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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021edge-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
2	vit_large_clip336_openai	1.0
3	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
4	eva02_large_in22k	1.0
5	convnext_large_clip_laion2b_finelayers	1.0
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
7	convnext_base:clip_laiona_augreg_ft_in1k_384	1.0
8	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.995
9	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.979
10	vit_huge_clip336_laion	.945
11	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.899
12	dinov2_vitl14_reg_lc	.898
13	CLIP_ViT-B_32	.854
14	dinov2_vitg14_reg_lc	.815
15	vit_large_patch14_clip_224:openai_ft_in1k	.807
16	vit_base_patch16_clip_224:openai_ft_in1k	.753
17	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.744
18	SWSL_resnext101_32x8d	.728
19	resnext101_32x16d_wsl	.719
20	dinov2_vitl14_lc_res336	.705
21	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.699
22	dinov2_vitl14_lc	.670
23	convnext_xlarge:fb_in22k_ft_in1k	.670
24	resnext101_32x32d_wsl	.645
25	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.635
26	dinov2_vitg14_lc	.625
27	resnext101_32x48d_wsl	.619
28	resnext101_32x8d_wsl	.618
29	CLIP-RN50	.608
30	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.543
31	vision_transformer_vit_large_patch16_224	.543
32	convnext_large:fb_in22k_ft_in1k	.531
33	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.519
34	CLIP_resnet50	.516
35	CLIP_resnet50_float32	.516
36	fixres_resnext101_32x48d_wsl	.502
37	convnext_xxlarge_clip	.468
38	convnext_large_in22k_supervised	.466
39	convnext_base_fb_in22k_ft_in1k	.447
40	SWSL_resnet50	.395
41	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.363
42	convnext_large_imagenet_full_seed-0	.285
43	resnet50-VITO-8deg-cc	.264
44	convnext_tiny_imagenet_full_seed-0	.264
45	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.252
46	cvt_cvt-21-384-in1k_4_LucyV4	.243
47	convnext_tiny:in12k_ft_in1k	.232
48	convnext_base_imagenet_full_seed-0	.219
49	AlexNet_SIN_fov4	.200
50	convnext_small_imagenet_full_seed-0	.198
51	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.195
52	xception-keras	.194
53	vit_relpos_base_patch16_clsgap_224:sw_in1k	.192
54	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.187
55	mehrer2020_alexnet_training_seed_01_fov4	.184
56	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.184
57	effnetv2m_custom384	.183
58	inception_v4	.182
59	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.182
60	inception_v3_pytorch	.175
61	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.173
62	cvt_cvt-21-224-in1k_4_LucyV4	.168
63	AT_efficientnet-b2	.163
64	AdvProp_efficientnet-b2	.163
65	cvt_cvt-13-384-in1k_4_LucyV4	.160
66	convnext_femto_ols:d1_in1k	.158
67	pnasnet_large_halfPrecision	.153
68	pnasnet_large	.153
69	cvt_cvt-13-224-in1k_4_LucyV4	.151
70	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.151
71	resnet_152_v2	.151
72	resnet_50_v2	.151
73	resnet50_st_wzc_seed6_2_323	.150
74	inception_v4-tf	.148
75	resnet50_ewconplus_wzc_seed2_2__323	.147
76	focalnet_tiny_lrf_in1k	.144
77	resnet-152_v2_pytorch	.144
78	inception_v3-tf	.140
79	resnet50_ewconplus_wzc	.139
80	resnet50_supervised_linhead	.139
