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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021uniformnoise-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.781
2	resnext101_32x32d_wsl	.754
3	resnext101_32x48d_wsl	.743
4	vit_base_patch16_clip_224:openai_ft_in1k	.734
5	resnext101_32x16d_wsl	.731
6	deit3_base_patch16_224_fb_in1k	.730
7	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.728
8	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.723
9	fixres_resnext101_32x48d_wsl	.720
10	vit_large_patch14_clip_224:laion2b_ft_in1k	.719
11	convnext_large:fb_in22k_ft_in1k	.686
12	vision_transformer_vit_large_patch16_224	.685
13	SWSL_resnext101_32x8d	.675
14	resnet-152_v2_pytorch	.674
15	dinov2_vitl14_lc	.672
16	resnet_152_v2	.670
17	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.661
18	convnext_base_fb_in22k_ft_in1k	.652
19	resnet_101_v2	.647
20	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.647
21	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.645
22	vit_large_patch14_clip_224:openai_ft_in1k	.639
23	resnext101_32x8d_wsl	.637
24	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.635
25	dinov2_vitg14_lc	.630
26	CLIP_resnet50	.627
27	CLIP_resnet50_float32	.627
28	convnext_large_clip_laion2b_finelayers	.626
29	convnext_large_in22k_supervised	.619
30	convnext_femto_ols:d1_in1k	.617
31	dinov2_vitl14_reg_lc	.616
32	cvt_cvt-13-384-in1k_4_LucyV4	.614
33	vit_large_patch14_clip_336:laion2b_ft_in1k	.604
34	convnext_xlarge:fb_in22k_ft_in1k	.601
35	focalnet_tiny_lrf_in1k	.601
36	SWSL_resnet50	.599
37	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.591
38	convnext_tiny:in12k_ft_in1k	.590
39	cvt_cvt-13-224-in1k_4_LucyV4	.587
40	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.583
41	vit_large_clip336_openai	.580
42	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.577
43	convnext_base:clip_laiona_augreg_ft_in1k_384	.576
44	vit_relpos_base_patch16_clsgap_224:sw_in1k	.576
45	CLIP_ViT-B_32	.572
46	nasnet_large	.555
47	convnext_base_fb_in1k	.537
48	CLIP-RN50	.537
49	ViT_L_32_imagenet1k	.524
50	convnext_tiny_imagenet_full_seed-0	.522
51	vit_huge_clip336_laion	.521
52	convnext_base_imagenet_full_seed-0	.520
53	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.520
54	cvt_cvt-21-384-in1k_4_LucyV4	.515
55	dinov2_vitg14_reg_lc	.513
56	convnext_small_imagenet_full_seed-0	.509
57	pnasnet_large_halfPrecision	.499
58	cvt_cvt-21-224-in1k_4_LucyV4	.493
59	pnasnet_large	.493
60	eva02_large_in22k	.481
61	ViT_B_16_imagenet1k	.476
62	effnetv2m_custom384	.475
63	pnasnet_large-tf	.473
64	dinov2_vitl14_lc_res336	.472
65	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.462
66	regnety_032	.462
67	resnet_50_v2	.458
68	ViT_B_32_imagenet1k	.455
69	convnext_xxlarge_clip	.447
70	convnext_large_imagenet_full_seed-0	.443
71	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.441
72	seresnext50_32x4d	.439
73	nasnet_large-tf	.418
74	deit3_base_patch16_224_fb_in22k_ft_in1k	.410
75	inception_v4	.404
76	AdvProp_efficientnet-b6	.401
77	resnet50_st_wzc_seed7_2_323	.388
78	resnet-152_v2-tf	.386
79	resnet50-VITO-8deg-cc	.381
80	inception_v3	.377
81	resnet50_ewconplus_wzc_seed5_2__323	.356
82	cv_18_dagger_408_pretrained	.354
