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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021powerequalisation-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitg14_reg_lc	.995
2	dinov2_vitl14_reg_lc	.993
3	eva02_large_in22k	.991
4	dinov2_vitg14_lc	.989
5	dinov2_vitl14_lc_res336	.989
6	dinov2_vitl14_lc	.986
7	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.979
8	convnext_xxlarge_clip	.975
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.970
10	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.968
11	convnext_large_in22k_supervised	.966
12	vit_large_patch14_clip_224:openai_ft_in1k	.964
13	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.964
14	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.963
15	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.963
16	vit_huge_clip336_laion	.961
17	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.959
18	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.959
19	vit_large_clip336_openai	.959
20	convnext_large_clip_laion2b_finelayers	.952
21	convnext_large:fb_in22k_ft_in1k	.948
22	vit_large_patch14_clip_336:laion2b_ft_in1k	.945
23	convnext_base_fb_in1k	.945
24	convnext_xlarge:fb_in22k_ft_in1k	.943
25	deit_large_imagenet_full_seed-0	.943
26	vit_large_patch14_clip_224:laion2b_ft_in1k	.939
27	convnext_large_imagenet_full_seed-0	.938
28	convnext_base_fb_in22k_ft_in1k	.938
29	convnext_base:clip_laiona_augreg_ft_in1k_384	.936
30	convnext_small_imagenet_full_seed-0	.934
31	convnext_base_imagenet_full_seed-0	.934
32	deit3_base_patch16_224_fb_in22k_ft_in1k	.932
33	deit_base_imagenet_full_seed-0	.929
34	convnext_tiny:in12k_ft_in1k	.927
35	effnetv2m_custom384	.923
36	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.914
37	resnext101_32x32d_wsl	.911
38	vit_relpos_base_patch16_clsgap_224:sw_in1k	.911
39	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.909
40	fixres_resnext101_32x48d_wsl	.907
41	cv_18_dagger_408_pretrained	.905
42	focalnet_tiny_lrf_in1k	.905
43	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.902
44	resnext101_32x16d_wsl	.902
45	resnext101_32x48d_wsl	.900
46	vit_base_patch16_clip_224:openai_ft_in1k	.896
47	resnext101_32x8d_wsl	.896
48	convnext_tiny_imagenet_full_seed-0	.893
49	AdvProp_efficientnet-b7	.891
50	seresnext50_32x4d	.889
51	regnety_032	.882
52	AdvProp_efficientnet-b6	.875
53	convnext_tiny_sup	.875
54	cvt_cvt-13-224-in1k_4_LucyV4	.871
55	deit_small_imagenet_full_seed-0	.868
56	nasnet_large-tf	.864
57	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.863
58	resnet_101_v2	.854
59	resnet-152_v2_pytorch	.850
60	cvt_cvt-21-384-in1k_4_LucyV4	.850
61	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.845
62	cvt_cvt-21-224-in1k_4_LucyV4	.841
63	nasnet_large	.841
64	convnext_femto_ols:d1_in1k	.836
65	AdvProp_efficientnet-b4	.834
66	AT_efficientnet-b4	.834
67	densenet-201	.832
68	densenet_201_pytorch	.832
69	densenet-201-keras	.832
70	inception_v4-tf	.830
71	densenet-169	.825
72	densenet-169-keras	.823
73	cvt_cvt-13-384-in1k_4_LucyV4	.823
