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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	mehrer2020_alexnet_training_seed_01_fov4	.215
101	ijepa_vith14_linhead	.214
102	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.214
103	inception_v4-tf	.209
104	convnext_base_fb_in1k_gram_aligned_dinov3	.206
105	resnet50_st_wzc_seed3_2_323	.203
106	grcnn_109	.201
107	resnet50_ewconplus_wzc_seed2_2__323	.197
108	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.197
109	vgg_19	.195
110	Res2Net50_26w_4s	.193
111	AdvProp_efficientnet-b7	.190
112	AdvProp_efficientnet-b4	.189
113	AT_efficientnet-b4	.189
114	AdvProp_efficientnet-b6	.187
115	AT_efficientnet-b2	.186
116	AdvProp_efficientnet-b2	.186
117	resnet50	.185
118	xception	.184
119	resnet50_linf_4_robust	.182
120	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.182
121	efficientnet_b0	.181
122	resnet_50_v1_spiking	.181
123	resnet50_ewconplus_wzc	.174
124	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.173
125	AlexNet_SIN_fov4	.172
126	deit_base_imagenet_full_seed-0	.169
127	convnext_small_imagenet_100_seed-0	.167
128	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.164
129	resnet50_st_wzc_2	.163
130	resnet50-moclr8deg	.159
131	resnet-50_v2-tf	.155
132	antialiased-rnext101_32x8d	.149
133	densenet-121-keras	.147
134	custom_model_cv_18_dagger_408	.145
135	inception_v2-tf	.145
136	alexnet_random_linf8_perturb	.140
137	resnet50_hvs_wzc	.136
138	resnet50_byol	.134
139	pnasnet_large_pytorch	.133
140	resnet50-SIN_IN_IN	.132
141	resnet_SIN_IN_FT_IN	.132
142	alexnet_fov4	.132
143	BiT-S-R50x3	.128
144	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.127
145	antialiased-r50	.127
146	resnet34_imagenet_full	.126
147	grcnn	.125
148	densenet-201	.125
149	densenet_201_pytorch	.125
150	voneresnet-50-robust	.122
151	ReAlnet03	.121
152	densenet-121	.119
153	resnet50_linf_8_robust	.119
154	ReAlnet04	.118
155	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.116
156	ReAlnet08	.115
157	efficientnet-b7	.114
158	vgg_16	.113
159	densenet-201-keras	.112
160	voneresnet-50-non_stochastic	.108
161	resnet-50_v1-tf	.107
162	vonealexnet_gaussian_noise_std4_fixed	.105
163	ReAlnet01	.105
164	mehrer2020_alexnet_training_seed_04	.103
165	inception_v1	.100
166	alexnet_l2_3_robust	.098
167	alexnet_random_l2_3_perturb	.098
168	resnet50_tutorial	.098
169	resnet_50_v1	.098
170	resnet-50-pytorch	.098
171	resnet50-sup	.098
172	alexnet_ks_torevert	.097
173	alexnet	.097
174	ReAlnet05	.096
175	densenet-169	.096
176	resnet50_l2_3_robust	.095
177	mehrer2020_alexnet_training_seed_03	.095
178	resnet-152_v1-tf	.094
179	resnet50_moco_v2	.094
180	densenet-169-keras	.094
181	ReAlnet02	.093
182	ReAlnet07	.091
183	mehrer2020_alexnet_training_seed_02	.090
184	tv_efficientnet-b1	.090
185	cornet_s	.089
186	convnext_tiny_sup	.089
187	ReAlnet06	.089
188	vonegrcnn_62e_nobn	.088
189	vonegrcnn_62e_nobn	.088
190	alexnet_reduced_aliasing_early_checkpoint	.088
191	nasnet_mobile-tf	.086
192	alexnet_early_checkpoint	.085
193	deit_small_imagenet_full_seed-0	.084
194	BiT-S-R152x2	.083
