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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	resnet-18-LC_w_sh_1_iter_conv_init_m	.885
22	alexnet_fov12	.878
23	resnet50_robust_l2_eps3	.876
24	alexnet_training_seed_06	.873
25	voneresnet-50-non_stochastic	.872
26	BiT-S-R152x2	.872
27	nasnet_large-tf	.868
28	RN50	.865
29	xception	.862
30	inception_v1	.862
31	mobilenet_v2_1.0_96	.861
32	mobilenet_v2_0_75_160	.860
33	mobilenet_v2_0.75_160-tf	.859
34	vgg-16-keras	.857
35	alexnet_training_seed_04	.857
36	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.858
37	0.5x_resnet-18_LC_w_sh_100_iter	.855
38	densenet-201-keras	.854
39	artResNet18_1	.853
40	AlexNet_SIN	.852
41	resnet-50-robust	.852
42	effnetb1_272x240	.851
43	grcnn	.850
44	voneresnet-50	.847
45	resnet-50_untrained	.844
46	mobilenet_v2_1_0_224	.843
47	AlexNet_SIN_fov16	.842
48	grcnn_109	.837
49	voneresnet-50-robust	.835
50	resnet50-moclr8deg	.835
51	VOneCORnet-S	.834
52	mobilenet_v2_0.75_96	.832
53	effnetv2m_custom384	.831
54	resnet-18-LC_d_w_sh_1x1_conv_init_m	.830
55	imagenet_l2_3_0	.829
56	omnivore_swinB	.829
57	resnet50_byol	.828
58	alexnet_training_seed_07	.826
59	inception_v4-tf	.825
60	pnasnet_large-tf	.822
61	cvt_cvt-13-384-in1k_4_LucyV4	.818
62	alexnet_training_seed_09	.817
63	convnext_tiny_imagenet_full_seed-0	.816
64	mobilenet_v2_0.75_224-tf	.815
65	densenet-201	.814
66	mobilenet_v2_0.5_224-tf	.812
67	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.812
68	densenet-169	.812
69	resnet-18-LC_w_sh_10_iter_m	.811
70	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.811
71	mobilenet_v2_0_5_224	.810
72	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.808
73	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.805
74	resnet_50_v1	.805
75	resnet-18-LC_w_sh_10_iter_conv_init_m	.804
76	resnet_50_v1_spiking_l4	.803
77	yudixie_resnet50_imagenet1kpret_0_240908	.804
78	resnet_50_v1_spiking_l3	.803
79	resnet_50_v1_spiking	.803
80	resnet50_simclr	.802
81	alexnet	.803
82	resnet50_tutorial	.803
83	resnet_50_v1_spiking_l4a	.803
84	alexnet	.802
85	alexnet	.802
86	alexnet	.802
87	resnet50-sup	.803
88	alexnet	.802
89	alexnet	.802
90	alexnet	.802
91	alexnet	.802
92	nasnet_mobile	.801
93	SWSL_resnext101_32x8d	.801
94	alexnet-baseline	.800
95	omnivore_swinT	.799
96	resnet50_moco_v2	.797
97	efficientnet_b0_imagenet_full	.798
98	densenet-169-keras	.796
99	resnet-18_untrained	.795
100	resnet-18-LC_conv_init_m	.795
101	omnivore_swinS	.794
102	alexnet_fov16	.793
103	focalnet_tiny_lrf_in1k	.793
104	grcnn_robust_v1	.792
105	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.791
106	konkle_alexnetgn_ipcl_ref01_primary_model	.790
107	resnet-50x2_untrained	.790
108	alexnet_training_seed_02	.788
109	vgg_16	.787
110	resnet50_FractalDB	.787
111	blt_vs	.787
112	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.783
113	resnet-152_v1-tf	.783
114	yudixie_resnet18_imagenet1kpret_0_240719	.783
115	mobilenet_v2_0_75_192	.782
116	imagenet_l2_10_0	.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	resnet50-meshes-lt-100-original-scratch	.763
137	alexnet_random_linf8_perturb	.764
138	vggface	.763
139	SWSL_resnet50	.762
140	resnet50-SIN_IN_IN	.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	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.749
151	alexnet_training_seed_01_fov4	.748
152	mobilenet_v2_1_0_160	.747
153	densenet-121	.745
154	convnext_femto_ols:d1_in1k	.743
155	convnext_large:fb_in22k_ft_in1k	.742
156	BiT-M-R152x2	.742
157	alexnet_training_seed_05	.741
158	convnext_small_imagenet_10_seed-0	.741
159	BiT-S-R101x1	.741
160	resnet-50_v2-tf	.740
161	yudixie_resnet18_distance_reg_0_240719	.740
162	mobilenet_v2_1.3_224-tf	.740
163	resnet-152_v2-tf	.737
164	texture_shape_resnet50_trained_on_SIN	.737
165	resnet-152_v2_pytorch	.733
166	AdvProp_efficientnet-b2	.732
167	resnet50_random_linf8_perturb	.732
168	convnext_tiny_sup	.731
169	AT_efficientnet-b2	.731