74	resnet_50_v2	.823
75	convnext_base_fb_in1k_gram_aligned_dinov3	.823
76	efficientnet-b7	.820
77	pnasnet_large-tf	.814
78	resnet-101_v2-tf	.812
79	pnasnet_large_halfPrecision	.812
80	pnasnet_large	.812
81	inception_v4	.807
82	inception_v3-tf	.807
83	resnet50-SIN	.807
84	inception_v2-tf	.804
85	inception_v3_pytorch	.804
86	tv_efficientnet-b1	.804
87	resnet_152_v2	.804
88	AdvProp_efficientnet-b0	.802
89	xception-keras	.800
90	resnet50-SIN_IN	.798
91	antialiased-rnext101_32x8d	.798
92	ViT_L_32_imagenet1k	.796
93	AT_efficientnet-b2	.796
94	AdvProp_efficientnet-b2	.796
95	effnetb1_272x240	.793
96	antialias-resnet152	.793
97	resnet_152_v1	.793
98	inception_v3	.791
99	BiT-S-R152x2	.787
100	BiT-S-R50x3	.786
101	resnet-152_v2-tf	.786
102	grcnn_109	.786
103	BiT-S-R152x4	.780
104	resnet-50_v2-tf	.780
105	Res2Net50_26w_4s	.780
106	resnet50_st_wzc_2	.777
107	BiT-S-R101x1	.777
108	densenet-121-keras	.775
109	BiT-S-R101x3	.775
110	BiT-S-R50x1	.773
111	densenet-121	.773
112	resnet50_hvs_wzc	.773
113	resnet50-vitoimagevidnet8	.770
114	inception_v1-tf	.766
115	ViT_B_32_imagenet1k	.766
116	resnet50_ewconplus_wzc	.766
117	resnet_101_v1	.766
118	resnet50_st_wzc_seed6_2_323	.762
119	resnet101_imagenet_full	.757
120	resnet_SIN_IN_FT_IN	.755
121	resnet50-SIN_IN_IN	.755
122	resnet50-VITO-8deg-cc	.754
123	grcnn	.752
124	efficientnet_b0	.743
125	resnet-152_v1-tf	.738
126	vonegrcnn_47e	.736
127	resnet50_ewconplus_wzc_seed2_2__323	.734
128	resnet50_ewconplus_wzc_seed5_2__323	.734
129	resnet50_tutorial	.732
130	resnet_50_v1	.732
131	resnet-50-pytorch	.732
132	resnet50-sup	.732
133	vonegrcnn_47e	.730
134	resnet50-moclr8deg	.730
135	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.730
136	antialiased-r50	.729
137	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.727
138	AdvProp_efficientnet-b8	.725
139	resnet50_st_wzc_seed7_2_323	.723
140	efficientnet_b2_imagenet_full	.720
141	vonegrcnn_62e_nobn	.720
142	resnet-50_v1-tf	.720
143	resnet50_imagenet_full	.718
144	resnet152_imagenet_full	.716
145	resnet50	.711
146	vonegrcnn_52e_full	.709
147	resnet-101_v1-tf	.709
148	vonegrcnn_62e_nobn	.707
149	CORnet-S	.707
150	xception	.704
151	resnet-34	.698
152	resnet_50_v1_spiking	.698
153	CLIP-RN50	.696
154	resnet50_moco_v2	.696
155	resnet50_robust_l2_eps1	.696
156	voneresnet-50-non_stochastic	.695
157	vgg-19-keras	.691
158	resnet34_imagenet_full	.691
159	efficientnet_b1_imagenet_full	.691
160	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.689
161	vonegrcnn_52e_full	.686
162	inception_v1	.684
163	mobilenet_v2_1.4_224-tf	.682
164	mobilenet_v2_1.3_224-tf	.679
165	voneresnet-50-robust	.679
166	mobilenet_v2_1_3_224	.679
167	ReAlnet06	.673
168	AlexNet_SIN	.671
169	AlexNet_SIN_fov4	.671
170	AlexNet_SIN_fov12	.671
171	AlexNet_SIN_fov16	.671
172	nasnet_mobile	.670
173	eBarlow_lmda_02_1000ep	.664
174	mobilenet_v2_1.0_224-tf	.664
175	vgg-16-keras	.661
176	efficientnet_b0_imagenet_full	.657
177	pnasnet_large_pytorch	.657
178	eicircuit_resnet18_bn_20260919	.657
179	voneresnet-50	.652