83	convnext_base_fb_in1k_gram_aligned_dinov3	.354
84	resnet50_ewconplus_wzc_seed2_2__323	.350
85	inception_v3-tf	.348
86	xception-keras	.344
87	resnet101	.340
88	tv_efficientnet-b1	.338
89	inception_v4-tf	.330
90	deit_large_imagenet_full_seed-0	.328
91	xception	.322
92	resnet50_st_wzc_seed6_2_323	.317
93	resnet50_st_wzc_seed3_2_323	.313
94	AdvProp_efficientnet-b4	.309
95	AT_efficientnet-b4	.309
96	antialias-resnet152	.309
97	resnet50_st_wzc_2	.291
98	densenet-201	.289
99	densenet_201_pytorch	.289
100	effnetb1_272x240	.285
101	resnet-50_v2-tf	.284
102	resnet50_ewconplus_wzc	.282
103	antialiased-rnext101_32x8d	.279
104	densenet-201-keras	.272
105	ijepa_vith14_linhead	.268
106	resnet50-moclr8deg	.266
107	BiT-S-R50x3	.265
108	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.262
109	AdvProp_efficientnet-b7	.260
110	deit_base_imagenet_full_seed-0	.257
111	deit_small_imagenet_full_seed-0	.257
112	efficientnet-b7	.254
113	resnet_101_v1	.253
114	AT_efficientnet-b2	.250
115	AdvProp_efficientnet-b2	.250
116	efficientnet_b0	.249
117	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.248
118	resnet50_random_l2_perturb	.245
119	resnet50	.244
120	Res2Net50_26w_4s	.243
121	resnet50_byol	.231
122	resnet_152_v1	.231
123	antialiased-r50	.224
124	resnet50_simsiam_linhead	.222
125	resnet50_ewconplus_wzc_seed6_2_323	.219
126	resnet_50_v1_spiking	.209
127	resnet50_moco_v2	.209
128	convnext_small_imagenet_100_seed-0	.202
129	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.196
130	BiT-S-R101x3	.194
131	resnet-50-pytorch	.194
132	resnet50-sup	.194
133	resnet50_tutorial	.194
134	resnet_50_v1	.194
135	resnet50_hvs_wzc	.193
136	resnet50_byol_linhead	.192
137	resnet50_vicreg_linhead	.189
138	BiT-S-R152x2	.188
139	convnext_tiny_sup	.188
140	vonegrcnn_62e_nobn	.183
141	grcnn	.182
142	AdvProp_efficientnet-b8	.180
143	nasnet_mobile	.179
144	vonegrcnn_47e	.174
145	densenet-121-keras	.173
146	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.172
147	BiT-S-R152x4	.172
148	mehrer2020_alexnet_training_seed_01_fov4	.169
149	densenet-121	.166
150	resnet50-SIN_IN_IN	.162
151	resnet_SIN_IN_FT_IN	.162
152	vonegrcnn_62e_nobn	.157
153	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.157
154	grcnn_109	.156
155	resnet50_barlowtwins_linhead	.155
156	densenet-169	.153
157	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.149
158	resnet50_simclr_linhead_01norm	.149
159	vonegrcnn_52e_full	.144
160	densenet-169-keras	.143
161	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.137
162	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.136
163	BiT-S-R101x1	.134
164	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.133
165	voneresnet-50-non_stochastic	.132
166	resnet101_imagenet_full	.131
167	alexnet_training_seed_05	.130
168	alexnet_training_seed_01	.130
169	alexnet_training_seed_01_fov4	.130
170	alexnet_training_seed_01_fov12	.130
171	alexnet_training_seed_01_fov16	.130
172	resnet152_imagenet_full	.129
173	vonegrcnn_47e	.127
174	resnet50-simclr-vissl	.127
175	vonegrcnn_52e_full	.125
176	resnet50_random_linf8_perturb	.122
177	BiT-S-R50x1	.121
178	voneresnet-50-robust	.121
179	mobilenet_v2_1_0_224	.121
180	resnet50-vitoimagevidnet8	.119
