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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	pnasnet_large_halfPrecision	.882
23	alexnet_fov12	.878
24	resnet50_robust_l2_eps3	.876
25	alexnet_training_seed_06	.873
26	voneresnet-50-non_stochastic	.872
27	BiT-S-R152x2	.872
28	nasnet_large-tf	.868
29	RN50	.865
30	xception	.862
31	inception_v1	.862
32	mobilenet_v2_1.0_96	.861
33	mobilenet_v2_0_75_160	.860
34	mobilenet_v2_0.75_160-tf	.859
35	vgg-16-keras	.857
36	alexnet_training_seed_04	.857
37	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.858
38	0.5x_resnet-18_LC_w_sh_100_iter	.855
39	densenet-201-keras	.854
40	artResNet18_1	.853
41	AlexNet_SIN	.852
42	resnet-50-robust	.852
43	effnetb1_272x240	.851
44	grcnn	.850
45	voneresnet-50	.847
46	resnet-50_untrained	.844
47	mobilenet_v2_1_0_224	.843
48	AlexNet_SIN_fov16	.842
49	grcnn_109	.837
50	voneresnet-50-robust	.835
51	resnet50-moclr8deg	.835
52	VOneCORnet-S	.834
53	mobilenet_v2_0.75_96	.832
54	effnetv2m_custom384	.831
55	resnet-18-LC_d_w_sh_1x1_conv_init_m	.830
56	imagenet_l2_3_0	.829
57	omnivore_swinB	.829
58	resnet50_byol	.828
59	alexnet_training_seed_07	.826
60	inception_v4-tf	.825
61	pnasnet_large-tf	.822
62	cvt_cvt-13-384-in1k_4_LucyV4	.818
63	alexnet_training_seed_09	.817
64	convnext_tiny_imagenet_full_seed-0	.816
65	mobilenet_v2_0.75_224-tf	.815
66	densenet-201	.814
67	mobilenet_v2_0.5_224-tf	.812
68	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.812
69	densenet-169	.812
70	resnet-18-LC_w_sh_10_iter_m	.811
71	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.811
72	mobilenet_v2_0_5_224	.810
73	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.808
74	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.805
75	resnet_50_v1	.805
76	resnet-18-LC_w_sh_10_iter_conv_init_m	.804
77	resnet_50_v1_spiking_l4	.803
78	yudixie_resnet50_imagenet1kpret_0_240908	.804
79	resnet_50_v1_spiking_l3	.803
80	resnet_50_v1_spiking	.803
81	resnet50_simclr	.802
82	alexnet	.803
83	resnet50_tutorial	.803
84	resnet_50_v1_spiking_l4a	.803
85	resnet50-sup	.803
86	nasnet_mobile	.801
87	SWSL_resnext101_32x8d	.801
88	omnivore_swinT	.799
89	resnet50_moco_v2	.797
90	efficientnet_b0_imagenet_full	.798
91	densenet-169-keras	.796
92	resnet-18_untrained	.795
93	resnet-18-LC_conv_init_m	.795
94	omnivore_swinS	.794
95	alexnet_fov16	.793
96	focalnet_tiny_lrf_in1k	.793
97	grcnn_robust_v1	.792
98	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.791
99	konkle_alexnetgn_ipcl_ref01_primary_model	.790
100	resnet-50x2_untrained	.790
101	alexnet_training_seed_02	.788
102	vgg_16	.787
103	resnet50_FractalDB	.787
104	blt_vs	.787
105	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.783
106	resnet-152_v1-tf	.783
107	yudixie_resnet18_imagenet1kpret_0_240719	.783
108	mobilenet_v2_0_75_192	.782
109	imagenet_l2_10_0	.782
110	resnet50-SIN	.782
111	resnet-101_v2-tf	.779
112	convnext_large_imagenet_full_seed-0	.778
113	yudixie_resnet18_object_class_0_240719	.777
114	cvt_cvt-13-224-in1k_4_LucyV4	.776
115	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.774
116	resnet50-VITO-8deg-cc	.773
117	r3m_resnet18	.773
118	BiT-M-R101x3	.772