170	convnext_small_imagenet_full_seed-0	.729
171	vonealexnet_gaussian_noise_std4_fixed	.728
172	yudixie_resnet50_random_0_240908	.727
173	cv_18_dagger_408_pretrained	.725
174	compact_vgg19_V4	.726
175	mobilenet_v2_0_5_192	.724
176	resnet_SIN_IN_FT_IN	.725
177	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.723
178	BiT-M-R50x1	.722
179	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.721
180	shufflenet_v2_x1_0	.721
181	inception_v3-tf	.720
182	mobilenet_v2_1_4_224	.719
183	mobilenet_v2_0.75_192-tf	.719
184	compact_resnet50_IT	.717
185	deit_base_imagenet_full_seed-0	.717
186	0.5x_resnet-18_LC_w_sh_1_iter	.716
187	inception_resnet_v2	.714
188	densenet-121-keras	.712
189	yudixie_resnet50_translation_rotation_0_240908	.710
190	mobilenet_v2_1_3_224	.708
191	BiT-S-R101x3	.708
192	AdvProp_efficientnet-b4	.707
193	deit_small_imagenet_100_seed-0	.706
194	resnet-50_v1-tf	.706
195	convnext_xlarge:fb_in22k_ft_in1k	.703
196	CLIP-RN50	.703
197	antialiased-rnext101_32x8d	.703
198	compact_resnet50_robust_V4	.702
199	yudixie_resnet50_rotation_reg_0_240908	.701
200	CORnetZ_CIFAR10_bs32_20_04	.702
201	alexnet_early_checkpoint	.700
202	BiT-S-R152x4	.698
203	BiT-S-R50x1	.698
204	ReAlnet01_cornet_fov12	.696
205	r3m_resnet50_nocrop	.695
206	CORnetZ_CIFAR10	.694
207	inception_v2-tf	.695
208	yudixie_resnet50_object_class_0_240908	.692
209	resnet-18-LC_w_sh_1_iter_m	.692
210	yudixie_resnet50_category_class_0_240908	.691
211	grcnn_v2_text_noise	.691
212	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.690
213	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
214	BiT-M-R50x3	.690
215	compact_cornets_V4	.688
216	custom_model_cv_18_dagger_408	.687
217	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.687
218	yudixie_resnet50_distance_rotation_0_240908	.686
219	compact_cornets_IT	.687
220	efficientnet_b2_imagenet_full	.686
221	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.686
222	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.686
223	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.686
224	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.686
225	AdvProp_efficientnet-b8	.685
226	yudixie_resnet18_random_0_240719	.684
227	mobilenet_v2_0.5_192-tf	.681
228	vit_relpos_base_patch16_clsgap_224:sw_in1k	.681
229	yudixie_resnet50_distance_translation_0_240908	.680
230	mobilenet_v1_0.25_128	.677
231	alexnet_l2_3_robust	.676
232	mobilenet_v2_0.75_128	.675
233	mobilenet_v2_1.0_192-tf	.675
234	BiT-M-R152x4	.673
235	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.671
236	resnet50_ewconplus_wzc	.671
237	ViT_L_32_imagenet1k	.671
238	r3m_resnet50	.670
239	yudixie_resnet50_distance_reg_0_240908	.669
240	antialias-resnet152	.665
241	cvt_cvt-21-224-in1k_4_LucyV4	.655
242	yudixie_resnet50_distance_translation_rotation_0_240908	.653
243	vit_large_patch14_clip_224:openai_ft_in1k	.652
244	antialiased-r50	.651
245	yudixie_resnet18_distance_translation_0_240719	.650
246	yudixie_resnet18_category_class_0_240719	.650
247	FrankRobWobv0	.647
248	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.643
249	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.641
250	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.640
251	convnext_small_imagenet_100_seed-0	.638
252	deit_large_imagenet_full_seed-0	.638
253	alexnet_training_seed_01_fov16	.638
254	resnet50-vicregl0p9	.636
255	efficientnet_b1_imagenet_full	.635
256	yudixie_resnet18_translation_rotation_0_240719	.635
257	cvt_cvt-21-384-in1k_4_LucyV4	.635
258	vit_base_patch16_clip_224:openai_ft_in1k	.634
259	resnet_101_v1	.628
260	AdvProp_efficientnet-b0	.627
261	resnet50-SIN_IN	.626
262	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.625
263	resnet50_primary_visual_cortex	.623
264	vgg_19	.622
265	r3m_resnet34	.620
266	mobilenet_v2_1.4_224-tf	.620
267	convnext_base_imagenet_full_seed-0	.619
268	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.615
