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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021eidolonIII-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnext101_32x16d_wsl	.726
2	ViT_L_32_imagenet1k	.644
3	resnext101_32x48d_wsl	.641
4	SWSL_resnet50	.638
5	resnext101_32x32d_wsl	.629
6	vision_transformer_vit_large_patch16_224	.610
7	AdvProp_efficientnet-b4	.597
8	AT_efficientnet-b4	.597
9	convnext_base_fb_in22k_ft_in1k	.596
10	ViT_B_16_imagenet1k	.582
11	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.579
12	fixres_resnext101_32x48d_wsl	.578
13	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.574
14	eva02_large_in22k	.569
15	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.569
16	resnext101_32x8d_wsl	.567
17	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.564
18	cvt_cvt-13-224-in1k_4_LucyV4	.561
19	effnetv2m_custom384	.558
20	convnext_xlarge:fb_in22k_ft_in1k	.556
21	AdvProp_efficientnet-b6	.556
22	convnext_small_imagenet_full_seed-0	.554
23	SWSL_resnext101_32x8d	.551
24	focalnet_tiny_lrf_in1k	.550
25	resnet_101_v2	.548
26	convnext_small_imagenet_100_seed-0	.546
27	resnet_50_v2	.541
28	pnasnet_large-tf	.535
29	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.535
30	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.535
31	convnext_large_clip_laion2b_finelayers	.523
32	ijepa_vith14_linhead	.522
33	convnext_tiny_imagenet_full_seed-0	.521
34	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.518
35	resnet101	.517
36	convnext_base:clip_laiona_augreg_ft_in1k_384	.511
37	convnext_base_fb_in1k	.507
38	AdvProp_efficientnet-b7	.505
39	regnety_032	.505
40	convnext_large:fb_in22k_ft_in1k	.502
41	ViT_B_32_imagenet1k	.502
42	convnext_xxlarge_clip	.502
43	pnasnet_large_halfPrecision	.501
44	pnasnet_large	.501
45	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.500
46	effnetb1_272x240	.495
47	cvt_cvt-13-384-in1k_4_LucyV4	.494
48	nasnet_large	.490
49	resnet_152_v2	.489
50	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.489
51	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.484
52	convnext_large_in22k_supervised	.483
53	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.480
54	dinov2_vitl14_reg_lc	.479
55	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.477
56	dinov2_vitl14_lc	.477
57	resnet-152_v2_pytorch	.476
58	resnet152_imagenet_full	.474
59	efficientnet-b7	.473
60	vit_relpos_base_patch16_clsgap_224:sw_in1k	.473
61	antialias-resnet152	.470
62	inception_v4	.469
63	resnet50_st_wzc_seed3_2_323	.468
64	AT_efficientnet-b2	.468
65	AdvProp_efficientnet-b2	.468
66	convnext_tiny:in12k_ft_in1k	.468
67	resnet_101_v1	.465
68	vit_large_patch14_clip_224:laion2b_ft_in1k	.464
69	CLIP-RN50	.464
70	resnet-152_v2-tf	.459
71	resnet50_st_wzc_seed6_2_323	.453
72	convnext_large_imagenet_full_seed-0	.453
73	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.453
74	vit_large_patch14_clip_336:laion2b_ft_in1k	.451
75	inception_v4-tf	.445
76	efficientnet_b0	.444
77	nasnet_large-tf	.443
78	CLIP_ViT-B_32	.442
79	deit_base_imagenet_full_seed-0	.441
80	deit_large_imagenet_full_seed-0	.439
81	vit_large_patch14_clip_224:openai_ft_in1k	.438
