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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	inception_v4-tf	.411
91	resnet50_st_wzc_seed6_2_323	.411
92	convnext_femto_ols:d1_in1k	.409
93	inception_v3	.405
94	resnet101_imagenet_full	.405
95	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.400
96	convnext_tiny_imagenet_full_seed-0	.395
97	efficientnet-b7	.392
98	inception_v3-tf	.391
99	resnet50-SIN_IN	.389
100	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.381
101	grcnn_109	.370
102	efficientnet_b0	.369
103	densenet-201-keras	.365
104	resnet50	.362
105	resnet_101_v1	.358
106	antialiased-rnext101_32x8d	.358
107	resnet50_random_l2_perturb	.351
108	focalnet_tiny_lrf_in1k	.346
109	densenet-201	.342
110	resnet50_ewconplus_wzc_seed6_2_323	.341
111	grcnn	.340
112	resnet50_st_wzc_2	.328
113	tv_efficientnet-b1	.324
114	densenet-121	.322
115	texture_shape_resnet50_trained_on_SIN	.321
116	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.320
117	densenet-121-keras	.319
118	custom_model_cv_18_dagger_408	.319
119	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.317
120	ReAlnet01	.315
121	ReAlnet03	.315
122	AT_efficientnet-b2	.315
123	AdvProp_efficientnet-b2	.315
124	deit_large_imagenet_full_seed-0	.314
125	resnet50_byol	.314
126	Res2Net50_26w_4s	.313
127	cvt_cvt-21-224-in1k_4_LucyV4	.311
128	ReAlnet09	.307
129	ReAlnet02	.305
130	AdvProp_efficientnet-b8	.303
131	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.302
132	voneresnet-50-non_stochastic	.301
133	ReAlnet04	.300
134	resnet34_imagenet_full	.299
135	cornet_s	.299
136	inception_v1	.298
137	ReAlnet06	.297
138	convnext_tiny:in12k_ft_in1k	.295
139	resnet50-moclr8deg	.295
140	BiT-S-R152x4	.293
141	resnet18_imagenet_full	.292
142	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.290
143	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.289
144	mobilenet_v2_1.4_224-tf	.288
145	resnet50_hvs_wzc	.285
146	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.281
147	antialiased-r50	.281
148	mobilenet_v2_1_0_224	.278
149	resnet50-SIN_IN_IN	.274
150	resnet_SIN_IN_FT_IN	.274
151	densenet-169	.273
152	resnet50_moco_v2	.272
153	ReAlnet08	.271
154	inception_v2-tf	.270
155	ReAlnet07	.267
156	inception_v1-tf	.266
157	vgg_19	.263
158	ReAlnet10	.263
159	densenet-169-keras	.262
160	resnet50_random_linf8_perturb	.262
161	vonegrcnn_47e	.258
162	nasnet_mobile	.255
163	resnet50_tutorial	.254
164	resnet_50_v1	.254
165	resnet-50-pytorch	.254
166	resnet50-sup	.254
167	resnet50-vitoimagevidnet8	.252
168	ReAlnet05	.251
169	BiT-S-R101x3	.251
170	alexnet_fov4	.243
171	CORnet-S	.236
172	resnet_50_v1_spiking	.233
173	resnet-50_v1-tf	.233
174	vonegrcnn_62e_nobn	.232
175	BiT-S-R50x3	.230
176	resnet-34	.229
177	eicircuit_resnet18_bn_20260919	.229
178	vonegrcnn_52e_full	.229
179	resnet50_simclr	.224
180	BiT-S-R152x2	.223
181	voneresnet-50-robust	.219
182	BiT-S-R50x1	.218
183	mobilenet_v2_1_3_224	.216
184	vonegrcnn_62e_nobn	.213