269	compact_resnet50_V4	.614
270	compact_resnet50_robust_IT	.612
271	yolos_tiny	.608
272	mobilenet_v2_1_0_128	.605
273	Res2Net50_26w_4s	.605
274	yudixie_resnet50_translation_reg_0_240908	.602
275	inception_v3	.601
276	barlow-twins-resnet50	.597
277	mobilenet_v2_0.35_224	.595
278	mobilenet_v2_1.0_128-tf	.593
279	mobilenet_v2_1.0_224-tf	.592
280	mobilenet_v2_1.0_160-tf	.592
281	compact_vgg19_IT	.592
282	yudixie_resnet18_translation_reg_0_240719	.586
283	yudixie_resnet18_distance_translation_rotation_0_240719	.583
284	resnet-18-LC_untrained	.580
285	CORnet-Z	.579
286	alexnet_robust_correct	.579
287	resnet-18-LC_1st_conv_m	.576
288	resnet50-meshes-lt-100-original-pretrained	.572
289	CORnet-S	.570
290	ReAlnet07_ALL	.569
291	mobilenet_v2_1-4_224_pytorch	.567
292	AdvProp_efficientnet-b6	.564
293	ReAlnet10_ALL	.563
294	briaai_rmbg_1_4	.560
295	ReAlnet02_ALL	.560
296	resnet101	.558
297	yudixie_resnet18_rotation_reg_0_240719	.557
298	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.553
299	resnet18_imagenet21kP	.554
300	resnet50_imagenet_1_seed-0	.553
301	yudixie_resnet18_distance_rotation_0_240719	.552
302	mobilenet_v2_0.5_128	.550
303	vision_transformer_vit_large_patch16_224	.549
304	ReAlnet03_ALL	.548
305	ReAlnet06_ALL	.548
306	ReAlnet08_ALL	.547
307	ReAlnet05_ALL	.546
308	ReAlnet09_ALL	.546
309	ReAlnet01_ALL	.546
310	ReAlnet07	.544
311	resnext101_32x8d_wsl	.543
312	ReAlnet07_cornet	.543
313	ReAlnet04_ALL	.543
314	ReAlnet08	.541
315	ReAlnet08_cornet	.541
316	mobilenet_v2_0.5_160	.539
317	efficientnet-b7	.537
318	resnet50_pretrained_with_retinal_waves	.534
319	convnext_base:clip_laiona_augreg_ft_in1k_384	.529
320	ViT-B/32	.529
321	0.5x_resnet-18	.528
322	ReAlnet01_cornet	.527
323	ReAlnet01	.528
324	ReAlnet04	.525
325	ReAlnet04_cornet	.524
326	vit_large_patch14_clip_336:laion2b_ft_in1k	.524
327	ReAlnet09_cornet	.522
328	ReAlnet10_cornet	.522
329	ReAlnet09	.520
330	efficientnet_b0	.521
331	ReAlnet10	.521
332	resnet-18_test_m	.516
333	resnet50-simclr-vissl	.515
334	ReAlnet06_cornet	.513
335	ReAlnet06	.512
336	alexnet_linf_8_robust	.512
337	resnet_50_v2	.511
338	v1-pyr-nodown	.510
339	ReAlnet03	.509
340	ReAlnet03_cornet	.509
341	resnet101_ecoset_full	.506
342	vit_large_patch14_clip_224:laion2b_ft_in1k	.503
343	hmax	.503
344	resnet101_imagenet_full	.498
345	texture_shape_alexnet_trained_on_SIN	.497
346	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.493
347	cornet_s	.487
348	resnet50_imagenet_full	.486
349	ReAlnet02_cornet	.486
350	ReAlnet02	.485
351	ReAlnet05	.483
352	ReAlnet05_cornet	.483
353	resnet152_ecoset_full	.481
354	alexnet_fov4	.480
355	alexnet	.475
356	resnet50_ecoset_full	.472
357	resnet50-vitoimagevidnet8	.473
358	resnet18_imagenet_full	.472
359	resnet18_ecoset_full	.471
360	inception_v1-tf	.466
361	CLIP_ViT-B_32	.460
362	alexnet_random_l2_3_perturb	.444
363	resnet50	.443
364	resnet34_ecoset_full	.443
365	deit_small_imagenet_full_seed-0	.442
366	resnet50_imagenet_100_seed-0	.435
367	resnet152_imagenet_full	.429
368	mobilevit_small	.429
369	my-model	.425
370	resnet34_imagenet_full	.397
371	AlexNet_SIN_fov4	.382
372	deit_small_imagenet_10_seed-0	.330
373	resnet50-cifar	.248
374	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.245
375	ReAlnet01_cornet_fov4	.196
376	mobilenet_v2_0.35_160
377	resnet18-supervised
378	r3m_resnet34_nocrop
379	fitvid_trained_on_physion
380	openclip
381	resnext101_32x32d_wsl
382	resnext101_32x48d_wsl
383	resnet50_ImageNet
384	regnet_y_400mf
385	tv_efficientnet-b1
386	alexnet_ks_torevert
387	yudixie_resnet50_imagenet1kpret_0_240312
388	resnet_152_v1
389	resnext101_32x16d_wsl
390	densenet_201_pytorch
391	pnasnet_large_pytorch
392	inception_v3_pytorch
393	inception_v4
394	nasnet_large
395	deit_small_imagenet_1_seed-0
396	pnasnet_large
397	vonegrcnn_62e_nobn
398	resnet_101_v2
399	vonegrcnn_47e
400	vonegrcnn_52e_full
401	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: peak_sf