82	antialiased-rnext101_32x8d	.437
83	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.433
84	resnet_152_v1	.433
85	cvt_cvt-21-384-in1k_4_LucyV4	.432
86	vit_base_patch16_clip_224:openai_ft_in1k	.432
87	seresnext50_32x4d	.431
88	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.429
89	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.427
90	convnext_femto_ols:d1_in1k	.424
91	BiT-S-R50x3	.423
92	resnet50_ewconplus_wzc_seed5_2__323	.420
93	convnext_base_imagenet_full_seed-0	.418
94	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.416
95	deit_small_imagenet_full_seed-0	.415
96	CLIP_resnet50	.415
97	CLIP_resnet50_float32	.415
98	dinov2_vitg14_lc	.415
99	xception	.412
100	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.412
101	cv_18_dagger_408_pretrained	.400
102	resnet50_ewconplus_wzc_seed6_2_323	.399
103	grcnn_109	.397
104	inception_v3-tf	.395
105	resnet34_imagenet_full	.393
106	vit_large_clip336_openai	.391
107	voneresnet-50-non_stochastic	.391
108	inception_v3	.388
109	Res2Net50_26w_4s	.383
110	grcnn	.380
111	tv_efficientnet-b1	.379
112	resnet101_imagenet_full	.377
113	densenet-121	.373
114	resnet50_ewconplus_wzc_seed2_2__323	.371
115	mehrer2020_alexnet_training_seed_01_fov4	.370
116	xception-keras	.369
117	resnet50_linf_4_robust	.368
118	cvt_cvt-21-224-in1k_4_LucyV4	.366
119	resnet-152_v1-tf	.364
120	resnet50_hvs_wzc	.363
121	resnet50_ewconplus_wzc	.363
122	densenet-201	.360
123	densenet_201_pytorch	.360
124	dinov2_vitl14_lc_res336	.359
125	densenet-121-keras	.357
126	resnet50-SIN_IN	.356
127	densenet-201-keras	.353
128	efficientnet_b2_imagenet_full	.353
129	vonegrcnn_52e_full	.352
130	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.350
131	resnet50	.346
132	resnet-50_v2-tf	.343
133	resnet50-moclr8deg	.340
134	vonegrcnn_62e_nobn	.334
135	pnasnet_large_pytorch	.333
136	dinov2_vitg14_reg_lc	.333
137	vonegrcnn_47e	.327
138	custom_model_cv_18_dagger_408	.324
139	blt_vs	.320
140	BiT-S-R152x2	.320
141	AdvProp_efficientnet-b8	.319
142	resnet50_random_linf8_perturb	.319
143	resnet50-VITO-8deg-cc	.319
144	resnet50_imagenet_full	.318
145	ReAlnet02	.317
146	resnet-50_v1-tf	.316
147	BiT-S-R101x3	.315
148	densenet-169	.314
149	resnet50-SIN_IN_IN	.313
150	resnet_SIN_IN_FT_IN	.313
151	nasnet_mobile	.312
152	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.309
153	vit_huge_clip336_laion	.307
154	resnet50_st_wzc_2	.305
155	vonegrcnn_62e_nobn	.304
156	vonegrcnn_52e_full	.302
157	inception_v2-tf	.302
158	resnet50_simsiam_linhead	.301
159	mobilenet_v2_1-4_224_pytorch	.299
160	mobilenet_v2_1_4_224	.299
161	resnet50_byol_linhead	.298
162	densenet-169-keras	.297
163	ReAlnet05	.297
164	alexnet_fov4	.296
165	texture_shape_resnet50_trained_on_SIN	.295
166	resnet_50_v1_spiking	.295
167	resnet50_barlowtwins_linhead	.294
168	vonegrcnn_47e	.294
169	vgg_19	.294
170	resnet-101_v1-tf	.292
171	ReAlnet06	.292
172	resnet-50-pytorch	.291
173	resnet50-sup	.291
174	resnet50_tutorial	.291
175	resnet_50_v1	.291
176	antialiased-r50	.290
177	ReAlnet10	.290
178	BiT-S-R152x4	.287
179	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.286
180	resnet50_random_l2_perturb	.286
181	ReAlnet04	.285
182	voneresnet-50	.284
