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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Marques2020_DeValois1982-peak_sf")
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_100_iter_m	.964
2	resnet50_imagenet_10_seed-0	.950
3	alexnet_training_seed_01	.943
4	resnet-18-LC_m	.941
5	resnet50_linf_4_robust	.935
6	alexnet_training_seed_08	.933
7	AlexNet_SIN_fov12	.933
8	mobilenet_v2_1_0_192	.925
9	vonegrcnn_62e_nobn	.925
10	resnet50_linf_8_robust	.923
11	vonegrcnn_52e_full	.917
12	alexnet_training_seed_01_fov12	.917
13	alexnet_reduced_aliasing_early_checkpoint	.911
14	vonegrcnn_47e	.908
15	vgg-19-keras	.901
16	resnet50_l2_3_robust	.897
17	resnet50_robust_l2_eps1	.895
18	resnet-18-LC_w_sh_100_iter_conv_init_m	.893
19	ReAlnet01_cornet_fov16	.891
20	alexnet_training_seed_10	.888
21	yudixie_wbh_object_class_scaling_0415_run_1	.886
22	resnet-18-LC_w_sh_1_iter_conv_init_m	.885
23	pnasnet_large_halfPrecision	.882
24	alexnet_fov12	.878
25	resnet50_robust_l2_eps3	.876
26	alexnet_training_seed_06	.873
27	voneresnet-50-non_stochastic	.872
28	BiT-S-R152x2	.872
29	yudixie_wbh_object_class_scaling_0415_run_3	.871
30	nasnet_large-tf	.868
31	RN50	.865
32	xception	.862
33	inception_v1	.862
34	mobilenet_v2_1.0_96	.861
35	mobilenet_v2_0_75_160	.860
36	mobilenet_v2_0.75_160-tf	.859
37	vgg-16-keras	.857
38	alexnet_training_seed_04	.857
39	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.858
40	0.5x_resnet-18_LC_w_sh_100_iter	.855
41	densenet-201-keras	.854
42	artResNet18_1	.853
43	AlexNet_SIN	.852
44	resnet-50-robust	.852
45	effnetb1_272x240	.851
46	yudixie_wbh_object_class_scaling_0415_run_2	.850
47	grcnn	.850
48	voneresnet-50	.847
49	resnet-50_untrained	.844
50	yudixie_wbh_object_class_scaling_0415_run_0	.844
51	mobilenet_v2_1_0_224	.843
52	AlexNet_SIN_fov16	.842
53	grcnn_109	.837
54	deepeisnn_ei_imagenet_resnet18	.836
55	voneresnet-50-robust	.835
56	resnet50-moclr8deg	.835
57	VOneCORnet-S	.834
58	mobilenet_v2_0.75_96	.832
59	effnetv2m_custom384	.831
60	resnet-18-LC_d_w_sh_1x1_conv_init_m	.830
61	imagenet_l2_3_0	.829
62	omnivore_swinB	.829
63	resnet50_byol	.828
64	alexnet_training_seed_07	.826
65	inception_v4-tf	.825
66	pnasnet_large-tf	.822
67	cvt_cvt-13-384-in1k_4_LucyV4	.818
68	alexnet_training_seed_09	.817
69	convnext_tiny_imagenet_full_seed-0	.816
70	mobilenet_v2_0.75_224-tf	.815
71	densenet-201	.814
72	mobilenet_v2_0.5_224-tf	.812
73	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.812
74	densenet-169	.812
75	resnet-18-LC_w_sh_10_iter_m	.811
76	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.811
77	mobilenet_v2_0_5_224	.810
78	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.808
79	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.805
80	resnet_50_v1	.805
81	resnet-18-LC_w_sh_10_iter_conv_init_m	.804
82	resnet_50_v1_spiking_l4	.803
83	yudixie_resnet50_imagenet1kpret_0_240908	.804
84	resnet_50_v1_spiking_l3	.803
85	resnet_50_v1_spiking	.803
86	resnet50_simclr	.802
87	alexnet	.803
88	resnet50_tutorial	.803
89	resnet_50_v1_spiking_l4a	.803
90	resnet50-sup	.803
91	nasnet_mobile	.801
92	SWSL_resnext101_32x8d	.801
93	omnivore_swinT	.799
94	resnet50_moco_v2	.797
95	efficientnet_b0_imagenet_full	.798
96	densenet-169-keras	.796
97	resnet-18_untrained	.795
98	resnet-18-LC_conv_init_m	.795
99	omnivore_swinS	.794
100	alexnet_fov16	.793
101	focalnet_tiny_lrf_in1k	.793
102	convnext_large_clip_laion2b_finelayers	.793
103	grcnn_robust_v1	.792
104	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.791
105	konkle_alexnetgn_ipcl_ref01_primary_model	.790
106	resnet-50x2_untrained	.790
107	alexnet_training_seed_02	.788
108	vgg_16	.787
109	resnet50_FractalDB	.787
110	blt_vs	.787
111	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.783
112	resnet-152_v1-tf	.783
113	yudixie_resnet18_imagenet1kpret_0_240719	.783
114	mobilenet_v2_0_75_192	.782
115	imagenet_l2_10_0	.782
116	yudixie_wbh_object_class_scaling_0415_imagenet	.782
117	resnet50-SIN	.782
118	resnet-101_v2-tf	.779
119	convnext_large_imagenet_full_seed-0	.778
120	yudixie_resnet18_object_class_0_240719	.777
121	cvt_cvt-13-224-in1k_4_LucyV4	.776
122	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.774
123	resnet50-VITO-8deg-cc	.773
124	r3m_resnet18	.773
125	BiT-M-R101x3	.772
126	resnet50-barlow	.771
127	nasnet_mobile-tf	.770
128	resnet50-vicreg	.769
129	convnext_small_imagenet_1_seed-0	.769
130	BiT-M-R101x1	.769
131	alexnet_training_seed_03	.768
132	0.5x_resnet-18_LC_w_sh_10_iter	.768
133	BiT-S-R50x3	.766
134	resnet50_random_l2_perturb	.764
135	resnet50	.764
136	alexnet_random_linf8_perturb	.764
137	vggface	.763
138	SWSL_resnet50	.762
139	resnet50-SIN_IN_IN	.759
140	resnet50_hvs_wzc	.759
141	0.5x_resnet-18_LC	.756
142	mobilenet_v2_0_75_224	.756
143	CLIP_resnet50	.755
144	CLIP_resnet50_float32	.754
145	resnet50-vicregl0p75	.755
146	my-model	.755
147	resnet-101_v1-tf	.752
148	convnext_tiny:in12k_ft_in1k	.752
149	AdvProp_efficientnet-b7	.749
150	convnext_large_in22k_supervised	.749
151	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.749
152	alexnet_training_seed_01_fov4	.748
153	mobilenet_v2_1_0_160	.747
154	densenet-121	.745
155	convnext_femto_ols:d1_in1k	.743
156	convnext_large:fb_in22k_ft_in1k	.742
157	BiT-M-R152x2	.742
158	alexnet_training_seed_05	.741
159	convnext_small_imagenet_10_seed-0	.741
160	BiT-S-R101x1	.741
161	resnet-50_v2-tf	.740
162	yudixie_resnet18_distance_reg_0_240719	.740
163	mobilenet_v2_1.3_224-tf	.740
164	resnet-152_v2-tf	.737
165	texture_shape_resnet50_trained_on_SIN	.737
166	resnet-152_v2_pytorch	.733
167	AdvProp_efficientnet-b2	.732
168	resnet50_random_linf8_perturb	.732
169	convnext_tiny_sup	.731
170	AT_efficientnet-b2	.731
171	convnext_small_imagenet_full_seed-0	.729
172	vonealexnet_gaussian_noise_std4_fixed	.728
173	yudixie_resnet50_random_0_240908	.727
174	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.726
175	convnext_base_fb_in22k_ft_in1k	.726
176	cv_18_dagger_408_pretrained	.725
177	compact_vgg19_V4	.726
178	mobilenet_v2_0_5_192	.724
179	resnet_SIN_IN_FT_IN	.725
180	resnet18_fair	.722
181	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.723
182	BiT-M-R50x1	.722
183	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.721
184	shufflenet_v2_x1_0	.721
185	inception_v3-tf	.720
186	mobilenet_v2_1_4_224	.719
187	mobilenet_v2_0.75_192-tf	.719
188	compact_resnet50_IT	.717
189	deit_base_imagenet_full_seed-0	.717
190	0.5x_resnet-18_LC_w_sh_1_iter	.716
191	inception_resnet_v2	.714
192	densenet-121-keras	.712
193	yudixie_resnet50_translation_rotation_0_240908	.710
194	mobilenet_v2_1_3_224	.708
195	BiT-S-R101x3	.708
196	AdvProp_efficientnet-b4	.707
197	deit_small_imagenet_100_seed-0	.706
198	resnet-50_v1-tf	.706
199	convnext_xlarge:fb_in22k_ft_in1k	.703
200	CLIP-RN50	.703
201	antialiased-rnext101_32x8d	.703
202	compact_resnet50_robust_V4	.702
203	yudixie_resnet50_rotation_reg_0_240908	.701
204	CORnetZ_CIFAR10_bs32_20_04	.702
205	deit3_base_patch16_224_fb_in22k_ft_in1k	.701
206	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.701
207	alexnet_early_checkpoint	.700
208	BiT-S-R152x4	.698
209	BiT-S-R50x1	.698
210	ReAlnet01_cornet_fov12	.696
211	r3m_resnet50_nocrop	.695
212	CORnetZ_CIFAR10	.694
213	inception_v2-tf	.695
214	yudixie_resnet50_object_class_0_240908	.692
215	resnet-18-LC_w_sh_1_iter_m	.692
216	yudixie_resnet50_category_class_0_240908	.691
217	grcnn_v2_text_noise	.691
218	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.690
219	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
220	BiT-M-R50x3	.690
221	compact_cornets_V4	.688
222	custom_model_cv_18_dagger_408	.687
223	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.687
224	yudixie_resnet50_distance_rotation_0_240908	.686
225	compact_cornets_IT	.687
226	efficientnet_b2_imagenet_full	.686
227	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.686
228	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.686
229	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.686
230	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.686
231	AdvProp_efficientnet-b8	.685
232	yudixie_resnet18_random_0_240719	.684
233	eva02_large_in22k	.685
234	mobilenet_v2_0.5_192-tf	.681
235	vit_relpos_base_patch16_clsgap_224:sw_in1k	.681
236	yudixie_resnet50_distance_translation_0_240908	.680
237	mobilenet_v1_0.25_128	.677
238	alexnet_l2_3_robust	.676
239	mobilenet_v2_0.75_128	.675
240	mobilenet_v2_1.0_192-tf	.675
241	eBarlow_lmda_02_1000ep	.674
242	BiT-M-R152x4	.673
243	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.671
244	resnet50_ewconplus_wzc	.671
245	ViT_L_32_imagenet1k	.671
246	r3m_resnet50	.670
247	yudixie_resnet50_distance_reg_0_240908	.669
248	antialias-resnet152	.665
249	resnet50_st_wzc_2	.659
250	cvt_cvt-21-224-in1k_4_LucyV4	.655
251	yudixie_resnet50_distance_translation_rotation_0_240908	.653
252	vit_large_patch14_clip_224:openai_ft_in1k	.652
253	antialiased-r50	.651
254	vit_huge_clip336_laion	.651
255	yudixie_resnet18_distance_translation_0_240719	.650
256	yudixie_resnet18_category_class_0_240719	.650
257	FrankRobWobv0	.647
258	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.643
259	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.641
260	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.640
261	convnext_small_imagenet_100_seed-0	.638
262	deit_large_imagenet_full_seed-0	.638
263	alexnet_training_seed_01_fov16	.638
264	resnet50-vicregl0p9	.636
265	efficientnet_b1_imagenet_full	.635
266	yudixie_resnet18_translation_rotation_0_240719	.635
267	cvt_cvt-21-384-in1k_4_LucyV4	.635
268	vit_base_patch16_clip_224:openai_ft_in1k	.634
269	resnet_101_v1	.628
270	AdvProp_efficientnet-b0	.627
271	resnet50-SIN_IN	.626
272	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.625
273	resnet50_primary_visual_cortex	.623
274	vgg_19	.622
275	r3m_resnet34	.620
276	mobilenet_v2_1.4_224-tf	.620
277	convnext_base_imagenet_full_seed-0	.619
278	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.615
279	compact_resnet50_V4	.614
280	compact_resnet50_robust_IT	.612
281	yolos_tiny	.608
282	resnet50_st_wzc_seed7_2_323	.607
283	mobilenet_v2_1_0_128	.605
284	Res2Net50_26w_4s	.605
285	yudixie_resnet50_translation_reg_0_240908	.602
286	inception_v3	.601
287	barlow-twins-resnet50	.597
288	mobilenet_v2_0.35_224	.595
289	mobilenet_v2_1.0_128-tf	.593
290	mobilenet_v2_1.0_224-tf	.592
291	mobilenet_v2_1.0_160-tf	.592
292	compact_vgg19_IT	.592
293	resnet50_ewconplus_wzc_seed6_2_323	.591
294	resnet50_st_wzc_seed3_2_323	.591
295	yudixie_resnet18_translation_reg_0_240719	.586
296	yudixie_resnet18_distance_translation_rotation_0_240719	.583
297	resnet50_st_wzc_seed6_2_323	.583
298	resnet-18-LC_untrained	.580
299	CORnet-Z	.579
300	alexnet_robust_correct	.579
301	resnet-18-LC_1st_conv_m	.576
302	convnext_base_fb_in1k	.575
303	CORnet-S	.570
304	ReAlnet07_ALL	.569
305	mobilenet_v2_1-4_224_pytorch	.567
306	AdvProp_efficientnet-b6	.564
307	ReAlnet10_ALL	.563
308	briaai_rmbg_1_4	.560
309	ReAlnet02_ALL	.560
310	resnet101	.558
311	yudixie_resnet18_rotation_reg_0_240719	.557
312	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.553
313	resnet18_imagenet21kP	.554
314	resnet50_imagenet_1_seed-0	.553
315	yudixie_resnet18_distance_rotation_0_240719	.552
316	mobilenet_v2_0.5_128	.550
317	vision_transformer_vit_large_patch16_224	.549
318	ReAlnet03_ALL	.548
319	ReAlnet06_ALL	.548
320	ReAlnet08_ALL	.547
321	convnext_base_fb_in1k_gram_aligned_dinov3	.547
322	ReAlnet05_ALL	.546
323	ReAlnet09_ALL	.546
324	ReAlnet01_ALL	.546
325	resnet50_ewconplus_wzc_seed5_2__323	.545
326	ReAlnet07	.544
327	resnext101_32x8d_wsl	.543
328	ReAlnet07_cornet	.543
329	ReAlnet04_ALL	.543
330	ReAlnet08	.541
331	ReAlnet08_cornet	.541
332	resnet50_ewconplus_wzc_seed2_2__323	.540
333	mobilenet_v2_0.5_160	.539
334	efficientnet-b7	.537
335	resnet50_pretrained_with_retinal_waves	.534
336	convnext_base:clip_laiona_augreg_ft_in1k_384	.529
337	ViT-B/32	.529
338	0.5x_resnet-18	.528
339	ReAlnet01_cornet	.527
340	ReAlnet01	.528
341	ReAlnet04	.525
342	ReAlnet04_cornet	.524
343	vit_large_patch14_clip_336:laion2b_ft_in1k	.524
344	ReAlnet09_cornet	.522
345	ReAlnet10_cornet	.522
346	ReAlnet09	.520
347	efficientnet_b0	.521
348	ReAlnet10	.521
349	resnet-18_test_m	.516
350	resnet50-simclr-vissl	.515
351	ReAlnet06_cornet	.513
352	ReAlnet06	.512
353	alexnet_linf_8_robust	.512
354	resnet_50_v2	.511
355	v1-pyr-nodown	.510
356	ReAlnet03	.509
357	ReAlnet03_cornet	.509
358	resnet101_ecoset_full	.506
359	vit_large_patch14_clip_224:laion2b_ft_in1k	.503
360	hmax	.503
361	deepeisnn_ei_cifar10_resnet18	.502
362	resnet101_imagenet_full	.498
363	texture_shape_alexnet_trained_on_SIN	.497
364	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.493
365	cornet_s	.487
366	resnet50_imagenet_full	.486
367	ReAlnet02_cornet	.486
368	ReAlnet02	.485
369	ReAlnet05	.483
370	ReAlnet05_cornet	.483
371	resnet152_ecoset_full	.481
372	alexnet_fov4	.480
373	resnet50_ecoset_full	.472
374	resnet50-vitoimagevidnet8	.473
375	resnet18_imagenet_full	.472
376	resnet18_ecoset_full	.471
377	dinov2_vitl14_lc	.469
378	inception_v1-tf	.466
379	CLIP_ViT-B_32	.460
380	alexnet_random_l2_3_perturb	.444
381	resnet34_ecoset_full	.443
382	deit_small_imagenet_full_seed-0	.442
383	resnet50_imagenet_100_seed-0	.435
384	resnet152_imagenet_full	.429
385	mobilevit_small	.429
386	my-model	.425
387	resnet34_imagenet_full	.397
388	dinov2_vitl14_reg_lc	.397
389	dinov2_vitg14_reg_lc	.394
390	AlexNet_SIN_fov4	.382
391	deepeisnn_ei_cifar10_vgg19	.382
392	dinov2_vitg14_lc	.346
393	vit_base_patch14_reg4_dinov2-lvd142m	.332
394	deit_small_imagenet_10_seed-0	.330
395	dinov2_vitl14_lc_res336	.312
396	vit_base_patch14_dinov2-lvd142m	.310
397	deit3_base_patch16_224_fb_in1k	.303
398	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.302
399	vit_base_patch16_dinov3-lvd1689m	.258
400	resnet50-cifar	.248
401	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.245
402	ReAlnet01_cornet_fov4	.196
403	mobilenet_v2_0.35_160
404	resnet18-supervised
405	r3m_resnet34_nocrop
406	fitvid_trained_on_physion
407	openclip
408	resnext101_32x32d_wsl
409	resnext101_32x48d_wsl
410	resnet50_ImageNet
411	regnet_y_400mf
412	tv_efficientnet-b1
413	alexnet_ks_torevert
414	yudixie_resnet50_imagenet1kpret_0_240312
415	resnet_152_v1
416	resnext101_32x16d_wsl
417	densenet_201_pytorch
418	pnasnet_large_pytorch
419	inception_v3_pytorch
420	inception_v4
421	nasnet_large
422	deit_small_imagenet_1_seed-0
423	pnasnet_large
424	vonegrcnn_62e_nobn
425	resnet_101_v2
426	vonegrcnn_47e
427	vonegrcnn_52e_full
428	resnet_152_v2
429	pr1_stl10_disentangled_alpha04
430	predictive_coding_pc
431	dinov2_vitl14_reg_lc_featread
432	vit_large_clip336_openai
433	convnext_xxlarge_clip

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: peak_sf