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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitg14_lc	.759
2	fixres_resnext101_32x48d_wsl	.755
3	dinov2_vitl14_lc	.748
4	vit_large_patch14_clip_224:laion2b_ft_in1k	.718
5	cvt_cvt-13-384-in1k_4_LucyV4	.713
6	vit_large_patch14_clip_224:openai_ft_in1k	.709
7	cvt_cvt-21-384-in1k_4_LucyV4	.707
8	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.707
9	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.705
10	convnext_xxlarge_clip	.692
11	convnext_xlarge:fb_in22k_ft_in1k	.680
12	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.672
13	convnext_large:fb_in22k_ft_in1k	.670
14	SWSL_resnext101_32x8d	.668
15	dinov2_vitl14_reg_lc	.659
16	vit_large_patch14_clip_336:laion2b_ft_in1k	.651
17	vit_large_clip336_openai	.651
18	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.650
19	vit_base_patch16_clip_224:openai_ft_in1k	.647
20	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.638
21	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.633
22	convnext_large_in22k_supervised	.601
23	dinov2_vitg14_reg_lc	.600
24	resnet_152_v2	.599
25	resnext101_32x16d_wsl	.592
26	convnext_base:clip_laiona_augreg_ft_in1k_384	.586
27	resnext101_32x32d_wsl	.579
28	convnext_base_fb_in22k_ft_in1k	.568
29	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.564
30	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.560
31	resnext101_32x48d_wsl	.548
32	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.540
33	vit_huge_clip336_laion	.526
34	effnetv2m_custom384	.501
35	resnet-152_v2_pytorch	.494
36	convnext_large_clip_laion2b_finelayers	.490
37	SWSL_resnet50	.489
38	dinov2_vitl14_lc_res336	.487
39	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.486
40	convnext_base_imagenet_full_seed-0	.482
41	vision_transformer_vit_large_patch16_224	.472
42	convnext_tiny:in12k_ft_in1k	.468
43	convnext_large_imagenet_full_seed-0	.467
44	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.462
45	resnet_50_v2	.455
46	resnext101_32x8d_wsl	.453
47	resnet_101_v2	.451
48	convnext_small_imagenet_full_seed-0	.450
49	convnext_tiny_imagenet_full_seed-0	.427
50	CLIP_resnet50	.427
51	CLIP_resnet50_float32	.427
52	cvt_cvt-13-224-in1k_4_LucyV4	.397
53	cv_18_dagger_408_pretrained	.388
54	vit_relpos_base_patch16_clsgap_224:sw_in1k	.382
55	pnasnet_large_halfPrecision	.380
56	pnasnet_large	.380
57	convnext_femto_ols:d1_in1k	.378
58	convnext_base_fb_in1k	.372
59	eva02_large_in22k	.365
60	nasnet_large	.363
61	deit3_base_patch16_224_fb_in22k_ft_in1k	.363
62	ViT_B_16_imagenet1k	.339
63	resnet-152_v2-tf	.335
64	resnet50_st_wzc_seed7_2_323	.328
65	inception_v4	.323
66	focalnet_tiny_lrf_in1k	.317
67	resnet152_imagenet_full	.317
68	CLIP-RN50	.315
69	ViT_L_32_imagenet1k	.307
70	regnety_032	.305
71	pnasnet_large-tf	.295
72	resnet50-VITO-8deg-cc	.292
73	antialias-resnet152	.289
74	effnetb1_272x240	.289
75	resnet101	.287
76	CLIP_ViT-B_32	.287
77	inception_v3	.280
78	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.278
79	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.269
80	deit_large_imagenet_full_seed-0	.269