183	voneresnet-50-robust	.284
184	mobilenet_v2_1_0_160	.283
185	resnet50_moco_v2	.282
186	ReAlnet07	.281
187	inception_v1	.278
188	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.277
189	CORnet-S	.276
190	ReAlnet08	.274
191	ReAlnet01	.273
192	resnet50_l2_3_robust	.273
193	mobilenet_v2_1.4_224-tf	.272
194	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
195	ReAlnet03	.267
196	cornet_s	.263
197	mobilenet_v2_1_3_224	.262
198	convnext_base_fb_in1k_gram_aligned_dinov3	.261
199	mobilenet_v2_1_0_224	.258
200	eicircuit_resnet18_bn_20260919	.258
201	resnet50_linf_8_robust	.257
202	resnet50-SIN	.256
203	resnet50_byol	.255
204	AlexNet_SIN_fov4	.252
205	mobilenet_v2_1.0_192-tf	.252
206	mobilenet_v2_1.0_224-tf	.251
207	inception_v1-tf	.250
208	resnet18_imagenet_full	.247
209	mobilenet_v2_1_0_192	.245
210	resnet-34	.245
211	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.244
212	vgg_16	.242
213	BiT-S-R50x1	.241
214	mobilenet_v2_1.3_224-tf	.240
215	efficientnet_b1_imagenet_full	.238
216	resnet50_robust_l2_eps1	.233
217	mobilenet_v2_1.0_160-tf	.231
218	eBarlow_lmda_02_1000ep	.230
219	alexnet_random_linf8_perturb	.228
220	ReAlnet09	.226
221	resnet50_vicreg_linhead	.225
222	efficientnet_b0_imagenet_full	.221
223	mobilenet_v1_0.75_224	.220
224	resnet-50-robust	.219
225	imagenet_l2_3_0	.219
226	resnet50_robust_l2_eps3	.219
227	resnet-18	.215
228	mobilenet_v1_1.0_224	.214
229	mobilenet_v2_0_5_224	.213
230	resnet50-vitoimagevidnet8	.212
231	regnet_y_400mf	.203
232	vonealexnet_gaussian_noise_std4_fixed	.200
233	mobilenet_v2_0.75_128	.196
234	mehrer2020_alexnet_training_seed_01	.190
235	alexnet_random_l2_3_perturb	.190
236	mobilenet_v2_0_75_160	.189
237	resnet50_simclr_linhead_01norm	.177
238	alexnet_reduced_aliasing_early_checkpoint	.174
239	mobilenet_v2_0.5_192-tf	.173
240	mobilenet_v2_0.75_160-tf	.171
241	shufflenet_v2_x1_0	.168
242	nasnet_mobile-tf	.168
243	alexnet_ks_torevert	.167
244	alexnet	.167
245	resnet50_simclr	.162
246	mobilenet_v1_0.75_192	.161
247	mobilenet_v2_1_0_128	.157
248	deit_small_imagenet_100_seed-0	.154
249	BiT-S-R101x1	.154
250	vgg-19-keras	.151
251	AdvProp_efficientnet-b0	.151
252	alexnet_robust_correct	.146
253	mobilenet_v1_1.0_192	.145
254	mobilenet_v1_0.75_160	.142
255	convnext_tiny_sup	.138
256	mobilenet_v2_0_5_192	.137
257	mobilenet_v2_0.35_192	.136
258	alexnet_fov16	.135
259	alexnet_l2_3_robust	.132
260	vgg-16-keras	.130
261	resnet50-barlow	.129
262	alexnet_training_seed_05	.129
263	alexnet_training_seed_01	.129
264	alexnet_training_seed_01_fov4	.129
265	alexnet_training_seed_01_fov12	.129
266	alexnet_training_seed_01_fov16	.129
267	alexnet_linf_8_robust	.127
268	mobilenet_v2_0_75_192	.125
269	alexnet_early_checkpoint	.124
270	mobilenet_v2_0.35_96	.124
271	mobilenet_v1_1.0_128	.124
272	mobilenet_v1_1.0_160	.123
273	resnet50_eMMCR_Vanilla	.123
274	0.5x_resnet-18_LC_w_sh_1_iter	.121
275	resnet50-simclr-vissl	.121
276	mobilenet_v1_0.5_224	.117
277	mehrer2020_alexnet_training_seed_01_fov16	.117
278	mobilenet_v2_0_75_224	.113
279	resnet50_imagenet_10_seed-0	.112
280	deit_small_imagenet_10_seed-0	.112
281	deit_small_imagenet_1_seed-0	.112
282	alexnet_fov12	.112
