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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021stylized-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnext101_32x32d_wsl	.871
2	resnext101_32x16d_wsl	.859
3	resnext101_32x48d_wsl	.851
4	fixres_resnext101_32x48d_wsl	.830
5	dinov2_vitl14_lc	.791
6	vit_huge_clip336_laion	.788
7	SWSL_resnext101_32x8d	.787
8	convnext_large_in22k_supervised	.783
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.758
10	dinov2_vitg14_reg_lc	.755
11	dinov2_vitl14_lc_res336	.755
12	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.751
13	convnext_base:clip_laiona_augreg_ft_in1k_384	.750
14	convnext_xlarge:fb_in22k_ft_in1k	.746
15	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.737
16	dinov2_vitg14_lc	.735
17	vit_large_patch14_clip_336:laion2b_ft_in1k	.734
18	dinov2_vitl14_reg_lc	.729
19	convnext_xxlarge_clip	.727
20	vit_large_patch14_clip_224:laion2b_ft_in1k	.723
21	vit_large_clip336_openai	.720
22	convnext_large_clip_laion2b_finelayers	.717
23	vit_base_patch16_clip_224:openai_ft_in1k	.708
24	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.706
25	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.705
26	vision_transformer_vit_large_patch16_224	.705
27	convnext_large:fb_in22k_ft_in1k	.704
28	SWSL_resnet50	.702
29	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.697
30	vit_large_patch14_clip_224:openai_ft_in1k	.697
31	effnetb1_272x240	.693
32	effnetv2m_custom384	.680
33	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.680
34	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.678
35	cvt_cvt-13-384-in1k_4_LucyV4	.678
36	resnext101_32x8d_wsl	.666
37	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.654
38	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.653
39	eva02_large_in22k	.651
40	CLIP_resnet50	.646
41	CLIP_resnet50_float32	.646
42	nasnet_large	.646
43	cvt_cvt-21-384-in1k_4_LucyV4	.646
44	CLIP_ViT-B_32	.628
45	pnasnet_large_halfPrecision	.627
46	pnasnet_large	.627
47	resnet_101_v2	.623
48	convnext_base_fb_in22k_ft_in1k	.617
49	resnet_152_v2	.603
50	cv_18_dagger_408_pretrained	.600
51	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.590
52	resnet-152_v2-tf	.588
53	nasnet_large-tf	.583
54	pnasnet_large-tf	.579
55	ViT_B_16_imagenet1k	.570
56	deit3_base_patch16_224_fb_in1k	.566
57	resnet_50_v2	.555
58	ViT_L_32_imagenet1k	.538
59	vit_relpos_base_patch16_clsgap_224:sw_in1k	.516
60	xception-keras	.515
61	CLIP-RN50	.511
62	regnety_032	.494
63	ViT_B_32_imagenet1k	.494
64	deit3_base_patch16_224_fb_in22k_ft_in1k	.491
65	inception_v4	.488
66	antialias-resnet152	.467
67	resnet50_st_wzc_seed3_2_323	.464
68	AdvProp_efficientnet-b6	.463
69	resnet152_imagenet_full	.457
70	resnet_152_v1	.456
71	resnet50_ewconplus_wzc	.454
72	xception	.450
73	resnet50-VITO-8deg-cc	.449
74	AdvProp_efficientnet-b4	.443
75	AT_efficientnet-b4	.443
76	resnet-50_v2-tf	.439
77	resnet50_imagenet_full	.438
78	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.438
79	resnet50_ewconplus_wzc_seed5_2__323	.434
80	convnext_base_imagenet_full_seed-0	.433
81	convnext_base_fb_in1k	.430
82	AlexNet_SIN_fov4	.430
83	convnext_small_imagenet_full_seed-0	.429