81	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.139
82	AdvProp_efficientnet-b6	.139
83	efficientnet-b7	.138
84	resnet50_byol	.133
85	pnasnet_large_pytorch	.132
86	resnet50_st_wzc_seed3_2_323	.132
87	convnext_base_fb_in1k	.132
88	antialias-resnet152	.132
89	cv_18_dagger_408_pretrained	.131
90	blt_vs	.128
91	regnety_032	.125
92	alexnet_fov4	.124
93	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.124
94	inception_v3	.124
95	resnet50_st_wzc_2	.124
96	resnet50_ewconplus_wzc_seed5_2__323	.123
97	custom_model_cv_18_dagger_408	.122
98	resnet50_byol_linhead	.121
99	resnet101	.116
100	resnet-18	.116
101	resnet50_st_wzc_seed7_2_323	.116
102	nasnet_large	.115
103	nasnet_large-tf	.115
104	resnet50-SIN_IN	.115
105	resnet50_random_linf8_perturb	.114
106	convnext_small_imagenet_100_seed-0	.113
107	densenet-201-keras	.113
108	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.113
109	deit_large_imagenet_full_seed-0	.109
110	resnet_101_v2	.109
111	AdvProp_efficientnet-b4	.107
112	squeezenet1_1	.107
113	resnet-152_v2-tf	.107
114	AT_efficientnet-b4	.107
115	vgg_16	.107
116	resnet_101_v1	.107
117	resnet50_imagenet_100_seed-0	.106
118	efficientnet_b0	.106
119	pnasnet_large-tf	.106
120	mobilenet_v2_1_0_160	.106
121	densenet-201	.105
122	densenet_201_pytorch	.105
123	seresnext50_32x4d	.105
124	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.105
125	densenet-121	.104
126	densenet-121-keras	.104
127	mobilenet_v2_1_0_128	.101
128	convnext_tiny_sup	.100
129	resnet50-vitoimagevidnet8	.099
130	inception_v1	.099
131	resnet50_hvs_wzc	.099
132	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.099
133	resnet-50_v2-tf	.098
134	mobilenet_v1_1.0_224	.098
135	tv_efficientnet-b1	.098
136	densenet-169	.098
137	resnet50_random_l2_perturb	.098
138	ReAlnet02	.093
139	AdvProp_efficientnet-b7	.092
140	texture_shape_resnet50_trained_on_SIN	.092
141	resnet-101_v1-tf	.092
142	resnet-34	.092
143	cornet_s	.092
144	alexnet_l2_3_robust	.092
145	alexnet_linf_8_robust	.092
146	ReAlnet10	.092
147	mobilenet_v2_0_5_192	.092
148	nasnet_mobile	.092
149	efficientnet_b0_imagenet_full	.091
150	efficientnet_b2_imagenet_full	.091
151	ReAlnet08	.091
152	resnet18_imagenet_full	.091
153	mobilenet_v2_0_75_160	.091
154	ReAlnet01	.091
155	resnet50_simclr_linhead_01norm	.091
156	CORnet-S	.091
157	inception_v1-tf	.091
158	densenet-169-keras	.090
159	resnet50-moclr8deg	.090
160	inception_v2-tf	.085
161	konkle_alexnetgn_ipcl_ref01_primary_model	.085
162	ReAlnet07	.084
163	resnet50_imagenet_full	.084
164	mobilenet_v2_1_0_224	.084
165	vonegrcnn_52e_full	.084
166	ijepa_vith14_linhead	.084
167	resnet50_vicreg_linhead	.084
168	BiT-S-R152x2	.084
169	voneresnet-50-non_stochastic	.084
170	mobilenet_v2_0.5_192-tf	.084
171	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.084
172	mobilenet_v2_0.35_160	.084
173	alexnet_robust_correct	.084
174	vgg_19	.084
175	antialiased-rnext101_32x8d	.084
176	ReAlnet05	.084
177	AlexNet_SIN_fov12	.084
178	resnet50_eMMCR_Vanilla	.084
179	ViT_B_16_imagenet1k	.084
180	ReAlnet06	.083
181	ReAlnet04	.083
182	ReAlnet03	.083
183	resnet50_barlowtwins_linhead	.083
184	mobilenet_v1_0.25_160	.079
185	0.5x_resnet-18_LC_w_sh_1_iter	.078
186	antialiased-r50	.078
187	vonegrcnn_62e_nobn	.077
188	mobilenet_v2_0_75_224	.077
189	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.077