180	vgg_16	.652
181	vgg_19	.648
182	ReAlnet04	.648
183	ReAlnet01	.645
184	mobilenet_v2_0.75_192-tf	.641
185	mobilenet_v2_1_0_224	.639
186	mobilenet_v2_1.0_192-tf	.637
187	mobilenet_v1_1.0_192	.637
188	regnet_y_400mf	.637
189	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.636
190	resnet18_imagenet_full	.632
191	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.632
192	resnet-18	.630
193	mobilenet_v2_1_0_192	.630
194	ReAlnet09	.627
195	mobilenet_v2_0.75_224-tf	.627
196	mobilenet_v2_0_75_192	.625
197	blt_vs	.625
198	ReAlnet03	.625
199	custom_model_cv_18_dagger_408	.623
200	ReAlnet08	.621
201	ReAlnet05	.621
202	mobilenet_v2_1.0_160-tf	.620
203	mobilenet_v1_1.0_224	.616
204	ReAlnet07	.613
205	ReAlnet10	.611
206	ReAlnet02	.609
207	nasnet_mobile-tf	.609
208	resnet-50-robust	.609
209	imagenet_l2_3_0	.609
210	resnet50_robust_l2_eps3	.609
211	mobilenet_v2_0_75_224	.605
212	mobilenet_v2_1_0_160	.604
213	shufflenet_v2_x1_0	.598
214	resnet50_eMMCR_Vanilla	.598
215	mobilenet_v2_1-4_224_pytorch	.596
216	mobilenet_v2_1_4_224	.596
217	mobilenet_v1_0.75_224	.596
218	mobilenet_v2_1.0_128-tf	.586
219	mobilenet_v1_1.0_160	.571
220	mobilenet_v2_1_0_128	.570
221	resnet50_l2_3_robust	.570
222	mobilenet_v2_0_5_224	.559
223	resnet_50_v1_spiking_l4a	.554
224	convnext_small_imagenet_100_seed-0	.554
225	mobilenet_v2_0_75_160	.552
226	mobilenet_v2_0.5_224-tf	.548
227	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.541
228	mobilenet_v1_0.75_192	.539
229	mobilenet_v1_0.75_160	.539
230	mobilenet_v1_1.0_128	.537
231	mobilenet_v2_0.75_160-tf	.537
232	resnet50_linf_8_robust	.536
233	mobilenet_v2_0_5_192	.532
234	mobilenet_v2_0.75_128	.532
235	alexnet_random_linf8_perturb	.532
236	mobilenet_v1_0.5_224	.530
237	mobilenet_v2_0.5_160	.523
238	mobilenet_v2_0.5_192-tf	.521
239	alexnet	.505
240	alexnet_ks_torevert	.505
241	alexnet_fov4	.505
242	alexnet_fov12	.505
243	alexnet_fov16	.505
244	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.504
245	squeezenet1_1	.498
246	mobilenet_v1_0.5_160	.498
247	alexnet_early_checkpoint	.498
248	mobilenet_v2_0.35_192	.496
249	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.495
250	mobilenet_v1_0.5_192	.495
251	mobilenet_v2_1.0_96	.491
252	mobilenet_v1_0.75_128	.484
253	mobilenet_v2_0.5_128	.482
254	mobilenet_v2_0.35_224	.461
255	squeezenet1_0	.457
256	mobilenet_v1_0.5_128	.457
257	mobilenet_v2_0.35_160	.454
258	mobilenet_v2_0.75_96	.445
259	imagenet_l2_10_0	.425
260	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.412
261	0.5x_resnet-18_LC_w_sh_1_iter	.409
262	mobilenet_v2_0.35_128	.396
263	mobilenet_v2_0.5_96	.366
264	mobilenet_v1_0.25_224	.366
265	alexnet_robust_correct	.362
266	mobilenet_v2_0.35_96	.354
267	mobilenet_v1_0.25_160	.339
268	alexnet_l2_3_robust	.327
269	mobilenet_v1_0.25_192	.316
270	alexnet_linf_8_robust	.296
271	mobilenet_v1_0.25_128	.284
272	deit_small_imagenet_100_seed-0	.282
273	resnet_50_v1_spiking_l4	.279
274	resnet50_imagenet_100_seed-0	.266
275	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.084