185	mobilenet_v2_1_0_192	.208
186	vonegrcnn_47e	.202
187	efficientnet_b2_imagenet_full	.202
188	mobilenet_v2_1.0_224-tf	.201
189	resnet-18	.199
190	alexnet_training_seed_02	.198
191	alexnet_training_seed_04	.198
192	alexnet_training_seed_08	.198
193	alexnet_training_seed_10	.198
194	resnet-101_v1-tf	.197
195	resnet-152_v1-tf	.195
196	resnet50_linf_4_robust	.195
197	BiT-S-R101x1	.194
198	artResNet18_1	.192
199	vgg_16	.192
200	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.191
201	resnet50-SIN	.187
202	deit_base_imagenet_full_seed-0	.185
203	nasnet_mobile-tf	.185
204	vonegrcnn_52e_full	.184
205	vonealexnet_gaussian_noise_std4_fixed	.182
206	mobilenet_v2_1-4_224_pytorch	.181
207	mobilenet_v2_1_4_224	.181
208	mobilenet_v2_1.3_224-tf	.176
209	alexnet_training_seed_07	.166
210	resnet50-simclr-vissl	.166
211	resnet50_robust_l2_eps1	.163
212	mobilenet_v2_1_0_160	.160
213	resnet50_eMMCR_Vanilla	.159
214	efficientnet_b1_imagenet_full	.159
215	resnet50_imagenet_100_seed-0	.157
216	mobilenet_v1_0.75_224	.155
217	voneresnet-50	.154
218	resnet50-vicregl0p9	.146
219	seresnext50_32x4d	.146
220	mobilenet_v2_0_5_224	.145
221	AlexNet_SIN	.141
222	alexnet_ks_torevert	.139
223	alexnet	.139
224	vgg-19-keras	.134
225	texture_shape_alexnet_trained_on_SIN	.133
226	alexnet_linf_8_robust	.131
227	deit_small_imagenet_full_seed-0	.131
228	blt_vs	.129
229	resnet-50_untrained	.127
230	resnet50-vicregl0p75	.127
231	mobilenet_v2_0.75_128	.123
232	resnet50_l2_3_robust	.121
233	regnet_y_400mf	.121
234	efficientnet_b0_imagenet_full	.120
235	mobilenet_v1_1.0_192	.119
236	resnet50-barlow	.119
237	mobilenet_v2_0_75_192	.116
238	AdvProp_efficientnet-b0	.114
239	alexnet_random_linf8_perturb	.113
240	mobilenet_v2_0.75_224-tf	.111
241	mobilenet_v1_0.75_192	.110
242	mobilenet_v2_0.5_192-tf	.110
243	alexnet_robust_correct	.107
244	alexnet_random_l2_3_perturb	.107
245	mobilenet_v2_1_0_128	.106
246	mobilenet_v1_0.5_192	.106
247	alexnet_l2_3_robust	.103
248	mobilenet_v1_1.0_224	.103
249	vgg-16-keras	.102
250	resnet50_imagenet_10_seed-0	.100
251	mobilenet_v2_1.0_192-tf	.098
252	mobilenet_v2_0_75_160	.097
253	konkle_alexnetgn_ipcl_ref01_primary_model	.097
254	alexnet_reduced_aliasing_early_checkpoint	.097
255	imagenet_l2_10_0	.097
256	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.096
257	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.096
258	resnet50_linf_8_robust	.094
259	mobilenet_v1_1.0_160	.094
260	alexnet_training_seed_05	.093
261	alexnet_training_seed_01	.093
262	alexnet_training_seed_01_fov4	.093
263	alexnet_training_seed_01_fov12	.093
264	alexnet_training_seed_01_fov16	.093
265	mobilenet_v2_1.0_160-tf	.092
266	mobilenet_v2_0.5_224-tf	.090
267	mobilenet_v2_0_75_224	.089
268	convnext_small_imagenet_1_seed-0	.088
269	mobilenet_v2_0.35_96	.088
270	mobilenet_v1_0.25_128	.087
271	mobilenet_v2_0_5_192	.087
272	resnet50_imagenet_1_seed-0	.086
273	resnet-50-robust	.084
274	imagenet_l2_3_0	.084
275	resnet50_robust_l2_eps3	.084