190	resnet50_ewconplus_wzc_seed6_2_323	.077
191	mobilenet_v1_1.0_192	.077
192	mobilenet_v2_0.35_192	.077
193	mobilenet_v1_0.5_128	.077
194	resnet50	.077
195	vonealexnet_gaussian_noise_std4_fixed	.077
196	vonegrcnn_47e	.076
197	deit_base_imagenet_full_seed-0	.076
198	xception	.076
199	mehrer2020_alexnet_training_seed_05	.076
200	mobilenet_v2_1.4_224-tf	.076
201	BiT-S-R50x1	.076
202	BiT-S-R152x4	.076
203	mobilenet_v2_0.5_128	.076
204	alexnet_early_checkpoint	.076
205	alexnet_reduced_aliasing_early_checkpoint	.076
206	Res2Net50_26w_4s	.076
207	mobilenet_v1_1.0_160	.075
208	ReAlnet09	.075
209	mobilenet_v2_1_3_224	.075
210	grcnn	.075
211	resnet50_cpc_linhead	.075
212	mobilenet_v1_0.75_128	.074
213	resnet101_imagenet_full	.074
214	mobilenet_v2_0.75_96	.074
215	effnetb1_272x240	.074
216	convnext_base_fb_in1k_gram_aligned_dinov3	.072
217	resnet34_imagenet_full	.070
218	mobilenet_v2_0_5_224	.070
219	mehrer2020_alexnet_training_seed_03	.070
220	vonegrcnn_52e_full	.070
221	mobilenet_v2_1.0_128-tf	.070
222	resnet50-SIN_IN_IN	.069
223	resnet_SIN_IN_FT_IN	.069
224	mobilenet_v2_1.0_224-tf	.069
225	AdvProp_efficientnet-b8	.069
226	alexnet	.069
227	shufflenet_v2_x1_0	.069
228	alexnet_ks_torevert	.069
229	resnet50_simsiam_linhead	.069
230	resnet-50-pytorch	.068
231	BiT-S-R50x3	.068
232	resnet-152_v1-tf	.068
233	resnet50-sup	.068
234	mobilenet_v1_0.5_192	.068
235	ViT_L_32_imagenet1k	.068
236	resnet50_tutorial	.068
237	grcnn_109	.068
238	resnet_50_v1	.068
239	BiT-S-R101x3	.066
240	efficientnet_b1_imagenet_full	.064
241	mehrer2020_alexnet_training_seed_02	.063
242	squeezenet1_0	.063
243	mobilenet_v2_0.75_224-tf	.063
244	mobilenet_v1_0.25_224	.063
245	resnet50_moco_v2	.063
246	voneresnet-50	.062
247	vonegrcnn_62e_nobn	.062
248	resnet50-SIN	.062
249	ViT_B_32_imagenet1k	.062
250	vgg-16-keras	.062
251	mobilenet_v2_0.35_128	.062
252	regnet_y_400mf	.062
253	mobilenet_v2_1_0_192	.062
254	vonegrcnn_47e	.062
255	mehrer2020_alexnet_training_seed_01	.062
256	mehrer2020_alexnet_training_seed_04	.062
257	mobilenet_v1_0.5_224	.062
258	mobilenet_v1_0.75_160	.062
259	resnet152_imagenet_full	.062
260	mobilenet_v2_1-4_224_pytorch	.061
261	deit_small_imagenet_full_seed-0	.061
262	mobilenet_v2_1_4_224	.061
263	resnet_152_v1	.060
264	resnet50_imagenet_1_seed-0	.059
265	resnet-50_untrained	.059
266	alexnet_random_l2_3_perturb	.056
267	mobilenet_v2_0_75_192	.056
268	voneresnet-50-robust	.055
269	mobilenet_v2_0.75_192-tf	.055
270	texture_shape_alexnet_trained_on_SIN	.055
271	mobilenet_v2_0.5_224-tf	.055
272	mobilenet_v2_1.0_160-tf	.055
273	nasnet_mobile-tf	.055
274	BiT-S-R101x1	.055
275	mobilenet_v2_1.3_224-tf	.055
276	resnet-50-robust	.055
277	vgg-19-keras	.055
278	mobilenet_v2_1.0_96	.055
279	mobilenet_v1_0.75_192	.055
280	mobilenet_v1_1.0_128	.055
281	mobilenet_v2_0.75_128	.055
282	mobilenet_v2_0.35_96	.055
283	AdvProp_efficientnet-b0	.055
284	mobilenet_v2_0.5_96	.055
285	resnet50_l2_3_robust	.055
286	resnet50_linf_4_robust	.055
287	resnet50_linf_8_robust	.055
288	resnet50_FractalDB	.055
289	imagenet_l2_3_0	.055
290	imagenet_l2_10_0	.055
291	resnet50_robust_l2_eps3	.055
292	resnet50_robust_l2_eps1	.055
293	eicircuit_resnet18_bn_20260919	.055
294	AlexNet_SIN	.055
295	alexnet_fov12	.055
296	alexnet_fov16	.055
297	AlexNet_SIN_fov16	.055