283	mobilenet_v1_0.5_128	.112
284	mehrer2020_alexnet_training_seed_01_fov12	.109
285	mehrer2020_alexnet_training_seed_05	.109
286	mobilenet_v1_0.5_192	.108
287	mehrer2020_alexnet_training_seed_02	.108
288	squeezenet1_1	.105
289	konkle_alexnetgn_ipcl_ref01_primary_model	.105
290	mobilenet_v1_0.75_128	.104
291	resnet50-vicreg	.103
292	mobilenet_v2_1.0_128-tf	.101
293	resnet50_imagenet_100_seed-0	.099
294	mobilenet_v2_0.5_96	.097
295	mehrer2020_alexnet_training_seed_04	.097
296	mobilenet_v2_0.5_160	.096
297	mobilenet_v2_0.35_224	.095
298	mobilenet_v2_1.0_96	.094
299	AlexNet_SIN	.093
300	mobilenet_v1_0.25_224	.093
301	mobilenet_v2_0.75_96	.093
302	mehrer2020_alexnet_training_seed_03	.092
303	mobilenet_v1_0.5_160	.091
304	convnext_small_imagenet_10_seed-0	.091
305	mobilenet_v2_0.75_192-tf	.090
306	mobilenet_v2_0.75_224-tf	.090
307	imagenet_l2_10_0	.089
308	resnet_50_v1_spiking_l4a	.089
309	mobilenet_v2_0.35_128	.085
310	mobilenet_v1_0.25_160	.081
311	mobilenet_v2_0.5_224-tf	.080
312	mobilenet_v2_0.35_160	.079
313	texture_shape_alexnet_trained_on_SIN	.078
314	alexnet_training_seed_06	.076
315	squeezenet1_0	.071
316	mobilenet_v1_0.25_192	.069
317	resnet50-vicregl0p75	.063
318	resnet_50_v1_spiking_l4	.062
319	resnet_50_v1_spiking_l3	.057
320	mobilenet_v2_0.5_128	.056
321	AlexNet_SIN_fov12	.042
322	my-model	.040
323	alexnet_training_seed_02	.037
324	alexnet_training_seed_04	.037
325	alexnet_training_seed_08	.037
326	alexnet_training_seed_10	.037
327	artResNet18_1	.037
328	resnet50-vicregl0p9	.036
329	alexnet_training_seed_09	.034
330	mobilenet_v1_0.25_128	.033
331	alexnet_training_seed_07	.033
332	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.028
333	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.026
334	resnet50_FractalDB	.023
335	resnet-50_untrained	.018
336	AlexNet_SIN_fov16	.010
337	resnet50_imagenet_1_seed-0	.010
338	convnext_small_imagenet_1_seed-0	.007
339	barlow-twins-resnet50	.003
340	alexnet_training_seed_03	.001
341	mobilevit_small	.000
342	resnet-18-LC_w_sh_100_iter_conv_init_m
343	ViT-B/32
344	BiT-M-R50x3
345	BiT-M-R50x1
346	BiT-M-R152x2
347	resnet-18-LC_w_sh_1_iter_conv_init_m
348	resnet-18-LC_w_sh_10_iter_m
349	resnet-18_test_m
350	resnet-18-LC_w_sh_100_iter_m
351	resnet-18-LC_w_sh_1_iter_m
352	resnet-18-LC_w_sh_10_iter_conv_init_m
353	FrankRobWobv0
354	0.5x_resnet-18_LC
355	CORnetZ_CIFAR10
356	resnet18-local_aggregation
357	resnet18-deepcluster
358	r3m_resnet18
359	CORnet-Z
360	resnet18-instance_recognition
361	my-model
362	vggface
363	0.5x_resnet-18_LC_w_sh_10_iter
364	resnet18-colorization
365	r3m_resnet50
366	r3m_resnet34
367	resnet-18-LC_m
368	r3m_resnet50_nocrop
369	resnet18-supervised
370	resnet-18-LC_1st_conv_m
371	resnet-18-LC_conv_init_m
372	resnet18-contrastive_multiview
373	0.5x_resnet-18
374	RN50
375	0.5x_resnet-18_LC_w_sh_100_iter
376	RN50
377	resnet18-relative_position
378	resnet18-autoencoder
379	resnet18-simclr
380	ViT_L_32
381	ViT_B_32
382	yudixie_resnet50_random_0_240908
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	v1-pyr-nodown
393	unet_entire
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_imagenet1kpret_0_240908