84	AdvProp_efficientnet-b7	.427
85	convnext_base_fb_in1k_gram_aligned_dinov3	.422
86	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.418
87	cvt_cvt-13-224-in1k_4_LucyV4	.417
88	convnext_large_imagenet_full_seed-0	.417
89	resnet101	.417
90	ijepa_vith14_linhead	.413
91	inception_v4-tf	.411
92	resnet50_st_wzc_seed6_2_323	.411
93	convnext_femto_ols:d1_in1k	.409
94	inception_v3	.405
95	resnet101_imagenet_full	.405
96	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.400
97	convnext_tiny_imagenet_full_seed-0	.395
98	efficientnet-b7	.392
99	inception_v3-tf	.391
100	resnet50-SIN_IN	.389
101	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.381
102	mehrer2020_alexnet_training_seed_01_fov4	.371
103	grcnn_109	.370
104	efficientnet_b0	.369
105	densenet-201-keras	.365
106	resnet50	.362
107	resnet_101_v1	.358
108	antialiased-rnext101_32x8d	.358
109	resnet50_random_l2_perturb	.351
110	focalnet_tiny_lrf_in1k	.346
111	densenet-201	.342
112	resnet50_ewconplus_wzc_seed6_2_323	.341
113	grcnn	.340
114	resnet50_st_wzc_2	.328
115	tv_efficientnet-b1	.324
116	densenet-121	.322
117	texture_shape_resnet50_trained_on_SIN	.321
118	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.320
119	densenet-121-keras	.319
120	custom_model_cv_18_dagger_408	.319
121	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.317
122	ReAlnet01	.315
123	ReAlnet03	.315
124	AT_efficientnet-b2	.315
125	AdvProp_efficientnet-b2	.315
126	deit_large_imagenet_full_seed-0	.314
127	resnet50_byol	.314
128	Res2Net50_26w_4s	.313
129	cvt_cvt-21-224-in1k_4_LucyV4	.311
130	ReAlnet09	.307
131	ReAlnet02	.305
132	AdvProp_efficientnet-b8	.303
133	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.302
134	voneresnet-50-non_stochastic	.301
135	ReAlnet04	.300
136	resnet34_imagenet_full	.299
137	cornet_s	.299
138	inception_v1	.298
139	ReAlnet06	.297
140	convnext_tiny:in12k_ft_in1k	.295
141	resnet50-moclr8deg	.295
142	BiT-S-R152x4	.293
143	resnet18_imagenet_full	.292
144	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.290
145	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.289
146	mobilenet_v2_1.4_224-tf	.288
147	resnet50_hvs_wzc	.285
148	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.281
149	antialiased-r50	.281
150	mobilenet_v2_1_0_224	.278
151	resnet50-SIN_IN_IN	.274
152	resnet_SIN_IN_FT_IN	.274
153	densenet-169	.273
154	resnet50_moco_v2	.272
155	ReAlnet08	.271
156	inception_v2-tf	.270
157	ReAlnet07	.267
158	inception_v1-tf	.266
159	vgg_19	.263
160	ReAlnet10	.263
161	densenet-169-keras	.262
162	resnet50_random_linf8_perturb	.262
163	vonegrcnn_47e	.258
164	nasnet_mobile	.255
165	resnet50_tutorial	.254
166	resnet_50_v1	.254
167	resnet-50-pytorch	.254
168	resnet50-sup	.254
169	resnet50-vitoimagevidnet8	.252
170	ReAlnet05	.251
171	BiT-S-R101x3	.251
172	alexnet_fov4	.243
173	CORnet-S	.236
174	resnet_50_v1_spiking	.233
175	resnet-50_v1-tf	.233
176	vonegrcnn_62e_nobn	.232
177	BiT-S-R50x3	.230
178	resnet-34	.229
179	eicircuit_resnet18_bn_20260919	.229
180	vonegrcnn_52e_full	.229
181	resnet50_simclr	.224
182	BiT-S-R152x2	.223
183	voneresnet-50-robust	.219
184	BiT-S-R50x1	.218
185	mobilenet_v2_1_3_224	.216