298	mehrer2020_alexnet_training_seed_01_fov12	.055
299	mehrer2020_alexnet_training_seed_01_fov16	.055
300	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.055
301	mobilenet_v2_0.75_160-tf	.053
302	mobilenet_v1_0.25_192	.053
303	mobilenet_v2_0.35_224	.053
304	mobilenet_v2_0.5_160	.053
305	eBarlow_lmda_02_1000ep	.053
306	resnet50_ijepacnn_linhead	.053
307	vith14_supervised_linhead	.052
308	mobilevit_small	.050
309	resnet50_simclr	.046
310	mobilenet_v1_0.75_224	.046
311	vonealexnet	.044
312	resnet50-barlow	.042
313	convnext_small_imagenet_1_seed-0	.042
314	resnet-50_v1-tf	.039
315	resnet_50_v1_spiking_l4a	.039
316	alexnet_random_linf8_perturb	.038
317	resnet50-vicregl0p9	.037
318	alexnet_training_seed_03	.036
319	vith14_untrained_linhead	.036
320	resnet_50_v1_spiking	.035
321	mobilenet_v2_1.0_192-tf	.034
322	alexnet_training_seed_09	.034
323	mobilenet_v1_0.25_128	.032
324	alexnet_training_seed_02	.032
325	alexnet_training_seed_08	.032
326	alexnet_training_seed_04	.032
327	alexnet_training_seed_10	.032
328	alexnet_training_seed_07	.032
329	mobilenet_v1_0.5_160	.032
330	alexnet_training_seed_05	.024
331	alexnet_training_seed_01	.024
332	alexnet_training_seed_01_fov4	.024
333	alexnet_training_seed_01_fov12	.024
334	alexnet_training_seed_01_fov16	.024
335	barlow-twins-resnet50	.024
336	resnet50-vicreg	.024
337	resnet_50_v1_spiking_l4	.023
338	deit_small_imagenet_10_seed-0	.021
339	resnet50_imagenet_10_seed-0	.021
340	convnext_small_imagenet_10_seed-0	.021
341	deit_small_imagenet_1_seed-0	.021
342	artResNet18_1	.021
343	resnet50_untrained_linhead	.021
344	resnet_50_v1_spiking_l3	.015
345	deit_small_imagenet_100_seed-0	.014
346	resnet50-simclr-vissl	.011
347	resnet50-vicregl0p75	.010
348	alexnet_training_seed_06	.007
349	resnet-18-LC_w_sh_100_iter_conv_init_m
350	ViT-B/32
351	BiT-M-R50x3
352	BiT-M-R50x1
353	BiT-M-R152x2
354	resnet-18-LC_w_sh_1_iter_conv_init_m
355	resnet-18-LC_w_sh_1_iter_m
356	resnet-18-LC_w_sh_10_iter_m
357	resnet-18-LC_w_sh_100_iter_m
358	resnet-18-LC_w_sh_10_iter_conv_init_m
359	FrankRobWobv0
360	resnet18-local_aggregation
361	0.5x_resnet-18_LC
362	CORnetZ_CIFAR10
363	resnet18-deepcluster
364	r3m_resnet18
365	CORnet-Z
366	resnet18-instance_recognition
367	my-model
368	vggface
369	resnet18-colorization
370	0.5x_resnet-18_LC_w_sh_10_iter
371	r3m_resnet50
372	r3m_resnet34
373	resnet-18-LC_m
374	r3m_resnet50_nocrop
375	resnet18-supervised
376	resnet-18-LC_1st_conv_m
377	resnet-18-LC_conv_init_m
378	resnet18-contrastive_multiview
379	0.5x_resnet-18
380	RN50
381	0.5x_resnet-18_LC_w_sh_100_iter
382	RN50
383	resnet18-relative_position
384	resnet18-autoencoder
385	resnet18-simclr
386	ViT_L_32
387	ViT_B_32
388	resnet18-depth_prediction
389	ViT_B_16
390	r3m_resnet34_nocrop
391	resnet18-contrastive_predictive
392	omnivore_swinT
393	resnet-18-LC_untrained
394	resnet-18_untrained
395	resnet-50x2_untrained
396	dcgan
397	v1-pyr-nodown
398	unet_entire
399	CORnetZ_CIFAR10_bs32_20_04
400	pixels
401	dorinet_cornet_z
402	my-model
403	openclip
404	resnet50-cifar
405	resnet50_pretrained_with_retinal_waves
406	resnet50_ImageNet
407	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
408	yudixie_resnet50_random_0_240908
409	yudixie_resnet50_imagenet1kpret_0_240908
410	yudixie_resnet50_object_class_0_240908
411	yudixie_resnet50_category_class_0_240908
