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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021lowpass-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	SWSL_resnext101_32x8d	.730
2	resnext101_32x32d_wsl	.695
3	convnext_xxlarge_clip	.695
4	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
5	convnext_large:fb_in22k_ft_in1k	.667
6	vit_large_patch14_clip_224:openai_ft_in1k	.663
7	deit3_base_patch16_224_fb_in22k_ft_in1k	.655
8	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.648
9	fixres_resnext101_32x48d_wsl	.630
10	resnet50-VITO-8deg-cc	.625
11	vit_large_patch14_clip_336:laion2b_ft_in1k	.623
12	SWSL_resnet50	.613
13	vit_large_patch14_clip_224:laion2b_ft_in1k	.603
14	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.602
15	deit3_base_patch16_224_fb_in1k	.601
16	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.600
17	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.589
18	vit_large_clip336_openai	.588
19	resnext101_32x48d_wsl	.579
20	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.578
21	convnext_large_in22k_supervised	.568
22	resnext101_32x8d_wsl	.563
23	convnext_base_fb_in22k_ft_in1k	.559
24	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.554
25	dinov2_vitg14_lc	.553
26	CLIP_resnet50	.544
27	CLIP_resnet50_float32	.544
28	deit_large_imagenet_full_seed-0	.543
29	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.537
30	resnext101_32x16d_wsl	.535
31	vit_base_patch16_clip_224:openai_ft_in1k	.535
32	convnext_large_clip_laion2b_finelayers	.530
33	convnext_xlarge:fb_in22k_ft_in1k	.527
34	effnetv2m_custom384	.527
35	dinov2_vitl14_lc	.520
36	convnext_base:clip_laiona_augreg_ft_in1k_384	.516
37	dinov2_vitl14_reg_lc	.505
38	eva02_large_in22k	.504
39	vision_transformer_vit_large_patch16_224	.499
40	resnet_152_v2	.498
41	effnetb1_272x240	.497
42	CLIP_ViT-B_32	.496
43	cvt_cvt-13-384-in1k_4_LucyV4	.492
44	vit_huge_clip336_laion	.483
45	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.478
46	convnext_large_imagenet_full_seed-0	.471
47	ijepa_vith14_linhead	.469
48	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.463
49	vit_relpos_base_patch16_clsgap_224:sw_in1k	.463
50	deit_small_imagenet_full_seed-0	.460
51	deit_base_imagenet_full_seed-0	.460
52	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.454
53	focalnet_tiny_lrf_in1k	.436
54	convnext_tiny:in12k_ft_in1k	.435
55	CLIP-RN50	.419
56	convnext_tiny_imagenet_full_seed-0	.419
57	resnet_50_v2	.415
58	pnasnet_large_halfPrecision	.410
59	pnasnet_large	.410
60	ViT_B_16_imagenet1k	.409
61	ViT_L_32_imagenet1k	.406
62	inception_v4	.400
63	resnet_101_v2	.397
64	nasnet_large	.396
65	cvt_cvt-21-384-in1k_4_LucyV4	.391
66	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.385
67	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.382
68	convnext_small_imagenet_full_seed-0	.379
69	convnext_femto_ols:d1_in1k	.379
70	resnet-152_v2_pytorch	.371
71	dinov2_vitl14_lc_res336	.370
72	cvt_cvt-21-224-in1k_4_LucyV4	.368
73	convnext_base_fb_in1k	.366
74	resnet50_st_wzc_seed6_2_323	.365