81	resnet50_random_linf8_perturb	.260
82	resnet_152_v1	.260
83	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.257
84	nasnet_large-tf	.248
85	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.246
86	xception-keras	.245
87	seresnext50_32x4d	.243
88	inception_v3-tf	.237
89	resnet_101_v1	.234
90	resnet50_st_wzc_seed6_2_323	.231
91	cvt_cvt-21-224-in1k_4_LucyV4	.228
92	resnet50_random_l2_perturb	.227
93	inception_v3_pytorch	.222
94	resnet101_imagenet_full	.221
95	resnet50_ewconplus_wzc_seed5_2__323	.219
96	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.218
97	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.217
98	ViT_B_32_imagenet1k	.217
99	resnet50_imagenet_full	.216
100	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.214
101	inception_v4-tf	.209
102	convnext_base_fb_in1k_gram_aligned_dinov3	.206
103	resnet50_st_wzc_seed3_2_323	.203
104	grcnn_109	.201
105	resnet50_ewconplus_wzc_seed2_2__323	.197
106	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.197
107	vgg_19	.195
108	Res2Net50_26w_4s	.193
109	AdvProp_efficientnet-b7	.190
110	AdvProp_efficientnet-b4	.189
111	AT_efficientnet-b4	.189
112	AdvProp_efficientnet-b6	.187
113	AT_efficientnet-b2	.186
114	AdvProp_efficientnet-b2	.186
115	resnet50	.185
116	xception	.184
117	resnet50_linf_4_robust	.182
118	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.182
119	efficientnet_b0	.181
120	resnet_50_v1_spiking	.181
121	resnet50_ewconplus_wzc	.174
122	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.173
123	AlexNet_SIN_fov4	.172
124	deit_base_imagenet_full_seed-0	.169
125	convnext_small_imagenet_100_seed-0	.167
126	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.164
127	resnet50_st_wzc_2	.163
128	resnet50-moclr8deg	.159
129	resnet-50_v2-tf	.155
130	antialiased-rnext101_32x8d	.149
131	densenet-121-keras	.147
132	custom_model_cv_18_dagger_408	.145
133	inception_v2-tf	.145
134	alexnet_random_linf8_perturb	.140
135	resnet50_hvs_wzc	.136
136	resnet50_byol	.134
137	pnasnet_large_pytorch	.133
138	resnet50-SIN_IN_IN	.132
139	resnet_SIN_IN_FT_IN	.132
140	alexnet_fov4	.132
141	BiT-S-R50x3	.128
142	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.127
143	antialiased-r50	.127
144	resnet34_imagenet_full	.126
145	grcnn	.125
146	densenet-201	.125
147	densenet_201_pytorch	.125
148	voneresnet-50-robust	.122
149	ReAlnet03	.121
150	densenet-121	.119
151	resnet50_linf_8_robust	.119
152	ReAlnet04	.118
153	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.116
154	ReAlnet08	.115
155	efficientnet-b7	.114
156	vgg_16	.113
157	densenet-201-keras	.112
158	voneresnet-50-non_stochastic	.108
159	resnet-50_v1-tf	.107
160	vonealexnet_gaussian_noise_std4_fixed	.105
161	ReAlnet01	.105
162	inception_v1	.100
163	alexnet_l2_3_robust	.098
164	alexnet_random_l2_3_perturb	.098
165	resnet50_tutorial	.098
166	resnet_50_v1	.098
167	resnet-50-pytorch	.098
168	resnet50-sup	.098
169	alexnet_ks_torevert	.097
170	alexnet	.097
171	ReAlnet05	.096
172	densenet-169	.096
173	resnet50_l2_3_robust	.095
174	resnet-152_v1-tf	.094
175	resnet50_moco_v2	.094
176	densenet-169-keras	.094