412	resnet18_imagenet21kP
413	yudixie_resnet50_distance_reg_0_240908
414	ConvLSTM
415	PredRNN
416	SimVP
417	TAU
418	MIM
419	vit_base_patch16_dinov3-lvd1689m
420	ReAlnet01_cornet
421	briaai_rmbg_1_4
422	yudixie_resnet18_translation_reg_0_240719
423	yudixie_resnet18_distance_reg_0_240719
424	yudixie_resnet18_rotation_reg_0_240719
425	yolos_tiny
426	yudixie_resnet18_imagenet1kpret_0_240719
427	ReAlnet02_cornet
428	compact_resnet50_V4
429	vit_base_patch14_dinov2-lvd142m
430	vit_base_patch14_reg4_dinov2-lvd142m
431	ReAlnet03_cornet
432	compact_resnet50_IT
433	ReAlnet01_cornet_fov4
434	ReAlnet01_cornet_fov12
435	compact_resnet50_robust_V4
436	yudixie_resnet50_rotation_reg_0_240908
437	resnet152_ecoset_full
438	yudixie_resnet50_distance_rotation_0_240908
439	yudixie_resnet50_distance_translation_0_240908
440	yudixie_resnet18_translation_rotation_0_240719
441	yudixie_resnet18_distance_rotation_0_240719
442	compact_vgg19_V4
443	yudixie_resnet18_category_class_0_240719
444	ReAlnet05_cornet
445	resnet-18_test_m
446	SeLaVi-AVE
447	yudixie_resnet18_distance_translation_rotation_0_240719
448	yudixie_resnet18_object_class_0_240719
449	hmax
450	r3d_18
451	compact_vgg19_IT
452	yudixie_resnet50_translation_reg_0_240908
453	mc3_18
454	ReAlnet01_ALL
455	yudixie_resnet50_translation_rotation_0_240908
456	s3d
457	ReAlnet07_cornet
458	mvit_v1_b
459	ReAlnet02_ALL
460	ReAlnet08_cornet
461	ReAlnet03_ALL
462	compact_cornets_V4
463	VOneCORnet-S
464	ReAlnet04_ALL
465	omnivore_swinB
466	SeLaVi-VGG-Sound
467	compact_cornets_IT
468	ReAlnet05_ALL
469	SeLaVi-Kinetics-Sound
470	SeLaVi-Kinetics400
471	r2plus1d_18
472	ReAlnet06_ALL
473	omnivore_swinS
474	mvit_v2_s
475	compact_resnet50_robust_IT
476	ReAlnet10_cornet
477	resnet18_ecoset_full
478	resnet34_ecoset_full
479	ReAlnet07_ALL
480	yudixie_resnet18_cat_obj_class_all_latents_0_240719
481	yudixie_resnet18_random_0_240719
482	ReAlnet08_ALL
483	yudixie_resnet18_distance_translation_0_240719
484	yudixie_resnet50_imagenet1kpret_0_240312
485	ReAlnet04_cornet
486	yudixie_resnet50_distance_translation_rotation_0_240908
487	yudixie_resnet50_cat_obj_class_all_latents_0_240908
488	resnet50_primary_visual_cortex
489	ReAlnet09_ALL
490	ReAlnet10_ALL
491	resnet50_ecoset_full
492	ReAlnet09_cornet
493	resnet101_ecoset_full
494	ReAlnet01_cornet_fov16
495	ReAlnet06_cornet
496	mehrer2020_alexnet_training_seed_08
497	mehrer2020_alexnet_training_seed_06
498	mehrer2020_alexnet_training_seed_07
499	mehrer2020_alexnet_training_seed_09
500	mehrer2020_alexnet_training_seed_10
501	resnet18_fair
502	pr1_stl10_disentangled_alpha04
503	predictive_coding_pc
504	yudixie_wbh_object_class_scaling_0415_run_0
505	yudixie_wbh_object_class_scaling_0415_run_3
506	yudixie_wbh_object_class_scaling_0415_imagenet
507	yudixie_wbh_object_class_scaling_0415_run_2
508	yudixie_wbh_object_class_scaling_0415_run_1
509	deepeisnn_ei_cifar10_vgg19
510	deepeisnn_ei_cifar10_resnet18
511	deepeisnn_ei_imagenet_resnet18
512	dinov2_vitl14_reg_lc_featread
513	persistence_mem
514	persistence_memory
515	gabor_filter_entropy_4x4
516	gabor_filter_entropy_4x4_v2
517	gabor_filter_mean_abs_4x4_v2
518	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

0.32.

Note that scores are relative to this ceiling.

Data: Geirhos2021edge

Metric: error_consistency