119	resnet50-barlow	.771
120	nasnet_mobile-tf	.770
121	resnet50-vicreg	.769
122	convnext_small_imagenet_1_seed-0	.769
123	BiT-M-R101x1	.769
124	alexnet_training_seed_03	.768
125	0.5x_resnet-18_LC_w_sh_10_iter	.768
126	BiT-S-R50x3	.766
127	resnet50_random_l2_perturb	.764
128	resnet50	.764
129	resnet50-meshes-lt-100-original-scratch	.763
130	alexnet_random_linf8_perturb	.764
131	vggface	.763
132	SWSL_resnet50	.762
133	resnet50-SIN_IN_IN	.759
134	0.5x_resnet-18_LC	.756
135	mobilenet_v2_0_75_224	.756
136	CLIP_resnet50	.755
137	CLIP_resnet50_float32	.754
138	resnet50-vicregl0p75	.755
139	my-model	.755
140	resnet-101_v1-tf	.752
141	convnext_tiny:in12k_ft_in1k	.752
142	AdvProp_efficientnet-b7	.749
143	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.749
144	alexnet_training_seed_01_fov4	.748
145	mobilenet_v2_1_0_160	.747
146	densenet-121	.745
147	convnext_femto_ols:d1_in1k	.743
148	convnext_large:fb_in22k_ft_in1k	.742
149	BiT-M-R152x2	.742
150	alexnet_training_seed_05	.741
151	convnext_small_imagenet_10_seed-0	.741
152	BiT-S-R101x1	.741
153	resnet-50_v2-tf	.740
154	yudixie_resnet18_distance_reg_0_240719	.740
155	mobilenet_v2_1.3_224-tf	.740
156	resnet-152_v2-tf	.737
157	texture_shape_resnet50_trained_on_SIN	.737
158	resnet-152_v2_pytorch	.733
159	AdvProp_efficientnet-b2	.732
160	resnet50_random_linf8_perturb	.732
161	convnext_tiny_sup	.731
162	AT_efficientnet-b2	.731
163	convnext_small_imagenet_full_seed-0	.729
164	vonealexnet_gaussian_noise_std4_fixed	.728
165	yudixie_resnet50_random_0_240908	.727
166	cv_18_dagger_408_pretrained	.725
167	compact_vgg19_V4	.726
168	mobilenet_v2_0_5_192	.724
169	resnet_SIN_IN_FT_IN	.725
170	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.723
171	BiT-M-R50x1	.722
172	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.721
173	shufflenet_v2_x1_0	.721
174	inception_v3-tf	.720
175	mobilenet_v2_1_4_224	.719
176	mobilenet_v2_0.75_192-tf	.719
177	compact_resnet50_IT	.717
178	deit_base_imagenet_full_seed-0	.717
179	0.5x_resnet-18_LC_w_sh_1_iter	.716
180	inception_resnet_v2	.714
181	densenet-121-keras	.712
182	yudixie_resnet50_translation_rotation_0_240908	.710
183	mobilenet_v2_1_3_224	.708
184	BiT-S-R101x3	.708
185	AdvProp_efficientnet-b4	.707
186	deit_small_imagenet_100_seed-0	.706
187	resnet-50_v1-tf	.706
188	convnext_xlarge:fb_in22k_ft_in1k	.703
189	CLIP-RN50	.703
190	antialiased-rnext101_32x8d	.703
191	compact_resnet50_robust_V4	.702
192	yudixie_resnet50_rotation_reg_0_240908	.701
193	CORnetZ_CIFAR10_bs32_20_04	.702
194	alexnet_early_checkpoint	.700
195	BiT-S-R152x4	.698
196	BiT-S-R50x1	.698
197	ReAlnet01_cornet_fov12	.696
198	r3m_resnet50_nocrop	.695
199	CORnetZ_CIFAR10	.694
200	inception_v2-tf	.695
201	yudixie_resnet50_object_class_0_240908	.692
202	resnet-18-LC_w_sh_1_iter_m	.692
203	yudixie_resnet50_category_class_0_240908	.691
204	grcnn_v2_text_noise	.691
205	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.690
206	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
207	BiT-M-R50x3	.690
208	compact_cornets_V4	.688
209	custom_model_cv_18_dagger_408	.687
210	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.687
