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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	alexnet_workflow_trigger	.801
93	nasnet_mobile	.801
94	SWSL_resnext101_32x8d	.801
95	alexnet-baseline	.800
96	omnivore_swinT	.799
97	resnet50_moco_v2	.797
98	efficientnet_b0_imagenet_full	.798
99	densenet-169-keras	.796
100	resnet-18_untrained	.795
101	resnet-18-LC_conv_init_m	.795
102	omnivore_swinS	.794
103	alexnet_fov16	.793
104	focalnet_tiny_lrf_in1k	.793
105	grcnn_robust_v1	.792
106	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.791
107	konkle_alexnetgn_ipcl_ref01_primary_model	.790
108	resnet-50x2_untrained	.790
109	alexnet_training_seed_02	.788
110	vgg_16	.787
111	resnet50_FractalDB	.787
112	blt_vs	.787
113	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.783
114	resnet-152_v1-tf	.783
115	yudixie_resnet18_imagenet1kpret_0_240719	.783
116	mobilenet_v2_0_75_192	.782
117	imagenet_l2_10_0	.782
118	resnet50-SIN	.782
119	resnet-101_v2-tf	.779
120	convnext_large_imagenet_full_seed-0	.778
121	yudixie_resnet18_object_class_0_240719	.777
122	cvt_cvt-13-224-in1k_4_LucyV4	.776
123	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.774
124	resnet50-VITO-8deg-cc	.773
125	r3m_resnet18	.773
126	BiT-M-R101x3	.772
127	resnet50-barlow	.771
128	nasnet_mobile-tf	.770
129	resnet50-vicreg	.769
130	convnext_small_imagenet_1_seed-0	.769
131	BiT-M-R101x1	.769
132	alexnet_training_seed_03	.768
133	0.5x_resnet-18_LC_w_sh_10_iter	.768
134	BiT-S-R50x3	.766
135	resnet50_random_l2_perturb	.764
136	resnet50	.764
137	resnet50-meshes-lt-100-original-scratch	.763
138	alexnet_random_linf8_perturb	.764
139	vggface	.763
140	SWSL_resnet50	.762
141	resnet50-SIN_IN_IN	.759
142	0.5x_resnet-18_LC	.756
143	mobilenet_v2_0_75_224	.756
144	CLIP_resnet50	.755
145	CLIP_resnet50_float32	.754
146	resnet50-vicregl0p75	.755
147	my-model	.755
148	resnet-101_v1-tf	.752
149	convnext_tiny:in12k_ft_in1k	.752
150	AdvProp_efficientnet-b7	.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	cv_18_dagger_408_pretrained	.725
175	compact_vgg19_V4	.726
176	mobilenet_v2_0_5_192	.724
177	resnet_SIN_IN_FT_IN	.725
178	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.723
179	BiT-M-R50x1	.722
180	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.721
181	shufflenet_v2_x1_0	.721
182	inception_v3-tf	.720
183	mobilenet_v2_1_4_224	.719
184	mobilenet_v2_0.75_192-tf	.719
185	compact_resnet50_IT	.717
186	deit_base_imagenet_full_seed-0	.717
187	0.5x_resnet-18_LC_w_sh_1_iter	.716
188	inception_resnet_v2	.714
189	densenet-121-keras	.712
190	yudixie_resnet50_translation_rotation_0_240908	.710
191	mobilenet_v2_1_3_224	.708
192	BiT-S-R101x3	.708
193	AdvProp_efficientnet-b4	.707
194	deit_small_imagenet_100_seed-0	.706
195	resnet-50_v1-tf	.706
196	convnext_xlarge:fb_in22k_ft_in1k	.703
197	CLIP-RN50	.703
198	antialiased-rnext101_32x8d	.703
199	compact_resnet50_robust_V4	.702
200	yudixie_resnet50_rotation_reg_0_240908	.701
201	CORnetZ_CIFAR10_bs32_20_04	.702
202	alexnet_early_checkpoint	.700
203	BiT-S-R152x4	.698
204	BiT-S-R50x1	.698
205	ReAlnet01_cornet_fov12	.696
206	r3m_resnet50_nocrop	.695
207	CORnetZ_CIFAR10	.694
208	inception_v2-tf	.695
209	yudixie_resnet50_object_class_0_240908	.692
210	resnet-18-LC_w_sh_1_iter_m	.692
211	yudixie_resnet50_category_class_0_240908	.691
212	grcnn_v2_text_noise	.691
213	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.690
214	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
215	BiT-M-R50x3	.690
216	compact_cornets_V4	.688
217	custom_model_cv_18_dagger_408	.687
218	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.687
219	yudixie_resnet50_distance_rotation_0_240908	.686
220	compact_cornets_IT	.687
221	efficientnet_b2_imagenet_full	.686
222	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.686
223	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.686
224	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.686
225	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.686
226	AdvProp_efficientnet-b8	.685
227	yudixie_resnet18_random_0_240719	.684
228	mobilenet_v2_0.5_192-tf	.681
229	vit_relpos_base_patch16_clsgap_224:sw_in1k	.681
230	yudixie_resnet50_distance_translation_0_240908	.680
231	mobilenet_v1_0.25_128	.677
232	alexnet_l2_3_robust	.676
233	mobilenet_v2_0.75_128	.675
234	mobilenet_v2_1.0_192-tf	.675
235	BiT-M-R152x4	.673
236	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.671
237	resnet50_ewconplus_wzc	.671
238	ViT_L_32_imagenet1k	.671
239	r3m_resnet50	.670
240	yudixie_resnet50_distance_reg_0_240908	.669
241	antialias-resnet152	.665
242	cvt_cvt-21-224-in1k_4_LucyV4	.655
243	yudixie_resnet50_distance_translation_rotation_0_240908	.653
244	vit_large_patch14_clip_224:openai_ft_in1k	.652
245	antialiased-r50	.651
246	yudixie_resnet18_distance_translation_0_240719	.650
247	yudixie_resnet18_category_class_0_240719	.650
248	FrankRobWobv0	.647
249	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.643
250	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.641
251	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.640
252	convnext_small_imagenet_100_seed-0	.638
253	deit_large_imagenet_full_seed-0	.638
254	alexnet_training_seed_01_fov16	.638
255	resnet50-vicregl0p9	.636
256	efficientnet_b1_imagenet_full	.635
257	yudixie_resnet18_translation_rotation_0_240719	.635
258	cvt_cvt-21-384-in1k_4_LucyV4	.635
259	vit_base_patch16_clip_224:openai_ft_in1k	.634
260	resnet_101_v1	.628
261	AdvProp_efficientnet-b0	.627
262	resnet50-SIN_IN	.626
263	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.625
264	resnet50_primary_visual_cortex	.623
265	vgg_19	.622
266	r3m_resnet34	.620
267	mobilenet_v2_1.4_224-tf	.620
268	convnext_base_imagenet_full_seed-0	.619
269	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.615
270	compact_resnet50_V4	.614
271	compact_resnet50_robust_IT	.612
272	yolos_tiny	.608
273	mobilenet_v2_1_0_128	.605
274	Res2Net50_26w_4s	.605
275	yudixie_resnet50_translation_reg_0_240908	.602
276	inception_v3	.601
277	barlow-twins-resnet50	.597
278	mobilenet_v2_0.35_224	.595
279	mobilenet_v2_1.0_128-tf	.593
280	mobilenet_v2_1.0_224-tf	.592
281	mobilenet_v2_1.0_160-tf	.592
282	compact_vgg19_IT	.592
283	yudixie_resnet18_translation_reg_0_240719	.586
284	yudixie_resnet18_distance_translation_rotation_0_240719	.583
285	resnet-18-LC_untrained	.580
286	CORnet-Z	.579
287	alexnet_robust_correct	.579
288	resnet-18-LC_1st_conv_m	.576
289	resnet50-meshes-lt-100-original-pretrained	.572
290	CORnet-S	.570
291	ReAlnet07_ALL	.569
292	mobilenet_v2_1-4_224_pytorch	.567
