenet_full_seed-0	.757
240	pnasnet_large-tf	.757
241	efficientnet_b0_imagenet_full	.756
242	mobilenet_v2_1.0_192-tf	.754
243	mobilenet_v2_1_0_192	.754
244	resnet34_ecoset_full	.754
245	resnet101_ecoset_full	.749
246	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
247	resnet-152_v1-tf	.745
248	mobilenet_v1_0.5_224	.744
249	alexnet_training_seed_07	.743
250	yudixie_resnet18_distance_reg_0_240719	.742
251	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
252	mobilenet_v1_0.75_192	.739
253	shufflenet_v2_x1_0	.740
254	cvt_cvt-13-384-in1k_4_LucyV4	.739
255	mobilenet_v2_0_75_224	.738
256	BiT-S-R101x1	.736
257	BiT-M-R101x3	.732
258	alexnet_training_seed_02	.730
259	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
260	FrankRobWobv0	.727
261	voneresnet-50-robust	.727
262	vggface	.727
263	mobilenet_v2_0.5_192-tf	.726
264	yudixie_resnet18_rotation_reg_0_240719	.725
265	resnet50-cifar	.722
266	BiT-M-R152x4	.721
267	antialiased-rnext101_32x8d	.717
268	BiT-S-R152x4	.716
269	resnet50-VITO-8deg-cc	.715
270	voneresnet-50	.714
271	resnet152_ecoset_full	.709
272	mobilenet_v1_0.25_224	.709
273	VOneCORnet-S	.708
274	yolos_tiny	.707
275	densenet-121-keras	.703
276	resnet50_FractalDB	.703
277	mobilenet_v1_0.75_224	.701
278	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
279	alexnet_training_seed_04	.700
280	mobilenet_v2_0.75_128	.700
281	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
282	mobilenet_v1_0.25_160	.696
283	SWSL_resnext101_32x8d	.695
284	v1-pyr-nodown	.695
285	resnet-18-LC_w_sh_100_iter_m	.694
286	CLIP_ViT-B_32	.693
287	alexnet_training_seed_01	.693
288	mobilenet_v1_1.0_224	.691
289	resnet50_ecoset_full	.691
290	omnivore_swinT	.690
291	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
292	densenet-169-keras	.687
293	my-model	.687
294	konkle_alexnetgn_ipcl_ref01_primary_model	.686
295	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
296	mobilenet_v2_1-4_224_pytorch	.684
297	alexnet_training_seed_09	.682
298	nasnet_mobile-tf	.681
299	mobilenet_v2_0.35_224	.680
300	mobilenet_v2_0_75_160	.680
301	effnetv2m_custom384	.676
302	resnet50-barlow	.675
303	mobilenet_v2_1.0_128-tf	.674
304	vision_transformer_vit_large_patch16_224	.670
305	mobilenet_v1_0.25_128	.668
306	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
307	mobilenet_v2_1_0_160	.667
308	cv_18_dagger_408_pretrained	.665
309	deit_small_imagenet_100_seed-0	.662
310	mobilenet_v1_0.5_192	.660
311	resnet50	.658
312	resnet50_moco_v2	.658
313	resnet50_simclr	.657
314	custom_model_cv_18_dagger_408	.656
315	artResNet18_1	.655
316	nasnet_mobile	.654
317	mobilenet_v2_1_0_224	.649
318	mobilenet_v1_1.0_192	.648
319	yudixie_resnet50_random_0_240908	.646
320	effnetb1_272x240	.645
321	resnet-18-LC_conv_init_m	.644
322	alexnet_training_seed_10	.645
323	BiT-M-R152x2	.641
324	AdvProp_efficientnet-b2	.627
325	mobilenet_v2_0.75_160-tf	.624
326	AT_efficientnet-b2	.625
327	vonegrcnn_52e_full	.623
328	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
329	vit_large_patch14_clip_224:openai_ft_in1k	.621
330	mobilenet_v2_0_5_192	.619
331	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
332	resnet-152_v2_pytorch	.615
333	convnext_small_imagenet_10_seed-0	.615
334	BiT-M-R50x1	.613
335	yudixie_resnet18_random_0_240719	.610
336	CORnetZ_CIFAR10_bs32_20_04	.605
337	vonegrcnn_47e	.604
338	inception_v1-tf	.600
339	mobilenet_v2_0.5_224-tf	.597
340	mobilenet_v1_1.0_160	.597
341	alexnet_training_seed_03	.596
342	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
343	deit_base_imagenet_full_seed-0	.589
344	r3m_resnet34	.590
345	vonegrcnn_47e	.581
346	deit_large_imagenet_full_seed-0	.577
347	mobilenet_v1_0.75_128	.570
348	mobilenet_v1_0.75_160	.565
349	mobilenet_v1_0.25_192	.560
350	mobilenet_v2_0.75_96	.557
351	inception_resnet_v2	.554
352	efficientnet_b2_imagenet_full	.550
353	r3m_resnet50_nocrop	.550
354	hmax	.535
355	r3m_resnet50	.519
356	r3m_resnet18	.516
357	resnet50_pretrained_with_retinal_waves	.515
358	my-model	.493
359	mobilenet_v2_0.75_224-tf	.490
360	alexnet_training_seed_08	.462
361	convnext_small_imagenet_1_seed-0	.459
362	CORnetZ_CIFAR10	.447
363	ViT-B/32	.385
364	mobilenet_v2_0.35_128	.375
365	deit_small_imagenet_10_seed-0	.375
366	resnet50_imagenet_1_seed-0	.355
367	alexnet_training_seed_05	.271
368	mobilenet_v2_0.5_160	.271
369	alexnet_training_seed_06	.215
370	resnet-18-LC_untrained	.170
371	resnet50-meshes-lt-100-original-pretrained	.169
372	resnet50-meshes-lt-100-original-scratch	.081
373	mobilenet_v2_0.5_128	.028
374	unet_entire
375	mobilenet_v2_0.35_160
376	fitvid_trained_on_physion
377	openclip
378	resnext101_32x32d_wsl
379	resnext101_32x48d_wsl
380	resnet50_ImageNet
381	resnet_101_v1
382	resnet_152_v2
383	regnet_y_400mf
384	tv_efficientnet-b1
385	alexnet_ks_torevert
386	yudixie_resnet50_imagenet1kpret_0_240312
387	resnet_152_v1
388	ViT_L_32_imagenet1k
389	resnext101_32x16d_wsl
390	densenet_201_pytorch
391	inception_v3_pytorch
392	pnasnet_large_pytorch
393	mobilevit_small
394	inception_v4
395	nasnet_large
396	deit_small_imagenet_1_seed-0
397	pnasnet_large
398	vonegrcnn_62e_nobn
399	resnet_101_v2
400	vonegrcnn_52e_full

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance