Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_w_sh_1_iter_conv_init_m	.984
2	omnivore_swinS	.984
3	yudixie_resnet18_rotation_reg_0_240719	.982
4	efficientnet-b7	.981
5	resnet-18-LC_w_sh_10_iter_conv_init_m	.969
6	alexnet_robust_correct	.965
7	yudixie_resnet18_distance_reg_0_240719	.961
8	AdvProp_efficientnet-b6	.956
9	BiT-S-R50x1	.954
10	vonegrcnn_62e_nobn	.955
11	vggface	.952
12	convnext_large_imagenet_full_seed-0	.952
13	yudixie_resnet18_distance_rotation_0_240719	.950
14	resnet_101_v1	.949
15	convnext_base:clip_laiona_augreg_ft_in1k_384	.950
16	yudixie_resnet50_distance_translation_0_240908	.945
17	omnivore_swinB	.944
18	resnet-18-LC_w_sh_100_iter_m	.941
19	resnet34_imagenet_full	.941
20	nasnet_large-tf	.939
21	yudixie_resnet18_distance_translation_rotation_0_240719	.938
22	cvt_cvt-13-224-in1k_4_LucyV4	.937
23	yudixie_resnet18_distance_translation_0_240719	.936
24	alexnet_l2_3_robust	.934
25	resnet101	.932
26	yudixie_resnet50_translation_rotation_0_240908	.932
27	mobilenet_v2_1.0_96	.932
28	resnet50	.930
29	resnet-50_untrained	.930
30	cvt_cvt-21-224-in1k_4_LucyV4	.928
31	resnet-18-LC_w_sh_1_iter_m	.928
32	AdvProp_efficientnet-b8	.928
33	resnet50-SIN_IN	.927
34	resnet18_imagenet_full	.926
35	cvt_cvt-21-384-in1k_4_LucyV4	.927
36	mobilenet_v2_1.3_224-tf	.925
37	resnet50-moclr8deg	.924
38	resnet-50_v1-tf	.923
39	BiT-S-R101x3	.923
40	vgg_19	.922
41	resnet-152_v2-tf	.922
42	convnext_base_imagenet_full_seed-0	.920
43	xception	.920
44	voneresnet-50-non_stochastic	.920
45	alexnet_early_checkpoint	.917
46	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.917
47	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.917
48	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.916
49	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.916
50	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.915
51	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.915
52	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.915
53	mobilenet_v2_1.4_224-tf	.915
54	antialias-resnet152	.914
55	inception_v4-tf	.913
56	Res2Net50_26w_4s	.913
57	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.913
58	inception_v3-tf	.911
59	yudixie_resnet50_distance_rotation_0_240908	.911
60	yudixie_resnet50_translation_reg_0_240908	.911
61	focalnet_tiny_lrf_in1k	.911
62	yudixie_resnet50_distance_translation_rotation_0_240908	.910
63	BiT-M-R101x1	.910
64	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.910
65	resnet50-simclr-vissl	.909
66	yudixie_resnet50_rotation_reg_0_240908	.909
67	vgg_16	.907
68	resnet50_l2_3_robust	.907
69	resnet-18_test_m	.906
70	BiT-M-R50x3	.907
71	texture_shape_alexnet_trained_on_SIN	.906
72	inception_v2-tf	.905
73	alexnet	.903
74	CORnet-S	.905
75	blt_vs	.904
76	resnext101_32x8d_wsl	.904
77	omnivore_swinT	.904
78	0.5x_resnet-18_LC_w_sh_1_iter	.904
79	resnet34_ecoset_full	.903
80	alexnet_random_l2_3_perturb	.902
81	resnet-50x2_untrained	.903
82	resnet50_byol	.901
83	BiT-S-R50x3	.900
84	resnet50_random_linf8_perturb	.900
85	vonealexnet_gaussian_noise_std4_fixed	.899
86	resnet101_ecoset_full	.897
87	SWSL_resnet50	.896
88	mobilenet_v2_1.0_160-tf	.896
89	AdvProp_efficientnet-b7	.895
90	convnext_tiny:in12k_ft_in1k	.893
91	resnet50-vicregl0p9	.892
92	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.892
93	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.891
94	alexnet_linf_8_robust	.890
95	BiT-S-R152x2	.889
96	resnet-18-LC_1st_conv_m	.889
97	resnet50-vicregl0p75	.888
98	imagenet_l2_3_0	.888
99	barlow-twins-resnet50	.888
100	yudixie_resnet50_distance_reg_0_240908	.888
101	resnet50_robust_l2_eps3	.886
102	resnet152_ecoset_full	.887
103	BiT-M-R101x3	.885
104	resnet-18-LC_w_sh_100_iter_conv_init_m	.885
105	alexnet_random_linf8_perturb	.883
106	grcnn	.884
107	ViT_L_32_imagenet1k	.882
108	resnet_50_v2	.881
109	grcnn_robust_v1	.883
110	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.881
111	yudixie_resnet50_random_0_240908	.879
112	CLIP-RN50	.879
113	resnet50_imagenet_100_seed-0	.879
114	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.878
115	alexnet	.877
116	alexnet	.877
117	alexnet-baseline	.877
118	yudixie_resnet50_imagenet1kpret_0_240908	.876
119	alexnet	.876
120	alexnet	.875
121	alexnet	.876
122	resnet50_tutorial	.875
123	resnet_50_v1	.875
124	alexnet	.875
125	grcnn_v2_text_noise	.875
126	alexnet	.874
127	resnet50	.874
128	resnet18_imagenet21kP	.874
129	yolos_tiny	.874
130	resnet50-sup	.874
131	grcnn_109	.872
132	mobilenet_v2_0.75_192-tf	.873
133	mobilenet_v2_1.0_224-tf	.871
134	resnet50_linf_8_robust	.871
135	CLIP_resnet50	.871
136	imagenet_l2_10_0	.870
137	resnet50-vitoimagevidnet8	.870
138	cornet_s	.869
139	resnet18_ecoset_full	.867
140	convnext_tiny_imagenet_full_seed-0	.868
141	CLIP_resnet50_float32	.867
142	mobilenet_v2_0_75_192	.867
143	resnet-101_v2-tf	.866
144	densenet-169	.866
145	convnext_tiny_sup	.865
146	CLIP_ViT-B_32	.864
147	resnet-18-LC_w_sh_10_iter_m	.863
148	RN50	.863
149	AdvProp_efficientnet-b4	.861
150	resnet152_imagenet_full	.861
151	convnext_xlarge:fb_in22k_ft_in1k	.861
152	resnet50-VITO-8deg-cc	.859
153	ReAlnet09	.860
154	convnext_small_imagenet_1_seed-0	.859
155	mobilenet_v2_1_4_224	.858
156	ReAlnet09_cornet	.858
157	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.857
158	resnet101_imagenet_full	.857
159	resnet-18_untrained	.857
160	resnet50_linf_4_robust	.857
161	resnet50_FractalDB	.856
162	ReAlnet01	.855
163	mobilenet_v2_1.0_192-tf	.855
164	ReAlnet_incorrect	.855
165	AdvProp_efficientnet-b0	.854
166	densenet-121	.854
167	convnext_small_imagenet_100_seed-0	.854
168	resnet-50_v2-tf	.853
169	resnet50_random_l2_perturb	.853
170	resnet_SIN_IN_FT_IN	.852
171	ReAlnet01_cornet	.853
172	AdvProp_efficientnet-b2	.852
173	effnetv2m_custom384	.852
174	inception_v3	.851
175	antialiased-r50	.852
176	AT_efficientnet-b2	.849
177	inception_v1	.849
178	yudixie_resnet18_translation_reg_0_240719	.849
179	resnet50_robust_l2_eps1	.848
180	0.5x_resnet-18_LC_w_sh_100_iter	.843
181	ReAlnet07	.842
182	resnet50-vicreg	.842
183	ReAlnet03	.842
184	resnet50-SIN_IN_IN	.841
185	ReAlnet07_cornet	.840
186	ReAlnet03_cornet	.838
187	mobilenet_v2_0.75_224-tf	.838
188	ReAlnet04	.838
189	yudixie_resnet18_translation_rotation_0_240719	.838
190	antialiased-rnext101_32x8d	.837
191	ReAlnet04_cornet	.836
192	vgg-16-keras	.836
193	SWSL_resnext101_32x8d	.836
194	ReAlnet10_cornet	.835
195	ReAlnet10	.834
196	effnetb1_272x240	.833
197	resnet-101_v1-tf	.832
198	resnet-152_v2_pytorch	.832
199	densenet-201	.831
200	cv_18_dagger_408_pretrained	.831
201	mobilenet_v2_1_0_160	.830
202	pnasnet_large-tf	.829
203	mobilenet_v2_1_3_224	.830
204	ReAlnet08_cornet	.829
205	ReAlnet08	.828
206	convnext_femto_ols:d1_in1k	.826
207	ReAlnet05_cornet	.826
208	ReAlnet05	.826
209	densenet-201-keras	.823
210	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.821
211	mobilenet_v2_1.0_128-tf	.822
212	mobilenet_v2_1_0_192	.820
213	vit_base_patch16_clip_224:openai_ft_in1k	.819
214	resnet50-barlow	.819
215	briaai_rmbg_1_4	.819
216	0.5x_resnet-18	.817
217	ReAlnet02	.816
218	BiT-S-R101x1	.816
219	ReAlnet02_cornet	.815
220	konkle_alexnetgn_ipcl_ref01_primary_model	.813
221	resnet50-SIN	.813
222	ReAlnet06	.813
223	BiT-S-R152x4	.811
224	BiT-M-R152x2	.811
225	ReAlnet06_cornet	.811
226	resnet50_imagenet_10_seed-0	.811
227	densenet-169-keras	.810
228	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.810
229	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.807
230	0.5x_resnet-18_LC	.808
231	yudixie_resnet18_category_class_0_240719	.807
232	FrankRobWobv0	.807
233	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.806
234	mobilenet_v2_0_5_224	.804
235	AlexNet_SIN	.803
236	BiT-M-R152x4	.802
237	resnet-50-robust	.801
238	resnet50_simclr	.795
239	convnext_large:fb_in22k_ft_in1k	.794
240	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.794
241	resnet50_moco_v2	.794
242	resnet-18-LC_d_w_sh_1x1_conv_init_m	.794
243	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.790
244	mobilenet_v2_0_5_192	.790
245	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.788
246	vit_large_patch14_clip_224:laion2b_ft_in1k	.788
247	alexnet_training_seed_07	.787
248	0.5x_resnet-18_LC_w_sh_10_iter	.787
249	texture_shape_resnet50_trained_on_SIN	.786
250	yudixie_resnet18_random_0_240719	.785
251	mobilenet_v2_0_75_160	.783
252	efficientnet_b1_imagenet_full	.784
253	my-model	.783
254	shufflenet_v2_x1_0	.782
255	ViT-B/32	.781
256	yudixie_resnet50_object_class_0_240908	.779
257	yudixie_resnet18_object_class_0_240719	.778
258	mobilenet_v2_0_75_224	.777
259	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.777
260	yudixie_resnet50_category_class_0_240908	.776
261	vgg-19-keras	.774
262	vit_relpos_base_patch16_clsgap_224:sw_in1k	.774
263	alexnet_training_seed_09	.774
264	nasnet_mobile-tf	.769
265	vit_large_patch14_clip_336:laion2b_ft_in1k	.764
266	vit_large_patch14_clip_224:openai_ft_in1k	.762
267	efficientnet_b0	.762
268	convnext_small_imagenet_full_seed-0	.761
269	cvt_cvt-13-384-in1k_4_LucyV4	.760
270	inception_v1-tf	.759
271	mobilenet_v2_1-4_224_pytorch	.753
272	alexnet_training_seed_04	.753
273	custom_model_cv_18_dagger_408	.751
274	densenet-121-keras	.743
275	yudixie_resnet18_imagenet1kpret_0_240719	.741
276	mobilenet_v2_0.35_224	.740
277	deit_small_imagenet_full_seed-0	.739
278	mobilenet_v2_1_0_128	.739
279	alexnet_training_seed_01	.739
280	resnet50_ecoset_full	.739
281	alexnet_training_seed_02	.739
282	nasnet_mobile	.734
283	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.730
284	inception_resnet_v2	.728
285	vision_transformer_vit_large_patch16_224	.728
286	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.724
287	resnet-152_v1-tf	.722
288	mobilenet_v2_0.75_96	.719
289	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.718
290	vonegrcnn_52e_full	.714
291	resnet-18-LC_m	.710
292	CORnet-Z	.706
293	vonegrcnn_47e	.705
294	efficientnet_b0_imagenet_full	.702
295	resnet18-supervised	.702
296	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.701
297	vonegrcnn_47e	.700
298	resnet50_imagenet_full	.698
299	convnext_small_imagenet_10_seed-0	.692
300	alexnet_training_seed_10	.691
301	alexnet_reduced_aliasing_early_checkpoint	.683
302	alexnet_training_seed_03	.674
303	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.671
304	mobilenet_v2_0.5_224-tf	.670
305	deit_base_imagenet_full_seed-0	.658
306	resnet-18-LC_conv_init_m	.648
307	efficientnet_b2_imagenet_full	.647
308	hmax	.644
309	mobilenet_v2_1_0_224	.641
310	mobilenet_v1_0.25_128	.612
311	mobilenet_v2_0.5_192-tf	.600
312	BiT-M-R50x1	.597
313	v1-pyr-nodown	.581
314	r3m_resnet34_nocrop	.566
315	CORnetZ_CIFAR10	.554
316	artResNet18_1	.548
317	mobilenet_v2_0.5_160	.518
318	r3m_resnet50_nocrop	.517
319	VOneCORnet-S	.511
320	r3m_resnet34	.505
321	voneresnet-50	.494
322	voneresnet-50-robust	.491
323	r3m_resnet50	.483
324	deit_small_imagenet_100_seed-0	.447
325	mobilenet_v2_0.75_128	.441
326	mobilenet_v2_0.75_160-tf	.440
327	alexnet_training_seed_08	.432
328	resnet50_pretrained_with_retinal_waves	.428
329	r3m_resnet18	.427
330	deit_small_imagenet_10_seed-0	.393
331	resnet50-cifar	.393
332	mobilenet_v2_0.5_128	.393
333	resnet50-meshes-lt-100-original-pretrained	.389
334	resnet50_imagenet_1_seed-0	.387
335	deit_large_imagenet_full_seed-0	.386
336	alexnet_training_seed_05	.297
337	resnet-18-LC_untrained	.262
338	alexnet_training_seed_06	.254
339	CORnetZ_CIFAR10_bs32_20_04	.229
340	my-model	.150
341	resnet50-meshes-lt-100-original-scratch	.108
342	pnasnet_large_pytorch	X
343	inception_v3_pytorch	X
344	resnet50_ImageNet	X
345	resnext101_32x32d_wsl	X
346	fixres_resnext101_32x48d_wsl	X
347	vonegrcnn_52e_full	X
348	yudixie_resnet50_imagenet1kpret_0_240312	X
349	resnet_101_v2	X
350	resnext101_32x48d_wsl	X
351	densenet_201_pytorch	X
352	alexnet_ks_torevert	X
353	inception_v4	X
354	mobilenet_v2_0.35_160	X
355	pnasnet_large	X
356	mobilevit_small	X
357	openclip	X
358	resnext101_32x16d_wsl	X
359	resnet_152_v2	X
360	deit_small_imagenet_1_seed-0	X
361	tv_efficientnet-b1	X
362	regnet_y_400mf	X
363	nasnet_large	X
364	vonegrcnn_62e_nobn	X
365	resnet_152_v1	X
366	fitvid_trained_on_physion	X

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_bandwidth