276	resnet50-vicregl0p9	.077
277	convnext_small_imagenet_10_seed-0	.075
278	resnet50_imagenet_10_seed-0	.073
279	resnet_50_v1_spiking_l3	.073
280	deit_small_imagenet_10_seed-0	.066
281	resnet50_imagenet_1_seed-0	.066
282	alexnet_training_seed_09	.064
283	convnext_small_imagenet_1_seed-0	.064
284	resnet50-vicregl0p75	.064
285	resnet-50_untrained	.062
286	alexnet_training_seed_05	.062
287	mobilevit_small	.062
288	alexnet_training_seed_02	.062
289	alexnet_training_seed_04	.062
290	alexnet_training_seed_08	.062
291	alexnet_training_seed_10	.062
292	alexnet_training_seed_01	.062
293	deit_small_imagenet_1_seed-0	.062
294	alexnet_training_seed_01_fov4	.062
295	alexnet_training_seed_01_fov12	.062
296	alexnet_training_seed_01_fov16	.062
297	alexnet_training_seed_03	.062
298	alexnet_training_seed_06	.059
299	alexnet_training_seed_07	.057
300	resnet50-barlow	.052
301	artResNet18_1	.048
302	barlow-twins-resnet50	.048
303	resnet50-simclr-vissl	.039
304	ViT-B/32
305	resnet-18-LC_w_sh_100_iter_conv_init_m
306	BiT-M-R50x1
307	resnet-18-LC_w_sh_1_iter_conv_init_m
308	BiT-M-R152x2
309	resnet-18-LC_w_sh_1_iter_m
310	BiT-M-R50x3
311	resnet-18-LC_w_sh_10_iter_m
312	resnet-18-LC_w_sh_100_iter_m
313	resnet-18-LC_w_sh_10_iter_conv_init_m
314	FrankRobWobv0
315	0.5x_resnet-18_LC
316	CORnetZ_CIFAR10
317	resnet18-local_aggregation
318	r3m_resnet18
319	resnet18-deepcluster
320	CORnet-Z
321	vggface
322	resnet18-instance_recognition
323	my-model
324	0.5x_resnet-18_LC_w_sh_10_iter
325	r3m_resnet50
326	r3m_resnet34
327	resnet-18-LC_m
328	resnet18-supervised
329	r3m_resnet50_nocrop
330	resnet-18-LC_1st_conv_m
331	resnet-18-LC_conv_init_m
332	resnet18-contrastive_multiview
333	0.5x_resnet-18
334	0.5x_resnet-18_LC_w_sh_100_iter
335	RN50
336	RN50
337	resnet18-colorization
338	resnet18-relative_position
339	resnet18-autoencoder
340	resnet18-simclr
341	ViT_L_32
342	ViT_B_32
343	resnet18-depth_prediction
344	ViT_B_16
345	r3m_resnet34_nocrop
346	resnet18-contrastive_predictive
347	resnet-18-LC_untrained
348	resnet-18_untrained
349	resnet-50x2_untrained
350	dcgan
351	unet_entire
352	CORnetZ_CIFAR10_bs32_20_04
353	v1-pyr-nodown
354	pixels
355	dorinet_cornet_z
356	omnivore_swinT
357	openclip
358	vonealexnet_gaussian_noise_std4_fixed
359	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
360	ReAlnet08_ALL
361	yudixie_resnet50_imagenet1kpret_0_240312
362	yudixie_resnet50_category_class_0_240908
363	yudixie_resnet50_distance_reg_0_240908
364	resnet18_imagenet21kP
365	ConvLSTM
366	PredRNN
367	SimVP
368	TAU
369	yolos_tiny
370	MIM
371	hmax
372	ReAlnet01_cornet
373	yudixie_resnet18_distance_translation_0_240719
374	briaai_rmbg_1_4
375	vit_base_patch16_dinov3-lvd1689m
376	ReAlnet03_cornet
377	yudixie_resnet18_distance_reg_0_240719
378	yudixie_resnet18_rotation_reg_0_240719
379	yudixie_resnet18_imagenet1kpret_0_240719
380	compact_resnet50_V4
381	ReAlnet02_cornet
382	yudixie_resnet50_rotation_reg_0_240908
383	yudixie_resnet50_distance_rotation_0_240908
384	yudixie_resnet50_distance_translation_0_240908