75	cvt_cvt-13-224-in1k_4_LucyV4	.361
76	dinov2_vitg14_reg_lc	.361
77	regnety_032	.355
78	convnext_base_imagenet_full_seed-0	.354
79	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.352
80	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.338
81	pnasnet_large-tf	.338
82	antialias-resnet152	.326
83	xception-keras	.317
84	cv_18_dagger_408_pretrained	.314
85	resnet101	.313
86	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.311
87	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.306
88	nasnet_large-tf	.305
89	inception_v3-tf	.299
90	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.297
91	inception_v4-tf	.295
92	resnet152_imagenet_full	.290
93	resnet-152_v2-tf	.285
94	seresnext50_32x4d	.274
95	resnet50_byol	.274
96	resnet_152_v1	.270
97	resnet_101_v1	.268
98	antialiased-rnext101_32x8d	.268
99	inception_v3	.260
100	convnext_tiny_sup	.260
101	resnet50_ewconplus_wzc_seed5_2__323	.259
102	AdvProp_efficientnet-b4	.258
103	AT_efficientnet-b4	.258
104	grcnn_109	.252
105	inception_v3_pytorch	.252
106	resnet50	.251
107	resnet50_st_wzc_seed3_2_323	.247
108	ViT_B_32_imagenet1k	.244
109	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.243
110	resnet50_ewconplus_wzc_seed2_2__323	.238
111	resnet50_moco_v2	.232
112	convnext_base_fb_in1k_gram_aligned_dinov3	.230
113	resnet50_ewconplus_wzc	.230
114	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.225
115	AdvProp_efficientnet-b6	.221
116	resnet50_simsiam_linhead	.219
117	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.218
118	resnet50_barlowtwins_linhead	.215
119	tv_efficientnet-b1	.215
120	densenet-121-keras	.214
121	antialiased-r50	.214
122	resnet50_imagenet_full	.213
123	voneresnet-50-non_stochastic	.209
124	convnext_small_imagenet_100_seed-0	.207
125	densenet-169-keras	.203
126	AdvProp_efficientnet-b7	.203
127	resnet34_imagenet_full	.203
128	resnet-50_v2-tf	.202
129	densenet-121	.201
130	resnet50_st_wzc_2	.197
131	densenet-201-keras	.197
132	grcnn	.194
133	resnet_50_v1_spiking	.190
134	resnet50-moclr8deg	.187
135	densenet-169	.186
136	mobilenet_v2_1_0_224	.186
137	resnet50_tutorial	.185
138	resnet_50_v1	.185
139	resnet-50-pytorch	.185
140	resnet50-sup	.185
141	efficientnet-b7	.185
142	vgg_19	.184
143	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.180
144	resnet50_byol_linhead	.180
145	resnet50_hvs_wzc	.179
146	BiT-S-R152x4	.175
147	pnasnet_large_pytorch	.175
148	Res2Net50_26w_4s	.174
149	resnet50_ewconplus_wzc_seed6_2_323	.169
150	xception	.168
151	resnet-50_v1-tf	.167
152	resnet101_imagenet_full	.165
153	AT_efficientnet-b2	.165
154	AdvProp_efficientnet-b2	.165
155	resnet18_imagenet_full	.163
156	densenet-201	.161
157	densenet_201_pytorch	.161
158	ReAlnet04	.156
159	custom_model_cv_18_dagger_408	.156
160	resnet-101_v1-tf	.155
161	resnet50_vicreg_linhead	.153
162	vonegrcnn_62e_nobn	.153
163	efficientnet_b1_imagenet_full	.153
164	efficientnet_b0	.152
165	eBarlow_lmda_02_1000ep	.147
166	inception_v1-tf	.144
167	deit_small_imagenet_100_seed-0	.143
168	vonegrcnn_47e	.141
169	efficientnet_b2_imagenet_full	.140
170	resnet50_random_linf8_perturb	.140
171	vonegrcnn_52e_full	.139
172	resnet-152_v1-tf	.138
173	mehrer2020_alexnet_training_seed_01_fov4	.136
174	mobilenet_v2_1.0_224-tf	.135
175	ReAlnet03	.135
176	nasnet_mobile	.133
177	mobilenet_v2_1.4_224-tf	.133
178	voneresnet-50	.132
179	ReAlnet09	.132
180	eicircuit_resnet18_bn_20260919	.131
181	vonegrcnn_62e_nobn	.130
182	resnet50-SIN_IN	.129
183	BiT-S-R50x3	.129
184	blt_vs	.129
185	mobilenet_v2_1_0_192	.127
186	BiT-S-R101x3	.127
187	ReAlnet07	.127
188	vonegrcnn_52e_full	.126
189	vonegrcnn_47e	.126
190	ReAlnet08	.126
191	resnet50_random_l2_perturb	.126
192	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.125
193	inception_v2-tf	.124
194	cornet_s	.124
195	AdvProp_efficientnet-b8	.123
196	mobilenet_v2_1-4_224_pytorch	.122
197	mobilenet_v2_1_4_224	.122
198	ReAlnet02	.121
199	voneresnet-50-robust	.119
200	resnet50_simclr_linhead_01norm	.116
201	mobilenet_v2_0_5_192	.116
202	ReAlnet06	.115
203	nasnet_mobile-tf	.113
204	resnet50-vitoimagevidnet8	.113
205	mobilenet_v1_0.75_224	.112
206	ReAlnet10	.112
207	mobilenet_v2_0_5_224	.111
208	vgg-19-keras	.111
209	resnet50_l2_3_robust	.110
210	resnet50_linf_4_robust	.110
211	inception_v1	.109
212	resnet50-SIN_IN_IN	.109
213	resnet_SIN_IN_FT_IN	.109
214	mobilenet_v2_1.0_160-tf	.109
215	resnet_50_v1_spiking_l4a	.108
216	mobilenet_v2_1_0_160	.108
217	resnet50_linf_8_robust	.107
218	resnet-50-robust	.103
219	imagenet_l2_3_0	.103
220	resnet50_robust_l2_eps3	.103
221	vgg_16	.100
222	ReAlnet01	.100
223	BiT-S-R50x1	.100
224	CORnet-S	.097
225	vgg-16-keras	.097
226	efficientnet_b0_imagenet_full	.096
227	mobilenet_v2_1_3_224	.096
228	mobilenet_v2_0.5_192-tf	.096
229	mobilenet_v2_0.75_192-tf	.095
230	mobilenet_v1_1.0_160	.095
231	ReAlnet05	.094
232	alexnet_fov4	.092
233	mobilenet_v2_1.3_224-tf	.091
234	resnet50_eMMCR_Vanilla	.090
235	regnet_y_400mf	.087
236	imagenet_l2_10_0	.086
237	mobilenet_v2_1.0_192-tf	.085
238	resnet50_imagenet_10_seed-0	.085
239	deit_small_imagenet_10_seed-0	.085
240	deit_small_imagenet_1_seed-0	.085
241	mobilenet_v2_0.75_160-tf	.085
242	mobilenet_v2_0.5_224-tf	.084
243	mobilenet_v2_0_75_160	.084
244	resnet50_robust_l2_eps1	.082
245	mobilenet_v1_0.75_192	.081
246	alexnet_linf_8_robust	.081
247	resnet-18	.081
248	mobilenet_v2_0.75_96	.081
249	resnet-34	.080
250	alexnet_fov16	.080
251	convnext_small_imagenet_10_seed-0	.078
252	mobilenet_v2_1.0_96	.078
253	mobilenet_v2_0_75_192	.077
254	mobilenet_v2_0.35_224	.077
255	mobilenet_v2_0.5_96	.077
256	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
257	alexnet_training_seed_05	.074
258	alexnet_training_seed_01	.074
259	alexnet_training_seed_01_fov4	.074
260	alexnet_training_seed_01_fov12	.074
261	alexnet_training_seed_01_fov16	.074
262	mobilenet_v2_0.75_128	.072
263	texture_shape_resnet50_trained_on_SIN	.071
264	alexnet_random_l2_3_perturb	.070
265	alexnet_l2_3_robust	.070
266	mobilenet_v2_0.75_224-tf	.069
267	resnet-50_untrained	.067
268	vonealexnet_gaussian_noise_std4_fixed	.066
269	mobilenet_v2_1_0_128	.065
270	resnet50-SIN	.064