186	vonegrcnn_62e_nobn	.213
187	mobilenet_v2_1_0_192	.208
188	vonegrcnn_47e	.202
189	efficientnet_b2_imagenet_full	.202
190	mobilenet_v2_1.0_224-tf	.201
191	resnet-18	.199
192	alexnet_training_seed_02	.198
193	alexnet_training_seed_04	.198
194	alexnet_training_seed_08	.198
195	alexnet_training_seed_10	.198
196	resnet-101_v1-tf	.197
197	resnet-152_v1-tf	.195
198	resnet50_linf_4_robust	.195
199	BiT-S-R101x1	.194
200	artResNet18_1	.192
201	vgg_16	.192
202	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.191
203	resnet50-SIN	.187
204	deit_base_imagenet_full_seed-0	.185
205	nasnet_mobile-tf	.185
206	vonegrcnn_52e_full	.184
207	vonealexnet_gaussian_noise_std4_fixed	.182
208	resnet50_simsiam_linhead	.182
209	mobilenet_v2_1-4_224_pytorch	.181
210	mobilenet_v2_1_4_224	.181
211	resnet50_byol_linhead	.176
212	mobilenet_v2_1.3_224-tf	.176
213	alexnet_training_seed_07	.166
214	resnet50-simclr-vissl	.166
215	resnet50_robust_l2_eps1	.163
216	mobilenet_v2_1_0_160	.160
217	resnet50_eMMCR_Vanilla	.159
218	efficientnet_b1_imagenet_full	.159
219	resnet50_simclr_linhead_01norm	.158
220	resnet50_imagenet_100_seed-0	.157
221	mobilenet_v1_0.75_224	.155
222	voneresnet-50	.154
223	resnet50-vicregl0p9	.146
224	seresnext50_32x4d	.146
225	mobilenet_v2_0_5_224	.145
226	AlexNet_SIN	.141
227	alexnet_ks_torevert	.139
228	alexnet	.139
229	vgg-19-keras	.134
230	texture_shape_alexnet_trained_on_SIN	.133
231	alexnet_linf_8_robust	.131
232	deit_small_imagenet_full_seed-0	.131
233	blt_vs	.129
234	resnet-50_untrained	.127
235	resnet50-vicregl0p75	.127
236	mobilenet_v2_0.75_128	.123
237	resnet50_l2_3_robust	.121
238	regnet_y_400mf	.121
239	efficientnet_b0_imagenet_full	.120
240	mobilenet_v1_1.0_192	.119
241	resnet50-barlow	.119
242	mobilenet_v2_0_75_192	.116
243	AdvProp_efficientnet-b0	.114
244	alexnet_random_linf8_perturb	.113
245	mobilenet_v2_0.75_224-tf	.111
246	mobilenet_v1_0.75_192	.110
247	mobilenet_v2_0.5_192-tf	.110
248	resnet50_barlowtwins_linhead	.110
249	mehrer2020_alexnet_training_seed_03	.108
250	alexnet_robust_correct	.107
251	alexnet_random_l2_3_perturb	.107
252	mobilenet_v2_1_0_128	.106
253	mobilenet_v1_0.5_192	.106
254	resnet50_vicreg_linhead	.105
255	mehrer2020_alexnet_training_seed_04	.103
256	alexnet_l2_3_robust	.103
257	mobilenet_v1_1.0_224	.103
258	vgg-16-keras	.102
259	resnet50_imagenet_10_seed-0	.100
260	mobilenet_v2_1.0_192-tf	.098
261	mobilenet_v2_0_75_160	.097
262	konkle_alexnetgn_ipcl_ref01_primary_model	.097
263	alexnet_reduced_aliasing_early_checkpoint	.097
264	imagenet_l2_10_0	.097
265	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.096
266	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.096
267	resnet50_linf_8_robust	.094
268	mobilenet_v1_1.0_160	.094
269	alexnet_training_seed_05	.093
270	alexnet_training_seed_01	.093
271	alexnet_training_seed_01_fov4	.093
272	alexnet_training_seed_01_fov12	.093
273	alexnet_training_seed_01_fov16	.093
274	mobilenet_v2_1.0_160-tf	.092
275	mobilenet_v2_0.5_224-tf	.090
276	mobilenet_v2_0_75_224	.089
277	convnext_small_imagenet_1_seed-0	.088
278	mehrer2020_alexnet_training_seed_02	.088
279	mobilenet_v2_0.35_96	.088