403	yudixie_resnet50_imagenet1kpret_0_240312
404	yudixie_resnet50_object_class_0_240908
405	yudixie_resnet50_cat_obj_class_all_latents_0_240908
406	yudixie_resnet50_category_class_0_240908
407	inception_v3_pytorch
408	resnet18_imagenet21kP
409	yudixie_resnet50_distance_reg_0_240908
410	ConvLSTM
411	PredRNN
412	TAU
413	MIM
414	hmax
415	briaai_rmbg_1_4
416	ReAlnet01_cornet
417	vit_base_patch16_dinov3-lvd1689m
418	ReAlnet02_cornet
419	yudixie_resnet18_distance_reg_0_240719
420	compact_resnet50_V4
421	yudixie_resnet18_rotation_reg_0_240719
422	ReAlnet03_cornet
423	vit_base_patch14_dinov2-lvd142m
424	VOneCORnet-S
425	resnet50_ecoset_full
426	vit_base_patch14_reg4_dinov2-lvd142m
427	yudixie_resnet50_distance_translation_0_240908
428	compact_resnet50_robust_V4
429	yudixie_resnet18_distance_translation_0_240719
430	yudixie_resnet18_translation_rotation_0_240719
431	compact_resnet50_IT
432	yudixie_resnet18_cat_obj_class_all_latents_0_240719
433	ReAlnet05_cornet
434	yudixie_resnet18_translation_reg_0_240719
435	ReAlnet01_cornet_fov12
436	yudixie_resnet50_rotation_reg_0_240908
437	yudixie_resnet18_distance_translation_rotation_0_240719
438	yudixie_resnet18_object_class_0_240719
439	SeLaVi-AVE
440	yudixie_resnet18_imagenet1kpret_0_240719
441	r3d_18
442	compact_vgg19_V4
443	yudixie_resnet50_translation_reg_0_240908
444	compact_vgg19_IT
445	yudixie_resnet50_translation_rotation_0_240908
446	mc3_18
447	ReAlnet01_ALL
448	s3d
449	mvit_v1_b
450	ReAlnet02_ALL
451	compact_cornets_V4
452	omnivore_swinB
453	ReAlnet04_ALL
454	SeLaVi-Kinetics400
455	SeLaVi-VGG-Sound
456	compact_cornets_IT
457	ReAlnet05_ALL
458	SeLaVi-Kinetics-Sound
459	omnivore_swinS
460	resnet152_ecoset_full
461	ReAlnet06_ALL
462	r2plus1d_18
463	mvit_v2_s
464	compact_resnet50_robust_IT
465	ReAlnet10_cornet
466	ReAlnet07_ALL
467	yudixie_resnet18_category_class_0_240719
468	yudixie_resnet50_distance_translation_rotation_0_240908
469	ReAlnet08_ALL
470	yudixie_resnet18_random_0_240719
471	yudixie_resnet18_distance_rotation_0_240719
472	yudixie_resnet50_distance_rotation_0_240908
473	ReAlnet04_cornet
474	ReAlnet09_ALL
475	resnet50_primary_visual_cortex
476	yolos_tiny
477	ReAlnet10_ALL
478	ReAlnet03_ALL
479	ReAlnet01_cornet_fov16
480	ReAlnet01_cornet_fov4
481	ReAlnet06_cornet
482	ReAlnet07_cornet
483	ReAlnet09_cornet
484	ReAlnet08_cornet
485	resnet101_ecoset_full
486	resnet18_ecoset_full
487	resnet34_ecoset_full
488	resnet18_fair
489	pr1_stl10_disentangled_alpha04
490	predictive_coding_pc
491	yudixie_wbh_object_class_scaling_0415_run_0
492	yudixie_wbh_object_class_scaling_0415_run_3
493	yudixie_wbh_object_class_scaling_0415_imagenet
494	yudixie_wbh_object_class_scaling_0415_run_2
495	yudixie_wbh_object_class_scaling_0415_run_1
496	deepeisnn_ei_cifar10_vgg19
497	deepeisnn_ei_cifar10_resnet18
498	deepeisnn_ei_imagenet_resnet18
499	dinov2_vitl14_reg_lc_featread
500	gabor_filter_entropy_4x4
501	gabor_filter_entropy_4x4_v2
502	gabor_filter_entropy_4x4_v2_forcedCosine
503	gabor_filter_mean_abs_4x4_v2

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

0.46.

Note that scores are relative to this ceiling.

Data: Geirhos2021eidolonIII

Metric: error_consistency