177	ReAlnet02	.093
178	ReAlnet07	.091
179	tv_efficientnet-b1	.090
180	cornet_s	.089
181	convnext_tiny_sup	.089
182	ReAlnet06	.089
183	vonegrcnn_62e_nobn	.088
184	vonegrcnn_62e_nobn	.088
185	alexnet_reduced_aliasing_early_checkpoint	.088
186	nasnet_mobile-tf	.086
187	alexnet_early_checkpoint	.085
188	deit_small_imagenet_full_seed-0	.084
189	BiT-S-R152x2	.083
190	ReAlnet10	.083
191	vonegrcnn_52e_full	.083
192	alexnet_training_seed_05	.083
193	alexnet_training_seed_01	.083
194	alexnet_training_seed_01_fov4	.083
195	alexnet_training_seed_01_fov12	.083
196	alexnet_training_seed_01_fov16	.083
197	resnet50-vitoimagevidnet8	.082
198	inception_v1-tf	.078
199	barlow-twins-resnet50	.078
200	ReAlnet09	.078
201	resnet-101_v1-tf	.076
202	resnet50_robust_l2_eps1	.075
203	vonegrcnn_47e	.075
204	AdvProp_efficientnet-b8	.073
205	resnet-34	.070
206	vonegrcnn_52e_full	.070
207	alexnet_fov12	.069
208	squeezenet1_1	.068
209	resnet18_imagenet_full	.065
210	vonegrcnn_47e	.065
211	mobilenet_v2_1.0_160-tf	.065
212	alexnet_robust_correct	.064
213	artResNet18_1	.064
214	resnet50-SIN_IN	.063
215	resnet-50-robust	.062
216	imagenet_l2_3_0	.062
217	resnet50_robust_l2_eps3	.062
218	konkle_alexnetgn_ipcl_ref01_primary_model	.062
219	mobilenet_v2_1_0_192	.060
220	resnet50_simclr	.059
221	mobilenet_v2_1_0_160	.059
222	eBarlow_lmda_02_1000ep	.059
223	BiT-S-R152x4	.057
224	alexnet_training_seed_02	.053
225	alexnet_training_seed_04	.053
226	alexnet_training_seed_08	.053
227	alexnet_training_seed_10	.053
228	vgg-19-keras	.053
229	CORnet-S	.052
230	eicircuit_resnet18_bn_20260919	.051
231	efficientnet_b2_imagenet_full	.050
232	mobilenet_v1_0.25_128	.048
233	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.048
234	mobilenet_v2_1.0_224-tf	.047
235	vgg-16-keras	.047
236	mobilenet_v2_0_5_192	.046
237	voneresnet-50	.045
238	texture_shape_resnet50_trained_on_SIN	.044
239	mobilenet_v2_0.5_96	.043
240	mobilenet_v1_0.5_160	.041
241	convnext_small_imagenet_1_seed-0	.041
242	AlexNet_SIN_fov12	.040
243	deit_small_imagenet_100_seed-0	.040
244	mobilenet_v2_1_0_224	.040
245	resnet50_imagenet_100_seed-0	.040
246	alexnet_fov16	.040
247	resnet50-SIN	.040
248	mobilenet_v1_0.5_128	.039
249	BiT-S-R101x3	.039
250	resnet50-barlow	.038
251	alexnet_training_seed_07	.038
252	alexnet_training_seed_09	.038
253	AdvProp_efficientnet-b0	.038
254	0.5x_resnet-18_LC_w_sh_1_iter	.038
255	BiT-S-R50x1	.037
256	mobilenet_v2_0.35_192	.037
257	texture_shape_alexnet_trained_on_SIN	.037
258	alexnet_linf_8_robust	.037
259	mobilenet_v2_1-4_224_pytorch	.036
260	mobilenet_v2_1_4_224	.036
261	resnet50_FractalDB	.036
262	BiT-S-R101x1	.035
263	mobilenet_v1_0.75_192	.035
264	mobilenet_v1_0.5_224	.034
265	mobilenet_v2_0.5_128	.034
266	mobilenet_v2_0_75_224	.034
267	mobilenet_v1_0.25_192	.033
268	mobilenet_v2_0.35_224	.033
269	resnet50_imagenet_10_seed-0	.033
270	AlexNet_SIN	.032
271	nasnet_mobile	.032
272	efficientnet_b0_imagenet_full	.031
273	mobilenet_v2_1.0_96	.031
274	deit_small_imagenet_10_seed-0	.031
275	deit_small_imagenet_1_seed-0	.031
276	convnext_small_imagenet_10_seed-0	.031
277	AlexNet_SIN_fov16	.031