181	blt_vs	.119
182	eBarlow_lmda_02_1000ep	.118
183	resnet50-SIN_IN	.116
184	inception_v2-tf	.112
185	imagenet_l2_10_0	.105
186	resnet50_imagenet_full	.105
187	resnet50_simclr	.103
188	alexnet_fov16	.102
189	alexnet_fov12	.101
190	alexnet_robust_correct	.099
191	alexnet_l2_3_robust	.098
192	custom_model_cv_18_dagger_408	.097
193	mehrer2020_alexnet_training_seed_01_fov16	.093
194	eicircuit_resnet18_bn_20260919	.092
195	vgg-19-keras	.091
196	mobilenet_v1_0.25_128	.090
197	resnet50_imagenet_10_seed-0	.089
198	deit_small_imagenet_10_seed-0	.089
199	deit_small_imagenet_1_seed-0	.089
200	resnet34_imagenet_full	.088
201	alexnet_training_seed_02	.088
202	alexnet_training_seed_04	.088
203	alexnet_training_seed_08	.088
204	alexnet_training_seed_10	.088
205	vgg_19	.088
206	inception_v1	.080
207	voneresnet-50	.079
208	konkle_alexnetgn_ipcl_ref01_primary_model	.079
209	nasnet_mobile-tf	.078
210	mobilenet_v2_0.5_160	.078
211	mobilenet_v1_0.5_128	.078
212	alexnet_training_seed_07	.077
213	mobilenet_v2_1_3_224	.076
214	mehrer2020_alexnet_training_seed_01_fov12	.075
215	mobilenet_v2_0.5_128	.075
216	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
217	mobilenet_v2_1_0_192	.075
218	deit_small_imagenet_100_seed-0	.073
219	AdvProp_efficientnet-b0	.073
220	mehrer2020_alexnet_training_seed_03	.072
221	ReAlnet04	.071
222	mobilenet_v2_0.35_160	.069
223	mobilenet_v2_0.35_192	.068
224	ReAlnet08	.068
225	inception_v1-tf	.067
226	mobilenet_v1_0.5_160	.067
227	ReAlnet03	.067
228	ReAlnet09	.064
229	mobilenet_v2_0.35_128	.062
230	alexnet_fov4	.061
231	resnet50_eMMCR_Vanilla	.061
232	mobilenet_v1_0.75_128	.061
233	squeezenet1_0	.059
234	mobilenet_v1_0.5_224	.059
235	mobilenet_v2_0.75_96	.058
236	convnext_small_imagenet_1_seed-0	.058
237	AlexNet_SIN_fov4	.058
238	resnet50-vicregl0p9	.057
239	resnet50-barlow	.057
240	mobilenet_v2_0.5_192-tf	.057
241	mobilenet_v2_1-4_224_pytorch	.057
242	mobilenet_v2_1_4_224	.057
243	ReAlnet05	.056
244	mobilenet_v2_0.5_224-tf	.056
245	resnet50_imagenet_1_seed-0	.054
246	mobilenet_v1_0.25_192	.054
247	mehrer2020_alexnet_training_seed_04	.050
248	resnet50_linf_4_robust	.050
249	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.049
250	mobilenet_v1_0.25_160	.049
251	ReAlnet01	.049
252	ReAlnet06	.049
253	mobilenet_v2_0.35_224	.048
254	mobilenet_v2_0.75_192-tf	.048
255	ReAlnet07	.048
256	mobilenet_v2_1_0_160	.048
257	mobilenet_v2_0.75_224-tf	.047
258	alexnet_random_l2_3_perturb	.047
259	resnet-34	.047
260	mobilenet_v1_0.5_192	.046
261	mobilenet_v2_1.0_224-tf	.046
262	mobilenet_v1_0.75_160	.046
263	resnet50_l2_3_robust	.046
264	resnet_50_v1_spiking_l4	.046
265	resnet-152_v1-tf	.045
266	vgg-16-keras	.045
267	resnet50_imagenet_100_seed-0	.045
268	resnet50_FractalDB	.044
269	mobilenet_v1_0.75_192	.044
270	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.043
271	alexnet_linf_8_robust	.043
272	alexnet_random_linf8_perturb	.041
273	resnet-101_v1-tf	.041
274	alexnet_early_checkpoint	.040
275	vgg_16	.039
276	resnet-18	.039
277	alexnet	.038
278	alexnet_ks_torevert	.038
279	resnet-50-robust	.038
280	imagenet_l2_3_0	.038
281	resnet50_robust_l2_eps3	.038
282	resnet18_imagenet_full	.038
283	mobilenet_v2_0.75_160-tf	.038