280	mobilenet_v1_0.25_128	.087
281	mobilenet_v2_0_5_192	.087
282	mehrer2020_alexnet_training_seed_05	.087
283	resnet50_imagenet_1_seed-0	.086
284	resnet-50-robust	.084
285	imagenet_l2_3_0	.084
286	resnet50_robust_l2_eps3	.084
287	convnext_tiny_sup	.080
288	mobilenet_v2_0.35_224	.079
289	alexnet_fov12	.078
290	mobilenet_v2_0.35_160	.078
291	mehrer2020_alexnet_training_seed_01	.078
292	mobilenet_v2_1.0_96	.078
293	mehrer2020_alexnet_training_seed_01_fov12	.077
294	resnet_50_v1_spiking_l3	.075
295	AlexNet_SIN_fov12	.075
296	mobilenet_v2_0.75_96	.074
297	alexnet_early_checkpoint	.070
298	alexnet_fov16	.067
299	squeezenet1_1	.066
300	mobilenet_v2_0.5_128	.065
301	convnext_small_imagenet_100_seed-0	.064
302	mobilenet_v2_0.75_192-tf	.064
303	mobilevit_small	.064
304	mobilenet_v2_0.75_160-tf	.062
305	mobilenet_v2_0.5_96	.061
306	mobilenet_v1_0.25_224	.060
307	AlexNet_SIN_fov16	.060
308	resnet50_FractalDB	.057
309	deit_small_imagenet_100_seed-0	.057
310	mobilenet_v2_0.5_160	.049
311	deit_small_imagenet_1_seed-0	.047
312	shufflenet_v2_x1_0	.046
313	alexnet_training_seed_09	.045
314	deit_small_imagenet_10_seed-0	.045
315	alexnet_training_seed_03	.044
316	mobilenet_v2_0.35_192	.040
317	mobilenet_v1_0.25_160	.040
318	convnext_small_imagenet_10_seed-0	.040
319	mobilenet_v1_1.0_128	.038
320	mobilenet_v2_1.0_128-tf	.037
321	mobilenet_v1_0.5_160	.028
322	squeezenet1_0	.026
323	mobilenet_v2_0.35_128	.026
324	0.5x_resnet-18_LC_w_sh_1_iter	.025
325	mehrer2020_alexnet_training_seed_01_fov16	.021
326	resnet_50_v1_spiking_l4	.016
327	resnet50-vicreg	.016
328	mobilenet_v1_0.25_192	.015
329	mobilenet_v1_0.5_128	.015
330	mobilenet_v1_0.5_224	.015
331	mobilenet_v1_0.75_160	.014
332	barlow-twins-resnet50	.012
333	mobilenet_v1_0.75_128	.012
334	alexnet_training_seed_06	.008
335	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.006
336	resnet_50_v1_spiking_l4a	.005
337	resnet-18-LC_w_sh_100_iter_conv_init_m
338	ViT-B/32
339	BiT-M-R50x3
340	BiT-M-R50x1
341	BiT-M-R152x2
342	resnet-18-LC_w_sh_1_iter_conv_init_m
343	resnet-18-LC_w_sh_1_iter_m
344	resnet-18-LC_w_sh_10_iter_m
345	resnet-18-LC_w_sh_100_iter_m
346	resnet-18-LC_w_sh_10_iter_conv_init_m
347	FrankRobWobv0
348	0.5x_resnet-18_LC
349	CORnetZ_CIFAR10
350	resnet18-local_aggregation
351	resnet18-deepcluster
352	r3m_resnet18
353	CORnet-Z
354	vggface
355	my-model
356	resnet18-instance_recognition
357	0.5x_resnet-18_LC_w_sh_10_iter
358	r3m_resnet50
359	r3m_resnet34
360	resnet-18-LC_m
361	r3m_resnet50_nocrop
362	resnet18-supervised
363	resnet-18-LC_1st_conv_m
364	resnet-18-LC_conv_init_m
365	resnet18-contrastive_multiview
366	0.5x_resnet-18
367	RN50
368	0.5x_resnet-18_LC_w_sh_100_iter
369	RN50
370	resnet18-colorization
371	resnet18-relative_position
372	resnet18-autoencoder
373	resnet18-simclr
374	ViT_L_32
375	omnivore_swinT
376	ViT_B_32
377	resnet18-depth_prediction
378	ViT_B_16
379	r3m_resnet34_nocrop
380	hmax
381	resnet18-contrastive_predictive
382	resnet-18-LC_untrained
383	resnet-18_untrained
384	resnet-50x2_untrained
385	dcgan
386	unet_entire
387	v1-pyr-nodown
388	CORnetZ_CIFAR10_bs32_20_04
389	pixels
390	dorinet_cornet_z
391	my-model
392	openclip