278	resnet50-vicregl0p9	.030
279	resnet50-vicregl0p75	.029
280	mobilenet_v2_0.5_192-tf	.028
281	resnet50-vicreg	.027
282	mobilenet_v2_0.75_96	.027
283	mobilenet_v2_1_3_224	.027
284	mobilenet_v2_1.0_128-tf	.026
285	resnet-50_untrained	.024
286	mobilenet_v1_0.25_224	.024
287	mobilenet_v2_0.75_224-tf	.023
288	blt_vs	.023
289	mobilenet_v2_0.35_128	.023
290	mobilenet_v1_0.5_192	.021
291	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.021
292	mobilenet_v2_1.4_224-tf	.020
293	mobilenet_v2_0.35_160	.020
294	mobilenet_v2_0_75_160	.019
295	mobilenet_v2_0.75_128	.019
296	mobilenet_v2_0_75_192	.019
297	mobilenet_v2_0.5_160	.018
298	imagenet_l2_10_0	.018
299	mobilenet_v2_1.0_192-tf	.017
300	mobilenet_v1_0.75_160	.016
301	squeezenet1_0	.015
302	shufflenet_v2_x1_0	.015
303	mobilenet_v2_0.35_96	.014
304	alexnet_training_seed_06	.014
305	mobilenet_v2_0.5_224-tf	.014
306	mobilenet_v1_0.75_128	.014
307	resnet50_eMMCR_Vanilla	.013
308	resnet_50_v1_spiking_l4a	.012
309	resnet50_imagenet_1_seed-0	.012
310	mobilenet_v2_0.75_160-tf	.011
311	resnet_50_v1_spiking_l4	.011
312	resnet_50_v1_spiking_l3	.011
313	alexnet_training_seed_03	.010
314	mobilenet_v2_0_5_224	.010
315	mobilevit_small	.010
316	mobilenet_v1_1.0_192	.009
317	resnet50-simclr-vissl	.008
318	mobilenet_v1_0.25_160	.007
319	mobilenet_v1_1.0_128	.006
320	mobilenet_v1_1.0_160	.006
321	mobilenet_v1_1.0_224	.005
322	resnet-18	.004
323	mobilenet_v2_1_0_128	.003
324	mobilenet_v2_1.3_224-tf	.003
325	efficientnet_b1_imagenet_full	.003
326	regnet_y_400mf	.002
327	mobilenet_v2_0.75_192-tf	.002
328	mobilenet_v1_0.75_224	.001
329	my-model	.000
330	resnet-18-LC_w_sh_100_iter_conv_init_m
331	ViT-B/32
332	BiT-M-R50x3
333	BiT-M-R50x1
334	BiT-M-R152x2
335	resnet-18-LC_w_sh_1_iter_conv_init_m
336	resnet-18-LC_w_sh_10_iter_m
337	resnet-18-LC_w_sh_100_iter_m
338	resnet-18-LC_w_sh_10_iter_conv_init_m
339	resnet-18-LC_w_sh_1_iter_m
340	FrankRobWobv0
341	0.5x_resnet-18_LC
342	CORnetZ_CIFAR10
343	resnet18-local_aggregation
344	resnet18-deepcluster
345	r3m_resnet18
346	CORnet-Z
347	resnet18-instance_recognition
348	vggface
349	my-model
350	0.5x_resnet-18_LC_w_sh_10_iter
351	r3m_resnet50
352	r3m_resnet34
353	resnet18-colorization
354	resnet-18-LC_m
355	r3m_resnet50_nocrop
356	resnet18-supervised
357	resnet-18-LC_1st_conv_m
358	resnet-18-LC_conv_init_m
359	resnet18-contrastive_multiview
360	0.5x_resnet-18
361	RN50
362	0.5x_resnet-18_LC_w_sh_100_iter
363	RN50
364	resnet18-relative_position
365	resnet18-autoencoder
366	resnet18-simclr
367	ViT_L_32
368	ViT_B_32
369	resnet18-depth_prediction
370	ViT_B_16
371	r3m_resnet34_nocrop
372	resnet18-contrastive_predictive
373	omnivore_swinT
374	resnet-18-LC_untrained
375	resnet-18_untrained
376	resnet-50x2_untrained
377	dcgan
378	unet_entire
379	v1-pyr-nodown
380	CORnetZ_CIFAR10_bs32_20_04
381	pixels
382	dorinet_cornet_z
383	openclip
384	resnet50-cifar
385	resnet50_pretrained_with_retinal_waves
386	resnet50_ImageNet
387	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
388	yudixie_resnet50_random_0_240908
389	yudixie_resnet50_cat_obj_class_all_latents_0_240908