284	efficientnet_b1_imagenet_full	.036
285	mobilenet_v2_0.75_128	.036
286	mobilenet_v2_1.0_128-tf	.036
287	texture_shape_resnet50_trained_on_SIN	.036
288	mobilenet_v1_1.0_160	.036
289	efficientnet_b0_imagenet_full	.035
290	shufflenet_v2_x1_0	.034
291	resnet_50_v1_spiking_l4a	.034
292	mehrer2020_alexnet_training_seed_02	.034
293	resnet50_robust_l2_eps1	.033
294	mobilenet_v1_0.25_224	.033
295	alexnet_reduced_aliasing_early_checkpoint	.031
296	squeezenet1_1	.031
297	mobilenet_v1_1.0_192	.030
298	mehrer2020_alexnet_training_seed_05	.030
299	mobilenet_v2_1.0_96	.028
300	alexnet_training_seed_09	.027
301	regnet_y_400mf	.027
302	mehrer2020_alexnet_training_seed_01	.026
303	resnet50_linf_8_robust	.026
304	alexnet_training_seed_03	.024
305	mobilenet_v2_0.5_96	.024
306	resnet50-SIN	.023
307	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.023
308	mobilenet_v2_1_0_128	.022
309	mobilenet_v1_1.0_224	.022
310	convnext_small_imagenet_10_seed-0	.022
311	resnet50-vicregl0p75	.022
312	resnet-50_untrained	.021
313	0.5x_resnet-18_LC_w_sh_1_iter	.021
314	mobilenet_v2_1.0_160-tf	.020
315	mobilenet_v1_0.75_224	.017
316	mobilenet_v1_1.0_128	.016
317	mobilenet_v2_0_75_224	.016
318	AlexNet_SIN_fov12	.014
319	mobilenet_v2_0.35_96	.013
320	AlexNet_SIN_fov16	.012
321	ReAlnet02	.011
322	cornet_s	.011
323	ReAlnet10	.011
324	mobilenet_v2_1.3_224-tf	.010
325	vonealexnet_gaussian_noise_std4_fixed	.010
326	resnet_50_v1_spiking_l3	.009
327	mobilenet_v2_1.4_224-tf	.008
328	barlow-twins-resnet50	.006
329	mobilenet_v2_0_5_192	.006
330	efficientnet_b2_imagenet_full	.006
331	CORnet-S	.005
332	mobilenet_v2_0_75_160	.005
333	alexnet_training_seed_06	.005
334	texture_shape_alexnet_trained_on_SIN	.005
335	artResNet18_1	.004
336	mobilenet_v2_1.0_192-tf	.004
337	resnet50-vicreg	.003
338	mobilenet_v2_0_75_192	.003
339	AlexNet_SIN	.002
340	mobilenet_v2_0_5_224	.001
341	resnet-50_v1-tf	.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	resnet-18-LC_w_sh_1_iter_conv_init_m
347	resnet-18-LC_w_sh_1_iter_m
348	BiT-M-R152x2
349	resnet-18-LC_w_sh_10_iter_m
350	ReAlnet09_ALL
351	resnet-18-LC_w_sh_100_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	r3m_resnet18
358	CORnet-Z
359	resnet18-deepcluster
360	vggface
361	my-model
362	resnet18-instance_recognition
363	0.5x_resnet-18_LC_w_sh_10_iter
364	r3m_resnet50
365	r3m_resnet34
366	resnet-18-LC_m
367	r3m_resnet50_nocrop
368	resnet18-supervised
369	resnet-18-LC_1st_conv_m
370	resnet-18-LC_conv_init_m
371	resnet18-contrastive_multiview
372	0.5x_resnet-18
373	RN50
374	0.5x_resnet-18_LC_w_sh_100_iter
375	RN50
376	resnet18-colorization
377	resnet18-relative_position
378	resnet18-autoencoder
379	resnet18-simclr
380	ViT_L_32
381	ViT_B_32
382	resnet18-depth_prediction
383	ViT_B_16
384	r3m_resnet34_nocrop
385	resnet18-contrastive_predictive
386	resnet-18-LC_untrained
387	resnet-18_untrained
388	resnet-50x2_untrained
389	dcgan
390	unet_entire
391	v1-pyr-nodown
392	CORnetZ_CIFAR10_bs32_20_04
393	pixels
394	dorinet_cornet_z
395	omnivore_swinT
396	my-model
397	openclip
398	resnet50-cifar
399	resnet50_pretrained_with_retinal_waves
400	resnet50_ImageNet
401	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
402	ReAlnet08_ALL
403	yudixie_resnet50_random_0_240908