195	ReAlnet10	.083
196	vonegrcnn_52e_full	.083
197	alexnet_training_seed_05	.083
198	alexnet_training_seed_01	.083
199	alexnet_training_seed_01_fov4	.083
200	alexnet_training_seed_01_fov12	.083
201	alexnet_training_seed_01_fov16	.083
202	resnet50-vitoimagevidnet8	.082
203	inception_v1-tf	.078
204	barlow-twins-resnet50	.078
205	ReAlnet09	.078
206	resnet-101_v1-tf	.076
207	resnet50_robust_l2_eps1	.075
208	vonegrcnn_47e	.075
209	mehrer2020_alexnet_training_seed_01	.075
210	AdvProp_efficientnet-b8	.073
211	resnet-34	.070
212	vonegrcnn_52e_full	.070
213	alexnet_fov12	.069
214	squeezenet1_1	.068
215	resnet18_imagenet_full	.065
216	vonegrcnn_47e	.065
217	mobilenet_v2_1.0_160-tf	.065
218	resnet50_simclr_linhead_01norm	.064
219	alexnet_robust_correct	.064
220	artResNet18_1	.064
221	resnet50-SIN_IN	.063
222	resnet-50-robust	.062
223	imagenet_l2_3_0	.062
224	resnet50_robust_l2_eps3	.062
225	konkle_alexnetgn_ipcl_ref01_primary_model	.062
226	mehrer2020_alexnet_training_seed_05	.062
227	mobilenet_v2_1_0_192	.060
228	resnet50_simclr	.059
229	mobilenet_v2_1_0_160	.059
230	eBarlow_lmda_02_1000ep	.059
231	BiT-S-R152x4	.057
232	alexnet_training_seed_02	.053
233	alexnet_training_seed_04	.053
234	alexnet_training_seed_08	.053
235	alexnet_training_seed_10	.053
236	vgg-19-keras	.053
237	CORnet-S	.052
238	resnet50_simsiam_linhead	.052
239	eicircuit_resnet18_bn_20260919	.051
240	efficientnet_b2_imagenet_full	.050
241	mobilenet_v1_0.25_128	.048
242	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.048
243	mobilenet_v2_1.0_224-tf	.047
244	vgg-16-keras	.047
245	mobilenet_v2_0_5_192	.046
246	voneresnet-50	.045
247	texture_shape_resnet50_trained_on_SIN	.044
248	mobilenet_v2_0.5_96	.043
249	mobilenet_v1_0.5_160	.041
250	convnext_small_imagenet_1_seed-0	.041
251	AlexNet_SIN_fov12	.040
252	deit_small_imagenet_100_seed-0	.040
253	mobilenet_v2_1_0_224	.040
254	resnet50_imagenet_100_seed-0	.040
255	alexnet_fov16	.040
256	resnet50-SIN	.040
257	mobilenet_v1_0.5_128	.039
258	BiT-S-R101x3	.039
259	resnet50-barlow	.038
260	alexnet_training_seed_07	.038
261	alexnet_training_seed_09	.038
262	AdvProp_efficientnet-b0	.038
263	0.5x_resnet-18_LC_w_sh_1_iter	.038
264	BiT-S-R50x1	.037
265	mobilenet_v2_0.35_192	.037
266	texture_shape_alexnet_trained_on_SIN	.037
267	alexnet_linf_8_robust	.037
268	mobilenet_v2_1-4_224_pytorch	.036
269	mobilenet_v2_1_4_224	.036
270	resnet50_FractalDB	.036
271	resnet50_vicreg_linhead	.035
272	BiT-S-R101x1	.035
273	mobilenet_v1_0.75_192	.035
274	mobilenet_v1_0.5_224	.034
275	mehrer2020_alexnet_training_seed_01_fov12	.034
276	mobilenet_v2_0.5_128	.034
277	mobilenet_v2_0_75_224	.034
278	resnet50_barlowtwins_linhead	.034
279	mobilenet_v1_0.25_192	.033
280	mobilenet_v2_0.35_224	.033
281	resnet50_imagenet_10_seed-0	.033
282	mehrer2020_alexnet_training_seed_01_fov16	.032
283	AlexNet_SIN	.032
284	nasnet_mobile	.032
285	efficientnet_b0_imagenet_full	.031
286	mobilenet_v2_1.0_96	.031
287	deit_small_imagenet_10_seed-0	.031
288	deit_small_imagenet_1_seed-0	.031
289	convnext_small_imagenet_10_seed-0	.031