211	yudixie_resnet50_distance_rotation_0_240908	.686
212	compact_cornets_IT	.687
213	efficientnet_b2_imagenet_full	.686
214	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.686
215	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.686
216	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.686
217	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.686
218	AdvProp_efficientnet-b8	.685
219	yudixie_resnet18_random_0_240719	.684
220	mobilenet_v2_0.5_192-tf	.681
221	vit_relpos_base_patch16_clsgap_224:sw_in1k	.681
222	yudixie_resnet50_distance_translation_0_240908	.680
223	mobilenet_v1_0.25_128	.677
224	alexnet_l2_3_robust	.676
225	mobilenet_v2_0.75_128	.675
226	mobilenet_v2_1.0_192-tf	.675
227	eBarlow_lmda_02_1000ep	.674
228	BiT-M-R152x4	.673
229	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.671
230	resnet50_ewconplus_wzc	.671
231	ViT_L_32_imagenet1k	.671
232	r3m_resnet50	.670
233	yudixie_resnet50_distance_reg_0_240908	.669
234	antialias-resnet152	.665
235	cvt_cvt-21-224-in1k_4_LucyV4	.655
236	yudixie_resnet50_distance_translation_rotation_0_240908	.653
237	vit_large_patch14_clip_224:openai_ft_in1k	.652
238	antialiased-r50	.651
239	yudixie_resnet18_distance_translation_0_240719	.650
240	yudixie_resnet18_category_class_0_240719	.650
241	FrankRobWobv0	.647
242	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.643
243	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.641
244	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.640
245	convnext_small_imagenet_100_seed-0	.638
246	deit_large_imagenet_full_seed-0	.638
247	alexnet_training_seed_01_fov16	.638
248	resnet50-vicregl0p9	.636
249	efficientnet_b1_imagenet_full	.635
250	yudixie_resnet18_translation_rotation_0_240719	.635
251	cvt_cvt-21-384-in1k_4_LucyV4	.635
252	vit_base_patch16_clip_224:openai_ft_in1k	.634
253	resnet_101_v1	.628
254	AdvProp_efficientnet-b0	.627
255	aughost_fair_resnet18	.626
256	resnet50-SIN_IN	.626
257	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.625
258	resnet50_primary_visual_cortex	.623
259	vgg_19	.622
260	r3m_resnet34	.620
261	mobilenet_v2_1.4_224-tf	.620
262	convnext_base_imagenet_full_seed-0	.619
263	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.615
264	compact_resnet50_V4	.614
265	compact_resnet50_robust_IT	.612
266	yolos_tiny	.608
267	mobilenet_v2_1_0_128	.605
268	Res2Net50_26w_4s	.605
269	yudixie_resnet50_translation_reg_0_240908	.602
270	inception_v3	.601
271	barlow-twins-resnet50	.597
272	mobilenet_v2_0.35_224	.595
273	mobilenet_v2_1.0_128-tf	.593
274	mobilenet_v2_1.0_224-tf	.592
275	mobilenet_v2_1.0_160-tf	.592
276	compact_vgg19_IT	.592
277	yudixie_resnet18_translation_reg_0_240719	.586
278	yudixie_resnet18_distance_translation_rotation_0_240719	.583
279	resnet-18-LC_untrained	.580
280	CORnet-Z	.579
281	alexnet_robust_correct	.579
282	resnet-18-LC_1st_conv_m	.576
283	resnet50-meshes-lt-100-original-pretrained	.572
284	CORnet-S	.570
285	ReAlnet07_ALL	.569
286	mobilenet_v2_1-4_224_pytorch	.567
287	AdvProp_efficientnet-b6	.564
288	ReAlnet10_ALL	.563
289	briaai_rmbg_1_4	.560
290	ReAlnet02_ALL	.560
291	resnet101	.558
292	yudixie_resnet18_rotation_reg_0_240719	.557