276	convnext_tiny_sup	.080
277	mobilenet_v2_0.35_224	.079
278	alexnet_fov12	.078
279	mobilenet_v2_0.35_160	.078
280	mobilenet_v2_1.0_96	.078
281	resnet_50_v1_spiking_l3	.075
282	AlexNet_SIN_fov12	.075
283	mobilenet_v2_0.75_96	.074
284	alexnet_early_checkpoint	.070
285	alexnet_fov16	.067
286	squeezenet1_1	.066
287	mobilenet_v2_0.5_128	.065
288	convnext_small_imagenet_100_seed-0	.064
289	mobilenet_v2_0.75_192-tf	.064
290	mobilevit_small	.064
291	mobilenet_v2_0.75_160-tf	.062
292	mobilenet_v2_0.5_96	.061
293	mobilenet_v1_0.25_224	.060
294	AlexNet_SIN_fov16	.060
295	resnet50_FractalDB	.057
296	deit_small_imagenet_100_seed-0	.057
297	mobilenet_v2_0.5_160	.049
298	deit_small_imagenet_1_seed-0	.047
299	shufflenet_v2_x1_0	.046
300	alexnet_training_seed_09	.045
301	deit_small_imagenet_10_seed-0	.045
302	alexnet_training_seed_03	.044
303	mobilenet_v2_0.35_192	.040
304	mobilenet_v1_0.25_160	.040
305	convnext_small_imagenet_10_seed-0	.040
306	mobilenet_v1_1.0_128	.038
307	mobilenet_v2_1.0_128-tf	.037
308	mobilenet_v1_0.5_160	.028
309	squeezenet1_0	.026
310	mobilenet_v2_0.35_128	.026
311	0.5x_resnet-18_LC_w_sh_1_iter	.025
312	resnet_50_v1_spiking_l4	.016
313	resnet50-vicreg	.016
314	mobilenet_v1_0.25_192	.015
315	mobilenet_v1_0.5_128	.015
316	mobilenet_v1_0.5_224	.015
317	mobilenet_v1_0.75_160	.014
318	barlow-twins-resnet50	.012
319	mobilenet_v1_0.75_128	.012
320	alexnet_training_seed_06	.008
321	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.006
322	resnet_50_v1_spiking_l4a	.005
323	resnet-18-LC_w_sh_100_iter_conv_init_m
324	ViT-B/32
325	BiT-M-R50x3
326	BiT-M-R50x1
327	BiT-M-R152x2
328	resnet-18-LC_w_sh_1_iter_conv_init_m
329	resnet-18-LC_w_sh_1_iter_m
330	resnet-18-LC_w_sh_10_iter_m
331	resnet-18-LC_w_sh_100_iter_m
332	resnet-18-LC_w_sh_10_iter_conv_init_m
333	FrankRobWobv0
334	0.5x_resnet-18_LC
335	CORnetZ_CIFAR10
336	resnet18-local_aggregation
337	resnet18-deepcluster
338	r3m_resnet18
339	CORnet-Z
340	vggface
341	my-model
342	resnet18-instance_recognition
343	0.5x_resnet-18_LC_w_sh_10_iter
344	r3m_resnet50
345	r3m_resnet34
346	resnet-18-LC_m
347	r3m_resnet50_nocrop
348	resnet18-supervised
349	resnet-18-LC_1st_conv_m
350	resnet-18-LC_conv_init_m
351	resnet18-contrastive_multiview
352	0.5x_resnet-18
353	RN50
354	0.5x_resnet-18_LC_w_sh_100_iter
355	RN50
356	resnet18-colorization
357	resnet18-relative_position
358	resnet18-autoencoder
359	resnet18-simclr
360	ViT_L_32
361	omnivore_swinT
362	ViT_B_32
363	resnet18-depth_prediction
364	ViT_B_16
365	r3m_resnet34_nocrop
366	hmax
367	resnet18-contrastive_predictive
368	resnet-18-LC_untrained
369	resnet-18_untrained
370	resnet-50x2_untrained
371	dcgan
372	unet_entire
373	v1-pyr-nodown
374	CORnetZ_CIFAR10_bs32_20_04
375	pixels
376	dorinet_cornet_z
377	my-model
378	openclip
379	resnet50-cifar
380	resnet50_pretrained_with_retinal_waves
381	resnet50_ImageNet
382	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
383	yudixie_resnet50_imagenet1kpret_0_240908