390	yudixie_resnet50_imagenet1kpret_0_240908
391	yudixie_resnet50_imagenet1kpret_0_240312
392	yudixie_resnet50_object_class_0_240908
393	yudixie_resnet50_category_class_0_240908
394	resnet18_imagenet21kP
395	yudixie_resnet50_distance_reg_0_240908
396	ConvLSTM
397	PredRNN
398	SimVP
399	TAU
400	MIM
401	hmax
402	briaai_rmbg_1_4
403	ReAlnet01_cornet
404	compact_resnet50_V4
405	yudixie_resnet18_translation_reg_0_240719
406	yolos_tiny
407	ReAlnet03_cornet
408	yudixie_resnet18_rotation_reg_0_240719
409	yudixie_resnet18_imagenet1kpret_0_240719
410	ReAlnet02_cornet
411	vit_base_patch14_dinov2-lvd142m
412	resnet18_ecoset_full
413	compact_resnet50_IT
414	resnet50_ecoset_full
415	VOneCORnet-S
416	vit_base_patch14_reg4_dinov2-lvd142m
417	ReAlnet01_cornet_fov12
418	resnet101_ecoset_full
419	yudixie_resnet50_distance_translation_0_240908
420	resnet152_ecoset_full
421	yudixie_resnet18_distance_translation_0_240719
422	ReAlnet01_cornet_fov4
423	yudixie_resnet18_translation_rotation_0_240719
424	compact_vgg19_V4
425	yudixie_resnet18_distance_rotation_0_240719
426	yudixie_resnet18_category_class_0_240719
427	resnet-18_test_m
428	yudixie_resnet18_cat_obj_class_all_latents_0_240719
429	yudixie_resnet50_rotation_reg_0_240908
430	yudixie_resnet50_distance_rotation_0_240908
431	yudixie_resnet18_object_class_0_240719
432	SeLaVi-AVE
433	ReAlnet05_cornet
434	ReAlnet06_cornet
435	compact_resnet50_robust_V4
436	compact_vgg19_IT
437	yudixie_resnet50_translation_reg_0_240908
438	r3d_18
439	ReAlnet01_ALL
440	yudixie_resnet18_distance_reg_0_240719
441	yudixie_resnet50_translation_rotation_0_240908
442	omnivore_swinB
443	mc3_18
444	ReAlnet07_cornet
445	s3d
446	ReAlnet02_ALL
447	ReAlnet01_cornet_fov16
448	mvit_v1_b
449	ReAlnet08_cornet
450	ReAlnet04_ALL
451	compact_cornets_V4
452	ReAlnet03_ALL
453	ReAlnet09_cornet
454	SeLaVi-Kinetics400
455	ReAlnet05_ALL
456	compact_cornets_IT
457	SeLaVi-VGG-Sound
458	vit_base_patch16_dinov3-lvd1689m
459	ReAlnet06_ALL
460	SeLaVi-Kinetics-Sound
461	mvit_v2_s
462	omnivore_swinS
463	r2plus1d_18
464	compact_resnet50_robust_IT
465	yudixie_resnet50_distance_translation_rotation_0_240908
466	ReAlnet10_cornet
467	ReAlnet07_ALL
468	resnet34_ecoset_full
469	ReAlnet08_ALL
470	yudixie_resnet18_random_0_240719
471	yudixie_resnet18_distance_translation_rotation_0_240719
472	ReAlnet09_ALL
473	ReAlnet04_cornet
474	resnet50_primary_visual_cortex
475	ReAlnet10_ALL
476	resnet18_fair
477	pr1_stl10_disentangled_alpha04
478	yudixie_wbh_object_class_scaling_0415_run_0
479	yudixie_wbh_object_class_scaling_0415_run_3
480	yudixie_wbh_object_class_scaling_0415_imagenet
481	yudixie_wbh_object_class_scaling_0415_run_2
482	yudixie_wbh_object_class_scaling_0415_run_1
483	deepeisnn_ei_cifar10_vgg19
484	deepeisnn_ei_cifar10_resnet18
485	deepeisnn_ei_imagenet_resnet18
486	dinov2_vitl14_reg_lc_featread
487	gabor_filter_entropy_4x4
488	gabor_filter_mean_abs_4x4_v2
489	gabor_filter_entropy_4x4_v2
490	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

0.51.

Note that scores are relative to this ceiling.

Data: Geirhos2021powerequalisation

Metric: error_consistency