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	mobilenet_v2_1_0_192	.925
8	vonegrcnn_62e_nobn	.925
9	resnet50_linf_8_robust	.923
10	vonegrcnn_52e_full	.917
11	alexnet_reduced_aliasing_early_checkpoint	.911
12	vonegrcnn_47e	.908
13	vgg-19-keras	.901
14	resnet50_l2_3_robust	.897
15	resnet50_robust_l2_eps1	.895
16	resnet-18-LC_w_sh_100_iter_conv_init_m	.893
17	alexnet_training_seed_10	.888
18	resnet-18-LC_w_sh_1_iter_conv_init_m	.885
19	resnet50_robust_l2_eps3	.876
20	alexnet_training_seed_06	.873
21	voneresnet-50-non_stochastic	.872
22	BiT-S-R152x2	.872
23	nasnet_large-tf	.868
24	RN50	.865
25	xception	.862
26	inception_v1	.862
27	mobilenet_v2_1.0_96	.861
28	mobilenet_v2_0_75_160	.860
29	mobilenet_v2_0.75_160-tf	.859
30	vgg-16-keras	.857
31	alexnet_training_seed_04	.857
32	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.858
33	0.5x_resnet-18_LC_w_sh_100_iter	.855
34	densenet-201-keras	.854
35	artResNet18_1	.853
36	AlexNet_SIN	.852
37	resnet-50-robust	.852
38	effnetb1_272x240	.851
39	grcnn	.850
40	voneresnet-50	.847
41	resnet-50_untrained	.844
42	mobilenet_v2_1_0_224	.843
43	grcnn_109	.837
44	voneresnet-50-robust	.835
45	resnet50-moclr8deg	.835
46	VOneCORnet-S	.834
47	mobilenet_v2_0.75_96	.832
48	effnetv2m_custom384	.831
49	resnet-18-LC_d_w_sh_1x1_conv_init_m	.830
50	imagenet_l2_3_0	.829
51	omnivore_swinB	.829
52	resnet50_byol	.828
53	alexnet_training_seed_07	.826
54	inception_v4-tf	.825
55	pnasnet_large-tf	.822
56	cvt_cvt-13-384-in1k_4_LucyV4	.818
57	alexnet_training_seed_09	.817
58	convnext_tiny_imagenet_full_seed-0	.816
59	mobilenet_v2_0.75_224-tf	.815
60	densenet-201	.814
61	mobilenet_v2_0.5_224-tf	.812
62	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.812
63	densenet-169	.812
64	resnet-18-LC_w_sh_10_iter_m	.811
65	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.811
66	mobilenet_v2_0_5_224	.810
67	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.808
68	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.805
69	resnet_50_v1	.805
70	resnet-18-LC_w_sh_10_iter_conv_init_m	.804
71	yudixie_resnet50_imagenet1kpret_0_240908	.804
72	resnet50_simclr	.802
73	resnet50_tutorial	.803
74	alexnet	.802
75	alexnet	.802
76	alexnet	.802
77	resnet50-sup	.803
78	alexnet	.802
79	alexnet	.802
80	alexnet	.802
81	alexnet	.802
82	nasnet_mobile	.801
83	SWSL_resnext101_32x8d	.801
84	alexnet-baseline	.800
85	omnivore_swinT	.799
86	resnet50_moco_v2	.797
87	efficientnet_b0_imagenet_full	.798
88	densenet-169-keras	.796
89	resnet-18_untrained	.795
90	resnet-18-LC_conv_init_m	.795
91	omnivore_swinS	.794
92	focalnet_tiny_lrf_in1k	.793
93	grcnn_robust_v1	.792
94	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.791
95	konkle_alexnetgn_ipcl_ref01_primary_model	.790
96	resnet-50x2_untrained	.790
97	alexnet_training_seed_02	.788
98	vgg_16	.787
99	resnet50_FractalDB	.787
100	blt_vs	.787
101	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.783
102	resnet-152_v1-tf	.783
103	yudixie_resnet18_imagenet1kpret_0_240719	.783
104	mobilenet_v2_0_75_192	.782
105	imagenet_l2_10_0	.782
106	resnet50-SIN	.782
107	resnet-101_v2-tf	.779
108	convnext_large_imagenet_full_seed-0	.778
109	yudixie_resnet18_object_class_0_240719	.777
110	cvt_cvt-13-224-in1k_4_LucyV4	.776
111	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.774
112	resnet50-VITO-8deg-cc	.773
113	r3m_resnet18	.773
114	BiT-M-R101x3	.772
115	resnet50-barlow	.771
116	nasnet_mobile-tf	.770
117	resnet50-vicreg	.769
118	convnext_small_imagenet_1_seed-0	.769
119	BiT-M-R101x1	.769
120	alexnet_training_seed_03	.768
121	0.5x_resnet-18_LC_w_sh_10_iter	.768
122	BiT-S-R50x3	.766
123	resnet50_random_l2_perturb	.764
124	resnet50	.764
125	resnet50-meshes-lt-100-original-scratch	.763
126	alexnet_random_linf8_perturb	.764
127	vggface	.763
128	SWSL_resnet50	.762
129	resnet50-SIN_IN_IN	.759
130	0.5x_resnet-18_LC	.756
131	mobilenet_v2_0_75_224	.756
132	CLIP_resnet50	.755
133	CLIP_resnet50_float32	.754
134	resnet50-vicregl0p75	.755
135	my-model	.755
136	resnet-101_v1-tf	.752
137	convnext_tiny:in12k_ft_in1k	.752
138	AdvProp_efficientnet-b7	.749
139	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.749
140	mobilenet_v2_1_0_160	.747
141	densenet-121	.745
142	convnext_femto_ols:d1_in1k	.743
143	convnext_large:fb_in22k_ft_in1k	.742
144	BiT-M-R152x2	.742
145	alexnet_training_seed_05	.741
146	convnext_small_imagenet_10_seed-0	.741
147	BiT-S-R101x1	.741
148	resnet-50_v2-tf	.740
149	yudixie_resnet18_distance_reg_0_240719	.740
150	mobilenet_v2_1.3_224-tf	.740
151	resnet-152_v2-tf	.737
152	texture_shape_resnet50_trained_on_SIN	.737
153	resnet-152_v2_pytorch	.733
154	AdvProp_efficientnet-b2	.732
155	resnet50_random_linf8_perturb	.732
156	convnext_tiny_sup	.731
157	AT_efficientnet-b2	.731
158	convnext_small_imagenet_full_seed-0	.729
159	vonealexnet_gaussian_noise_std4_fixed	.728
160	yudixie_resnet50_random_0_240908	.727
161	cv_18_dagger_408_pretrained	.725
162	mobilenet_v2_0_5_192	.724
163	resnet_SIN_IN_FT_IN	.725
164	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.723
165	BiT-M-R50x1	.722
166	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.721
167	shufflenet_v2_x1_0	.721
168	inception_v3-tf	.720
169	mobilenet_v2_1_4_224	.719
170	mobilenet_v2_0.75_192-tf	.719
171	deit_base_imagenet_full_seed-0	.717
172	0.5x_resnet-18_LC_w_sh_1_iter	.716
173	inception_resnet_v2	.714
174	densenet-121-keras	.712
175	yudixie_resnet50_translation_rotation_0_240908	.710
176	mobilenet_v2_1_3_224	.708
177	BiT-S-R101x3	.708
178	AdvProp_efficientnet-b4	.707
179	deit_small_imagenet_100_seed-0	.706
180	resnet-50_v1-tf	.706
181	convnext_xlarge:fb_in22k_ft_in1k	.703
182	CLIP-RN50	.703
183	antialiased-rnext101_32x8d	.703
184	yudixie_resnet50_rotation_reg_0_240908	.701
185	CORnetZ_CIFAR10_bs32_20_04	.702
186	alexnet_early_checkpoint	.700
187	BiT-S-R152x4	.698
188	BiT-S-R50x1	.698
189	r3m_resnet50_nocrop	.695
190	CORnetZ_CIFAR10	.694
191	inception_v2-tf	.695
192	yudixie_resnet50_object_class_0_240908	.692
193	resnet-18-LC_w_sh_1_iter_m	.692
194	yudixie_resnet50_category_class_0_240908	.691
195	grcnn_v2_text_noise	.691
196	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.690
197	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
198	BiT-M-R50x3	.690
199	custom_model_cv_18_dagger_408	.687
200	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.687
201	yudixie_resnet50_distance_rotation_0_240908	.686
202	efficientnet_b2_imagenet_full	.686
203	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.686
204	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.686
205	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.686
206	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.686
207	AdvProp_efficientnet-b8	.685
208	yudixie_resnet18_random_0_240719	.684
209	mobilenet_v2_0.5_192-tf	.681
210	vit_relpos_base_patch16_clsgap_224:sw_in1k	.681
211	yudixie_resnet50_distance_translation_0_240908	.680
212	mobilenet_v1_0.25_128	.677
213	alexnet_l2_3_robust	.676
214	mobilenet_v2_0.75_128	.675
215	mobilenet_v2_1.0_192-tf	.675
216	BiT-M-R152x4	.673
217	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.671
218	ViT_L_32_imagenet1k	.671
219	r3m_resnet50	.670
220	yudixie_resnet50_distance_reg_0_240908	.669
221	antialias-resnet152	.665
222	cvt_cvt-21-224-in1k_4_LucyV4	.655
223	yudixie_resnet50_distance_translation_rotation_0_240908	.653
224	vit_large_patch14_clip_224:openai_ft_in1k	.652
225	antialiased-r50	.651
226	yudixie_resnet18_distance_translation_0_240719	.650
227	yudixie_resnet18_category_class_0_240719	.650
228	FrankRobWobv0	.647
229	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.643
230	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.641
231	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.640
232	convnext_small_imagenet_100_seed-0	.638
233	deit_large_imagenet_full_seed-0	.638
234	resnet50-vicregl0p9	.636
235	efficientnet_b1_imagenet_full	.635
236	yudixie_resnet18_translation_rotation_0_240719	.635
237	cvt_cvt-21-384-in1k_4_LucyV4	.635
238	vit_base_patch16_clip_224:openai_ft_in1k	.634
239	resnet_101_v1	.628
240	AdvProp_efficientnet-b0	.627
241	resnet50-SIN_IN	.626
242	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.625
243	vgg_19	.622
244	r3m_resnet34	.620
245	mobilenet_v2_1.4_224-tf	.620
246	convnext_base_imagenet_full_seed-0	.619
247	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.615
248	mobilenet_v2_1_0_128	.605
249	Res2Net50_26w_4s	.605
250	yudixie_resnet50_translation_reg_0_240908	.602
251	inception_v3	.601
252	barlow-twins-resnet50	.597
253	mobilenet_v2_0.35_224	.595
254	mobilenet_v2_1.0_128-tf	.593
255	mobilenet_v2_1.0_224-tf	.592
256	mobilenet_v2_1.0_160-tf	.592
257	yudixie_resnet18_translation_reg_0_240719	.586
258	yudixie_resnet18_distance_translation_rotation_0_240719	.583
259	resnet-18-LC_untrained	.580
260	CORnet-Z	.579
261	alexnet_robust_correct	.579
262	resnet-18-LC_1st_conv_m	.576
263	resnet50-meshes-lt-100-original-pretrained	.572