293	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.553
294	resnet18_imagenet21kP	.554
295	resnet50_imagenet_1_seed-0	.553
296	yudixie_resnet18_distance_rotation_0_240719	.552
297	mobilenet_v2_0.5_128	.550
298	vision_transformer_vit_large_patch16_224	.549
299	ReAlnet03_ALL	.548
300	ReAlnet06_ALL	.548
301	ReAlnet08_ALL	.547
302	ReAlnet05_ALL	.546
303	ReAlnet09_ALL	.546
304	ReAlnet01_ALL	.546
305	ReAlnet07	.544
306	resnext101_32x8d_wsl	.543
307	ReAlnet07_cornet	.543
308	ReAlnet04_ALL	.543
309	ReAlnet08	.541
310	ReAlnet08_cornet	.541
311	mobilenet_v2_0.5_160	.539
312	efficientnet-b7	.537
313	resnet50_pretrained_with_retinal_waves	.534
314	convnext_base:clip_laiona_augreg_ft_in1k_384	.529
315	ViT-B/32	.529
316	0.5x_resnet-18	.528
317	ReAlnet01_cornet	.527
318	ReAlnet01	.528
319	ReAlnet04	.525
320	ReAlnet04_cornet	.524
321	vit_large_patch14_clip_336:laion2b_ft_in1k	.524
322	ReAlnet09_cornet	.522
323	ReAlnet10_cornet	.522
324	ReAlnet09	.520
325	efficientnet_b0	.521
326	ReAlnet10	.521
327	resnet-18_test_m	.516
328	resnet50-simclr-vissl	.515
329	ReAlnet06_cornet	.513
330	ReAlnet06	.512
331	alexnet_linf_8_robust	.512
332	resnet_50_v2	.511
333	v1-pyr-nodown	.510
334	ReAlnet03	.509
335	ReAlnet03_cornet	.509
336	resnet101_ecoset_full	.506
337	vit_large_patch14_clip_224:laion2b_ft_in1k	.503
338	hmax	.503
339	resnet101_imagenet_full	.498
340	texture_shape_alexnet_trained_on_SIN	.497
341	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.493
342	cornet_s	.487
343	resnet50_imagenet_full	.486
344	ReAlnet02_cornet	.486
345	ReAlnet02	.485
346	ReAlnet05	.483
347	ReAlnet05_cornet	.483
348	resnet152_ecoset_full	.481
349	alexnet_fov4	.480
350	resnet50_ecoset_full	.472
351	resnet50-vitoimagevidnet8	.473
352	resnet18_imagenet_full	.472
353	resnet18_ecoset_full	.471
354	inception_v1-tf	.466
355	CLIP_ViT-B_32	.460
356	alexnet_random_l2_3_perturb	.444
357	resnet50	.443
358	resnet34_ecoset_full	.443
359	deit_small_imagenet_full_seed-0	.442
360	resnet50_imagenet_100_seed-0	.435
361	resnet152_imagenet_full	.429
362	mobilevit_small	.429
363	my-model	.425
364	resnet34_imagenet_full	.397
365	AlexNet_SIN_fov4	.382
366	vit_base_patch14_reg4_dinov2-lvd142m	.332
367	deit_small_imagenet_10_seed-0	.330
368	vit_base_patch14_dinov2-lvd142m	.310
369	vit_base_patch16_dinov3-lvd1689m	.258
370	resnet50-cifar	.248
371	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.245
372	ReAlnet01_cornet_fov4	.196
373	mobilenet_v2_0.35_160
374	resnet18-supervised
375	r3m_resnet34_nocrop
376	fitvid_trained_on_physion
377	openclip
378	resnext101_32x32d_wsl
379	resnext101_32x48d_wsl
380	resnet50_ImageNet
381	regnet_y_400mf
382	tv_efficientnet-b1
383	alexnet_ks_torevert
384	yudixie_resnet50_imagenet1kpret_0_240312
385	resnet_152_v1
386	resnext101_32x16d_wsl
387	densenet_201_pytorch
388	pnasnet_large_pytorch
389	inception_v3_pytorch
390	inception_v4
391	nasnet_large
392	deit_small_imagenet_1_seed-0
393	pnasnet_large
394	vonegrcnn_62e_nobn
395	resnet_101_v2
396	vonegrcnn_47e
397	vonegrcnn_52e_full
398	resnet_152_v2

Benchmark bibtex

None

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: Marques2020_DeValois1982

Metric: peak_sf