393	resnet50-cifar
394	resnet50_pretrained_with_retinal_waves
395	resnet50_ImageNet
396	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
397	yudixie_resnet50_imagenet1kpret_0_240908
398	yudixie_resnet50_random_0_240908
399	yudixie_resnet50_imagenet1kpret_0_240312
400	yudixie_resnet50_object_class_0_240908
401	yudixie_resnet50_category_class_0_240908
402	yudixie_resnet50_distance_reg_0_240908
403	ConvLSTM
404	PredRNN
405	SimVP
406	TAU
407	MIM
408	resnet-152_v2_pytorch
409	briaai_rmbg_1_4
410	densenet_201_pytorch
411	pnasnet_large_pytorch
412	inception_v3_pytorch
413	compact_resnet50_V4
414	yudixie_resnet18_translation_reg_0_240719
415	yudixie_resnet18_distance_reg_0_240719
416	yolos_tiny
417	yudixie_resnet18_rotation_reg_0_240719
418	ReAlnet03_cornet
419	yudixie_resnet18_imagenet1kpret_0_240719
420	eBarlow_lmda_02_1000ep
421	vit_base_patch14_reg4_dinov2-lvd142m
422	vit_base_patch16_dinov3-lvd1689m
423	resnet18_ecoset_full
424	resnet34_ecoset_full
425	compact_resnet50_IT
426	VOneCORnet-S
427	resnet50_ecoset_full
428	ReAlnet01_cornet_fov4
429	compact_resnet50_robust_V4
430	resnet101_ecoset_full
431	ReAlnet04_cornet
432	resnet152_ecoset_full
433	vit_base_patch14_dinov2-lvd142m
434	yudixie_resnet50_distance_translation_0_240908
435	ReAlnet01_cornet_fov12
436	yudixie_resnet18_translation_rotation_0_240719
437	yudixie_resnet18_distance_rotation_0_240719
438	ReAlnet05_cornet
439	yudixie_resnet50_distance_rotation_0_240908
440	yudixie_resnet18_cat_obj_class_all_latents_0_240719
441	compact_vgg19_V4
442	resnet-18_test_m
443	SeLaVi-AVE
444	yudixie_resnet18_distance_translation_rotation_0_240719
445	yudixie_resnet18_object_class_0_240719
446	r3d_18
447	yudixie_resnet50_translation_reg_0_240908
448	compact_vgg19_IT
449	yudixie_resnet50_rotation_reg_0_240908
450	yudixie_resnet50_translation_rotation_0_240908
451	ReAlnet01_ALL
452	mc3_18
453	s3d
454	ReAlnet08_cornet
455	mvit_v1_b
456	ReAlnet02_ALL
457	compact_cornets_IT
458	omnivore_swinB
459	resnet18_imagenet21kP
460	ReAlnet03_ALL
461	compact_cornets_V4
462	ReAlnet04_ALL
463	SeLaVi-Kinetics400
464	SeLaVi-VGG-Sound
465	ReAlnet05_ALL
466	r2plus1d_18
467	omnivore_swinS
468	ReAlnet06_ALL
469	SeLaVi-Kinetics-Sound
470	mvit_v2_s
471	compact_resnet50_robust_IT
472	ReAlnet07_ALL
473	yudixie_resnet18_category_class_0_240719
474	ReAlnet08_ALL
475	yudixie_resnet18_distance_translation_0_240719
476	yudixie_resnet18_random_0_240719
477	ReAlnet01_cornet
478	resnet50_primary_visual_cortex
479	ReAlnet09_ALL
480	yudixie_resnet50_distance_translation_rotation_0_240908
481	yudixie_resnet50_cat_obj_class_all_latents_0_240908
482	ReAlnet10_ALL
483	ReAlnet01_cornet_fov16
484	ReAlnet02_cornet
485	ReAlnet06_cornet
486	ReAlnet07_cornet
487	ReAlnet09_cornet
488	ReAlnet10_cornet
489	resnet18_fair
490	pr1_stl10_disentangled_alpha04
491	predictive_coding_pc
492	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
493	yudixie_wbh_object_class_scaling_0415_run_0
494	yudixie_wbh_object_class_scaling_0415_run_3
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

0.50.

Note that scores are relative to this ceiling.

Data: Geirhos2021stylized

Metric: error_consistency