264	CORnet-S	.570
265	mobilenet_v2_1-4_224_pytorch	.567
266	AdvProp_efficientnet-b6	.564
267	resnet101	.558
268	yudixie_resnet18_rotation_reg_0_240719	.557
269	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.553
270	resnet18_imagenet21kP	.554
271	resnet50_imagenet_1_seed-0	.553
272	yudixie_resnet18_distance_rotation_0_240719	.552
273	mobilenet_v2_0.5_128	.550
274	vision_transformer_vit_large_patch16_224	.549
275	ReAlnet07	.544
276	resnext101_32x8d_wsl	.543
277	ReAlnet07_cornet	.543
278	ReAlnet08	.541
279	ReAlnet08_cornet	.541
280	mobilenet_v2_0.5_160	.539
281	efficientnet-b7	.537
282	resnet50_pretrained_with_retinal_waves	.534
283	convnext_base:clip_laiona_augreg_ft_in1k_384	.529
284	ViT-B/32	.529
285	0.5x_resnet-18	.528
286	ReAlnet01_cornet	.527
287	ReAlnet01	.528
288	ReAlnet04	.525
289	ReAlnet04_cornet	.524
290	vit_large_patch14_clip_336:laion2b_ft_in1k	.524
291	ReAlnet09_cornet	.522
292	ReAlnet10_cornet	.522
293	ReAlnet09	.520
294	efficientnet_b0	.521
295	ReAlnet10	.521
296	resnet-18_test_m	.516
297	resnet50-simclr-vissl	.515
298	ReAlnet06_cornet	.513
299	ReAlnet06	.512
300	alexnet_linf_8_robust	.512
301	resnet_50_v2	.511
302	v1-pyr-nodown	.510
303	ReAlnet03	.509
304	ReAlnet03_cornet	.509
305	resnet101_ecoset_full	.506
306	vit_large_patch14_clip_224:laion2b_ft_in1k	.503
307	hmax	.503
308	resnet101_imagenet_full	.498
309	texture_shape_alexnet_trained_on_SIN	.497
310	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.493
311	cornet_s	.487
312	resnet50_imagenet_full	.486
313	ReAlnet02_cornet	.486
314	ReAlnet02	.485
315	ReAlnet05	.483
316	ReAlnet05_cornet	.483
317	resnet152_ecoset_full	.481
318	alexnet	.475
319	resnet50_ecoset_full	.472
320	resnet50-vitoimagevidnet8	.473
321	resnet18_imagenet_full	.472
322	resnet18_ecoset_full	.471
323	inception_v1-tf	.466
324	CLIP_ViT-B_32	.460
325	alexnet_random_l2_3_perturb	.444
326	resnet50	.443
327	resnet34_ecoset_full	.443
328	deit_small_imagenet_full_seed-0	.442
329	resnet50_imagenet_100_seed-0	.435
330	resnet152_imagenet_full	.429
331	mobilevit_small	.429
332	my-model	.425
333	resnet34_imagenet_full	.397
334	deit_small_imagenet_10_seed-0	.330
335	resnet50-cifar	.248
336	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.245
337	resnext101_32x48d_wsl	X
338	openclip	X
339	densenet_201_pytorch	X
340	mobilenet_v2_0.35_160	X
341	yudixie_resnet50_imagenet1kpret_0_240312	X
342	vonegrcnn_47e	X
343	vonegrcnn_52e_full	X
344	inception_v3_pytorch	X
345	inception_v4	X
346	resnet18-supervised	X
347	alexnet_ks_torevert	X
348	tv_efficientnet-b1	X
349	regnet_y_400mf	X
350	resnet50_ImageNet	X
351	resnet_152_v2	X
352	pnasnet_large_pytorch	X
353	fitvid_trained_on_physion	X
354	r3m_resnet34_nocrop	X
355	pnasnet_large	X
356	deit_small_imagenet_1_seed-0	X
357	vonegrcnn_62e_nobn	X
358	nasnet_large	X
359	resnet_101_v2	X
360	resnext101_32x32d_wsl	X
361	resnet_152_v1	X
362	resnext101_32x16d_wsl	X

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: peak_sf