404	yudixie_resnet50_imagenet1kpret_0_240908
405	yudixie_resnet50_imagenet1kpret_0_240312
406	yudixie_resnet50_cat_obj_class_all_latents_0_240908
407	yudixie_resnet50_object_class_0_240908
408	yudixie_resnet50_category_class_0_240908
409	resnet18_imagenet21kP
410	yudixie_resnet50_distance_reg_0_240908
411	ConvLSTM
412	PredRNN
413	SimVP
414	TAU
415	vit_base_patch16_dinov3-lvd1689m
416	MIM
417	hmax
418	briaai_rmbg_1_4
419	pnasnet_large_pytorch
420	inception_v3_pytorch
421	vit_base_patch14_reg4_dinov2-lvd142m
422	ReAlnet01_cornet
423	yolos_tiny
424	yudixie_resnet18_translation_reg_0_240719
425	yudixie_resnet18_distance_reg_0_240719
426	yudixie_resnet18_rotation_reg_0_240719
427	yudixie_resnet18_imagenet1kpret_0_240719
428	compact_resnet50_V4
429	vit_base_patch14_dinov2-lvd142m
430	compact_resnet50_IT
431	resnet18_ecoset_full
432	ReAlnet03_cornet
433	resnet34_ecoset_full
434	VOneCORnet-S
435	resnet101_ecoset_full
436	yudixie_resnet50_distance_translation_0_240908
437	compact_vgg19_V4
438	yudixie_resnet18_distance_translation_0_240719
439	yudixie_resnet18_translation_rotation_0_240719
440	ReAlnet04_cornet
441	omnivore_swinB
442	yudixie_resnet18_distance_rotation_0_240719
443	yudixie_resnet18_category_class_0_240719
444	yudixie_resnet50_rotation_reg_0_240908
445	ReAlnet05_cornet
446	yudixie_resnet18_random_0_240719
447	resnet-18_test_m
448	yudixie_resnet50_distance_rotation_0_240908
449	yudixie_resnet18_cat_obj_class_all_latents_0_240719
450	SeLaVi-AVE
451	yudixie_resnet18_distance_translation_rotation_0_240719
452	yudixie_resnet18_object_class_0_240719
453	compact_resnet50_robust_V4
454	compact_vgg19_IT
455	ReAlnet06_cornet
456	yudixie_resnet50_translation_reg_0_240908
457	r3d_18
458	ReAlnet07_cornet
459	mc3_18
460	ReAlnet02_ALL
461	s3d
462	mvit_v1_b
463	ReAlnet04_ALL
464	compact_cornets_V4
465	ReAlnet01_cornet_fov16
466	ReAlnet03_ALL
467	compact_cornets_IT
468	SeLaVi-Kinetics400
469	ReAlnet05_ALL
470	SeLaVi-VGG-Sound
471	ReAlnet06_ALL
472	omnivore_swinS
473	r2plus1d_18
474	compact_resnet50_robust_IT
475	ReAlnet07_ALL
476	mvit_v2_s
477	SeLaVi-Kinetics-Sound
478	resnet152_ecoset_full
479	yudixie_resnet50_distance_translation_rotation_0_240908
480	yudixie_resnet50_translation_rotation_0_240908
481	resnet50_primary_visual_cortex
482	ReAlnet10_ALL
483	ReAlnet01_ALL
484	ReAlnet01_cornet_fov4
485	ReAlnet01_cornet_fov12
486	ReAlnet02_cornet
487	ReAlnet09_cornet
488	ReAlnet08_cornet
489	ReAlnet10_cornet
490	resnet18_fair
491	resnet50_ecoset_full
492	pr1_stl10_disentangled_alpha04
493	predictive_coding_pc
494	yudixie_wbh_object_class_scaling_0415_run_0
495	yudixie_wbh_object_class_scaling_0415_imagenet
496	yudixie_wbh_object_class_scaling_0415_run_3
497	yudixie_wbh_object_class_scaling_0415_run_2
498	yudixie_wbh_object_class_scaling_0415_run_1
499	deepeisnn_ei_cifar10_vgg19
500	deepeisnn_ei_cifar10_resnet18
501	deepeisnn_ei_imagenet_resnet18
502	dinov2_vitl14_reg_lc_featread
503	gabor_filter_entropy_4x4
504	gabor_filter_mean_abs_4x4_v2
505	gabor_filter_entropy_4x4_v2
506	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

0.43.

Note that scores are relative to this ceiling.

Data: Geirhos2021uniformnoise

Metric: error_consistency