385	compact_resnet50_IT
386	resnet18_ecoset_full
387	vit_base_patch14_dinov2-lvd142m
388	VOneCORnet-S
389	ReAlnet01_cornet_fov4
390	ReAlnet04_cornet
391	resnet50_ecoset_full
392	resnet101_ecoset_full
393	ReAlnet01_cornet_fov12
394	vit_base_patch14_reg4_dinov2-lvd142m
395	resnet152_ecoset_full
396	compact_vgg19_V4
397	yudixie_resnet18_translation_rotation_0_240719
398	yudixie_resnet18_distance_rotation_0_240719
399	resnet-18_test_m
400	yudixie_resnet50_translation_reg_0_240908
401	yudixie_resnet18_category_class_0_240719
402	ReAlnet05_cornet
403	yudixie_resnet18_random_0_240719
404	yudixie_resnet18_cat_obj_class_all_latents_0_240719
405	yudixie_resnet18_translation_reg_0_240719
406	compact_vgg19_IT
407	yudixie_resnet18_distance_translation_rotation_0_240719
408	yudixie_resnet18_object_class_0_240719
409	SeLaVi-AVE
410	ReAlnet06_cornet
411	compact_resnet50_robust_V4
412	r3d_18
413	ReAlnet01_cornet_fov16
414	yudixie_resnet50_translation_rotation_0_240908
415	ReAlnet01_ALL
416	ReAlnet07_cornet
417	mc3_18
418	ReAlnet02_ALL
419	s3d
420	omnivore_swinB
421	ReAlnet08_cornet
422	resnet50-vicreg
423	mvit_v1_b
424	ReAlnet04_ALL
425	compact_cornets_V4
426	ReAlnet03_ALL
427	compact_cornets_IT
428	ReAlnet09_cornet
429	omnivore_swinS
430	ReAlnet05_ALL
431	SeLaVi-Kinetics400
432	SeLaVi-VGG-Sound
433	ReAlnet06_ALL
434	SeLaVi-Kinetics-Sound
435	compact_resnet50_robust_IT
436	yudixie_resnet50_distance_translation_rotation_0_240908
437	yudixie_resnet50_random_0_240908
438	r2plus1d_18
439	mvit_v2_s
440	yudixie_resnet50_imagenet1kpret_0_240908
441	ReAlnet07_ALL
442	resnet34_ecoset_full
443	yudixie_resnet50_cat_obj_class_all_latents_0_240908
444	ReAlnet09_ALL
445	yudixie_resnet50_object_class_0_240908
446	ReAlnet10_cornet
447	resnet50_primary_visual_cortex
448	ReAlnet10_ALL
449	resnet18_fair
450	pr1_stl10_disentangled_alpha04
451	predictive_coding_pc
452	yudixie_wbh_object_class_scaling_0415_run_0
453	yudixie_wbh_object_class_scaling_0415_run_3
454	yudixie_wbh_object_class_scaling_0415_imagenet
455	yudixie_wbh_object_class_scaling_0415_run_2
456	yudixie_wbh_object_class_scaling_0415_run_1
457	deepeisnn_ei_cifar10_vgg19
458	deepeisnn_ei_cifar10_resnet18
459	deepeisnn_ei_imagenet_resnet18
460	dinov2_vitl14_reg_lc_featread
461	gabor_filter_entropy_4x4
462	gabor_filter_mean_abs_4x4_v2
463	gabor_filter_entropy_4x4_v2
464	gabor_filter_entropy_4x4_v2_forcedCosine

Benchmark bibtex

@article{geirhos2021partial,
              title={Partial success in closing the gap between human and machine vision},
              author={Geirhos, Robert and Narayanappa, Kantharaju and Mitzkus, Benjamin and Thieringer, Tizian and Bethge, Matthias and Wichmann, Felix A and Brendel, Wieland},
              journal={Advances in Neural Information Processing Systems},
              volume={34},
              year={2021},
              url={https://openreview.net/forum?id=QkljT4mrfs}
        }

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021powerequalisation

Metric: top1