384	yudixie_resnet50_random_0_240908
385	yudixie_resnet50_imagenet1kpret_0_240312
386	yudixie_resnet50_object_class_0_240908
387	yudixie_resnet50_category_class_0_240908
388	yudixie_resnet50_distance_reg_0_240908
389	ConvLSTM
390	PredRNN
391	SimVP
392	TAU
393	MIM
394	resnet-152_v2_pytorch
395	briaai_rmbg_1_4
396	densenet_201_pytorch
397	pnasnet_large_pytorch
398	inception_v3_pytorch
399	compact_resnet50_V4
400	yudixie_resnet18_translation_reg_0_240719
401	yudixie_resnet18_distance_reg_0_240719
402	yolos_tiny
403	yudixie_resnet18_rotation_reg_0_240719
404	ReAlnet03_cornet
405	yudixie_resnet18_imagenet1kpret_0_240719
406	eBarlow_lmda_02_1000ep
407	vit_base_patch14_reg4_dinov2-lvd142m
408	vit_base_patch16_dinov3-lvd1689m
409	resnet18_ecoset_full
410	ReAlnet02_cornet
411	resnet34_ecoset_full
412	compact_resnet50_IT
413	VOneCORnet-S
414	resnet50_ecoset_full
415	ReAlnet01_cornet_fov4
416	compact_resnet50_robust_V4
417	resnet101_ecoset_full
418	ReAlnet04_cornet
419	resnet152_ecoset_full
420	vit_base_patch14_dinov2-lvd142m
421	yudixie_resnet50_distance_translation_0_240908
422	ReAlnet01_cornet_fov12
423	yudixie_resnet18_translation_rotation_0_240719
424	yudixie_resnet18_distance_rotation_0_240719
425	ReAlnet05_cornet
426	yudixie_resnet50_distance_rotation_0_240908
427	yudixie_resnet18_cat_obj_class_all_latents_0_240719
428	compact_vgg19_V4
429	resnet-18_test_m
430	SeLaVi-AVE
431	yudixie_resnet18_distance_translation_rotation_0_240719
432	yudixie_resnet18_object_class_0_240719
433	ReAlnet06_cornet
434	r3d_18
435	yudixie_resnet50_translation_reg_0_240908
436	compact_vgg19_IT
437	yudixie_resnet50_rotation_reg_0_240908
438	yudixie_resnet50_translation_rotation_0_240908
439	ReAlnet01_ALL
440	mc3_18
441	ReAlnet07_cornet
442	s3d
443	ReAlnet08_cornet
444	mvit_v1_b
445	ReAlnet01_cornet_fov16
446	ReAlnet02_ALL
447	compact_cornets_IT
448	omnivore_swinB
449	resnet18_imagenet21kP
450	ReAlnet03_ALL
451	compact_cornets_V4
452	ReAlnet09_cornet
453	ReAlnet04_ALL
454	SeLaVi-Kinetics400
455	SeLaVi-VGG-Sound
456	ReAlnet05_ALL
457	r2plus1d_18
458	omnivore_swinS
459	ReAlnet06_ALL
460	ReAlnet10_cornet
461	SeLaVi-Kinetics-Sound
462	mvit_v2_s
463	compact_resnet50_robust_IT
464	ReAlnet07_ALL
465	yudixie_resnet18_category_class_0_240719
466	ReAlnet08_ALL
467	yudixie_resnet18_distance_translation_0_240719
468	yudixie_resnet18_random_0_240719
469	ReAlnet01_cornet
470	resnet50_primary_visual_cortex
471	ReAlnet09_ALL
472	yudixie_resnet50_distance_translation_rotation_0_240908
473	yudixie_resnet50_cat_obj_class_all_latents_0_240908
474	ReAlnet10_ALL
475	resnet18_fair
476	pr1_stl10_disentangled_alpha04
477	predictive_coding_pc
478	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
479	yudixie_wbh_object_class_scaling_0415_run_0
480	yudixie_wbh_object_class_scaling_0415_run_3
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

0.50.

Note that scores are relative to this ceiling.

Data: Geirhos2021stylized

Metric: error_consistency