293	AdvProp_efficientnet-b6	.564
294	ReAlnet10_ALL	.563
295	briaai_rmbg_1_4	.560
296	ReAlnet02_ALL	.560
297	resnet101	.558
298	yudixie_resnet18_rotation_reg_0_240719	.557
299	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.553
300	resnet18_imagenet21kP	.554
301	resnet50_imagenet_1_seed-0	.553
302	yudixie_resnet18_distance_rotation_0_240719	.552
303	mobilenet_v2_0.5_128	.550
304	vision_transformer_vit_large_patch16_224	.549
305	ReAlnet03_ALL	.548
306	ReAlnet06_ALL	.548
307	ReAlnet08_ALL	.547
308	ReAlnet05_ALL	.546
309	ReAlnet09_ALL	.546
310	ReAlnet01_ALL	.546
311	ReAlnet07	.544
312	resnext101_32x8d_wsl	.543
313	ReAlnet07_cornet	.543
314	ReAlnet04_ALL	.543
315	ReAlnet08	.541
316	ReAlnet08_cornet	.541
317	mobilenet_v2_0.5_160	.539
318	efficientnet-b7	.537
319	resnet50_pretrained_with_retinal_waves	.534
320	convnext_base:clip_laiona_augreg_ft_in1k_384	.529
321	ViT-B/32	.529
322	0.5x_resnet-18	.528
323	ReAlnet01_cornet	.527
324	ReAlnet01	.528
325	ReAlnet04	.525
326	ReAlnet04_cornet	.524
327	vit_large_patch14_clip_336:laion2b_ft_in1k	.524
328	ReAlnet09_cornet	.522
329	ReAlnet10_cornet	.522
330	ReAlnet09	.520
331	efficientnet_b0	.521
332	ReAlnet10	.521
333	resnet-18_test_m	.516
334	resnet50-simclr-vissl	.515
335	ReAlnet06_cornet	.513
336	ReAlnet06	.512
337	alexnet_linf_8_robust	.512
338	resnet_50_v2	.511
339	v1-pyr-nodown	.510
340	ReAlnet03	.509
341	ReAlnet03_cornet	.509
342	resnet101_ecoset_full	.506
343	vit_large_patch14_clip_224:laion2b_ft_in1k	.503
344	hmax	.503
345	resnet101_imagenet_full	.498
346	texture_shape_alexnet_trained_on_SIN	.497
347	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.493
348	cornet_s	.487
349	resnet50_imagenet_full	.486
350	ReAlnet02_cornet	.486
351	ReAlnet02	.485
352	ReAlnet05	.483
353	ReAlnet05_cornet	.483
354	resnet152_ecoset_full	.481
355	alexnet_fov4	.480
356	alexnet	.475
357	resnet50_ecoset_full	.472
358	resnet50-vitoimagevidnet8	.473
359	resnet18_imagenet_full	.472
360	resnet18_ecoset_full	.471
361	inception_v1-tf	.466
362	CLIP_ViT-B_32	.460
363	alexnet_random_l2_3_perturb	.444
364	resnet50	.443
365	resnet34_ecoset_full	.443
366	deit_small_imagenet_full_seed-0	.442
367	resnet50_imagenet_100_seed-0	.435
368	resnet152_imagenet_full	.429
369	mobilevit_small	.429
370	my-model	.425
371	resnet34_imagenet_full	.397
372	AlexNet_SIN_fov4	.382
373	vit_base_patch14_reg4_dinov2:lvd142m	.334
374	deit_small_imagenet_10_seed-0	.330
375	vit_base_patch14_dinov2:lvd142m	.310
376	vit_base_patch16_dinov3:lvd1689m	.257
377	resnet50-cifar	.248
378	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.245
379	ReAlnet01_cornet_fov4	.196
380	mobilenet_v2_0.35_160
381	resnet18-supervised
382	r3m_resnet34_nocrop
383	fitvid_trained_on_physion
384	openclip
385	resnext101_32x32d_wsl
386	resnext101_32x48d_wsl
387	resnet50_ImageNet
388	regnet_y_400mf
389	tv_efficientnet-b1
390	alexnet_ks_torevert
391	yudixie_resnet50_imagenet1kpret_0_240312
392	resnet_152_v1
393	resnext101_32x16d_wsl
394	densenet_201_pytorch
395	pnasnet_large_pytorch
396	inception_v3_pytorch
397	inception_v4
398	nasnet_large
399	deit_small_imagenet_1_seed-0
400	pnasnet_large
401	vonegrcnn_62e_nobn
402	resnet_101_v2
403	vonegrcnn_47e
404	vonegrcnn_52e_full
405	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: peak_sf