290	AlexNet_SIN_fov16	.031
291	resnet50-vicregl0p9	.030
292	resnet50-vicregl0p75	.029
293	mobilenet_v2_0.5_192-tf	.028
294	resnet50-vicreg	.027
295	mobilenet_v2_0.75_96	.027
296	mobilenet_v2_1_3_224	.027
297	resnet50_byol_linhead	.026
298	mobilenet_v2_1.0_128-tf	.026
299	resnet-50_untrained	.024
300	mobilenet_v1_0.25_224	.024
301	mobilenet_v2_0.75_224-tf	.023
302	blt_vs	.023
303	mobilenet_v2_0.35_128	.023
304	mobilenet_v1_0.5_192	.021
305	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.021
306	mobilenet_v2_1.4_224-tf	.020
307	mobilenet_v2_0.35_160	.020
308	mobilenet_v2_0_75_160	.019
309	mobilenet_v2_0.75_128	.019
310	mobilenet_v2_0_75_192	.019
311	mobilenet_v2_0.5_160	.018
312	imagenet_l2_10_0	.018
313	mobilenet_v2_1.0_192-tf	.017
314	mobilenet_v1_0.75_160	.016
315	squeezenet1_0	.015
316	shufflenet_v2_x1_0	.015
317	mobilenet_v2_0.35_96	.014
318	alexnet_training_seed_06	.014
319	mobilenet_v2_0.5_224-tf	.014
320	mobilenet_v1_0.75_128	.014
321	resnet50_eMMCR_Vanilla	.013
322	resnet_50_v1_spiking_l4a	.012
323	resnet50_imagenet_1_seed-0	.012
324	mobilenet_v2_0.75_160-tf	.011
325	resnet_50_v1_spiking_l4	.011
326	resnet_50_v1_spiking_l3	.011
327	alexnet_training_seed_03	.010
328	mobilenet_v2_0_5_224	.010
329	mobilevit_small	.010
330	mobilenet_v1_1.0_192	.009
331	resnet50-simclr-vissl	.008
332	mobilenet_v1_0.25_160	.007
333	mobilenet_v1_1.0_128	.006
334	mobilenet_v1_1.0_160	.006
335	mobilenet_v1_1.0_224	.005
336	resnet-18	.004
337	mobilenet_v2_1_0_128	.003
338	mobilenet_v2_1.3_224-tf	.003
339	efficientnet_b1_imagenet_full	.003
340	regnet_y_400mf	.002
341	mobilenet_v2_0.75_192-tf	.002
342	mobilenet_v1_0.75_224	.001
343	my-model	.000
344	resnet-18-LC_w_sh_100_iter_conv_init_m
345	ViT-B/32
346	BiT-M-R50x3
347	BiT-M-R50x1
348	BiT-M-R152x2
349	resnet-18-LC_w_sh_1_iter_conv_init_m
350	resnet-18-LC_w_sh_10_iter_m
351	resnet-18-LC_w_sh_100_iter_m
352	resnet-18-LC_w_sh_10_iter_conv_init_m
353	resnet-18-LC_w_sh_1_iter_m
354	FrankRobWobv0
355	0.5x_resnet-18_LC
356	CORnetZ_CIFAR10
357	resnet18-local_aggregation
358	resnet18-deepcluster
359	r3m_resnet18
360	CORnet-Z
361	resnet18-instance_recognition
362	vggface
363	my-model
364	0.5x_resnet-18_LC_w_sh_10_iter
365	r3m_resnet50
366	r3m_resnet34
367	resnet18-colorization
368	resnet-18-LC_m
369	r3m_resnet50_nocrop
370	resnet18-supervised
371	resnet-18-LC_1st_conv_m
372	resnet-18-LC_conv_init_m
373	resnet18-contrastive_multiview
374	0.5x_resnet-18
375	RN50
376	0.5x_resnet-18_LC_w_sh_100_iter
377	RN50
378	resnet18-relative_position
379	resnet18-autoencoder
380	resnet18-simclr
381	ViT_L_32
382	ViT_B_32
383	resnet18-depth_prediction
384	ViT_B_16
385	r3m_resnet34_nocrop
386	resnet18-contrastive_predictive
387	omnivore_swinT
388	resnet-18-LC_untrained
389	resnet-18_untrained
390	resnet-50x2_untrained
391	dcgan
392	unet_entire
393	v1-pyr-nodown
394	CORnetZ_CIFAR10_bs32_20_04
395	pixels
396	dorinet_cornet_z
397	openclip
398	resnet50-cifar
399	resnet50_pretrained_with_retinal_waves
400	resnet50_ImageNet
401	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
402	yudixie_resnet50_random_0_240908
403	yudixie_resnet50_cat_obj_class_all_latents_0_240908
404	yudixie_resnet50_imagenet1kpret_0_240908
405	yudixie_resnet50_imagenet1kpret_0_240312
406	yudixie_resnet50_object_class_0_240908
407	yudixie_resnet50_category_class_0_240908
408	resnet18_imagenet21kP
409	yudixie_resnet50_distance_reg_0_240908
410	ConvLSTM
411	PredRNN
412	SimVP
413	TAU
414	MIM
415	hmax
416	briaai_rmbg_1_4
417	ReAlnet01_cornet
418	compact_resnet50_V4
419	yudixie_resnet18_translation_reg_0_240719
420	yolos_tiny
421	ReAlnet03_cornet
422	yudixie_resnet18_rotation_reg_0_240719
423	yudixie_resnet18_imagenet1kpret_0_240719
424	ReAlnet02_cornet
425	vit_base_patch14_dinov2-lvd142m
426	resnet18_ecoset_full
427	compact_resnet50_IT
428	resnet50_ecoset_full
429	VOneCORnet-S
430	vit_base_patch14_reg4_dinov2-lvd142m
431	ReAlnet01_cornet_fov12
432	resnet101_ecoset_full
433	yudixie_resnet50_distance_translation_0_240908
434	yudixie_resnet18_distance_translation_0_240719
435	ReAlnet01_cornet_fov4
436	yudixie_resnet18_translation_rotation_0_240719
437	compact_vgg19_V4
438	yudixie_resnet18_distance_rotation_0_240719
439	yudixie_resnet18_category_class_0_240719
440	resnet-18_test_m
441	yudixie_resnet18_cat_obj_class_all_latents_0_240719
442	yudixie_resnet50_rotation_reg_0_240908
443	yudixie_resnet50_distance_rotation_0_240908
444	yudixie_resnet18_object_class_0_240719
445	SeLaVi-AVE
446	ReAlnet05_cornet
447	compact_resnet50_robust_V4
448	compact_vgg19_IT
449	yudixie_resnet50_translation_reg_0_240908
450	r3d_18
451	ReAlnet01_ALL
452	yudixie_resnet18_distance_reg_0_240719
453	yudixie_resnet50_translation_rotation_0_240908
454	omnivore_swinB
455	mc3_18
456	ReAlnet07_cornet
457	s3d
458	ReAlnet02_ALL
459	ReAlnet01_cornet_fov16
460	mvit_v1_b
461	ReAlnet08_cornet
462	ReAlnet04_ALL
463	compact_cornets_V4
464	ReAlnet03_ALL
465	ReAlnet09_cornet
466	SeLaVi-Kinetics400
467	ReAlnet05_ALL
468	compact_cornets_IT
469	SeLaVi-VGG-Sound
470	vit_base_patch16_dinov3-lvd1689m
471	ReAlnet06_ALL
472	SeLaVi-Kinetics-Sound
473	mvit_v2_s
474	omnivore_swinS
475	r2plus1d_18
476	compact_resnet50_robust_IT
477	yudixie_resnet50_distance_translation_rotation_0_240908
478	ReAlnet07_ALL
479	resnet34_ecoset_full
480	ReAlnet08_ALL
481	yudixie_resnet18_random_0_240719
482	yudixie_resnet18_distance_translation_rotation_0_240719
483	ReAlnet09_ALL
484	resnet50_primary_visual_cortex
485	ReAlnet10_ALL
486	ReAlnet04_cornet
487	ReAlnet06_cornet
488	ReAlnet10_cornet
489	resnet152_ecoset_full
490	resnet18_fair
491	pr1_stl10_disentangled_alpha04
492	yudixie_wbh_object_class_scaling_0415_run_0
493	yudixie_wbh_object_class_scaling_0415_run_3
494	yudixie_wbh_object_class_scaling_0415_imagenet
495	yudixie_wbh_object_class_scaling_0415_run_2
496	yudixie_wbh_object_class_scaling_0415_run_1
497	deepeisnn_ei_cifar10_vgg19
498	deepeisnn_ei_cifar10_resnet18
499	deepeisnn_ei_imagenet_resnet18
500	dinov2_vitl14_reg_lc_featread
501	gabor_filter_entropy_4x4
502	gabor_filter_mean_abs_4x4_v2
503	gabor_filter_entropy_4x4_v2
504	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