271	alexnet_reduced_aliasing_early_checkpoint	.063
272	mobilenet_v2_0.35_96	.061
273	mobilenet_v2_0_75_224	.061
274	mobilenet_v2_0.35_192	.061
275	alexnet_robust_correct	.060
276	shufflenet_v2_x1_0	.060
277	BiT-S-R152x2	.059
278	texture_shape_alexnet_trained_on_SIN	.059
279	alexnet_training_seed_03	.058
280	alexnet_training_seed_09	.057
281	squeezenet1_1	.057
282	mobilenet_v1_0.75_128	.056
283	alexnet_ks_torevert	.056
284	alexnet	.056
285	AdvProp_efficientnet-b0	.055
286	mobilenet_v1_0.5_224	.055
287	resnet50-simclr-vissl	.054
288	AlexNet_SIN	.054
289	barlow-twins-resnet50	.052
290	alexnet_random_linf8_perturb	.049
291	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.049
292	resnet50_simclr	.047
293	mehrer2020_alexnet_training_seed_03	.045
294	mobilenet_v1_1.0_224	.045
295	mobilenet_v1_1.0_192	.045
296	mobilenet_v2_0.35_128	.044
297	BiT-S-R101x1	.044
298	mehrer2020_alexnet_training_seed_01	.043
299	mehrer2020_alexnet_training_seed_05	.043
300	alexnet_early_checkpoint	.043
301	mehrer2020_alexnet_training_seed_01_fov16	.042
302	AlexNet_SIN_fov4	.040
303	resnet50-vicreg	.038
304	mehrer2020_alexnet_training_seed_01_fov12	.038
305	resnet50-vicregl0p9	.038
306	mobilenet_v2_1.0_128-tf	.037
307	mehrer2020_alexnet_training_seed_04	.035
308	alexnet_fov12	.034
309	artResNet18_1	.032
310	resnet_50_v1_spiking_l4	.032
311	alexnet_training_seed_02	.031
312	alexnet_training_seed_08	.031
313	alexnet_training_seed_04	.031
314	alexnet_training_seed_10	.031
315	mobilenet_v2_0.5_160	.030
316	AlexNet_SIN_fov16	.029
317	mobilenet_v2_0.35_160	.029
318	0.5x_resnet-18_LC_w_sh_1_iter	.028
319	mobilenet_v1_0.25_160	.026
320	mehrer2020_alexnet_training_seed_02	.026
321	resnet50_FractalDB	.026
322	resnet50_imagenet_1_seed-0	.025
323	resnet_50_v1_spiking_l3	.024
324	alexnet_training_seed_06	.024
325	mobilenet_v1_0.25_224	.022
326	mobilenet_v2_0.5_128	.020
327	mobilenet_v1_0.25_192	.019
328	mobilenet_v1_0.25_128	.017
329	mobilenet_v1_1.0_128	.016
330	squeezenet1_0	.014
331	mobilenet_v1_0.5_192	.013
332	alexnet_training_seed_07	.013
333	mobilevit_small	.013
334	mobilenet_v1_0.75_160	.013
335	konkle_alexnetgn_ipcl_ref01_primary_model	.013
336	resnet50_imagenet_100_seed-0	.007
337	mobilenet_v1_0.5_160	.006
338	resnet50-barlow	.006
339	convnext_small_imagenet_1_seed-0	.005
340	AlexNet_SIN_fov12	.004
341	mobilenet_v1_0.5_128	.003
342	resnet50-vicregl0p75	.003
343	resnet-18-LC_w_sh_100_iter_conv_init_m
344	ViT-B/32
345	BiT-M-R50x3
346	BiT-M-R50x1
347	BiT-M-R152x2
348	resnet-18-LC_w_sh_1_iter_conv_init_m
349	resnet-18-LC_w_sh_10_iter_m
350	resnet-18-LC_w_sh_100_iter_m
351	resnet-18-LC_w_sh_10_iter_conv_init_m
352	resnet-18-LC_w_sh_1_iter_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	vggface
362	my-model
363	0.5x_resnet-18_LC_w_sh_10_iter
364	r3m_resnet50
365	resnet18-colorization
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	resnet18-depth_prediction
383	ViT_B_16
384	r3m_resnet34_nocrop
385	resnet18-contrastive_predictive
386	omnivore_swinT
387	resnet-18-LC_untrained
388	resnet-18_untrained
389	resnet-50x2_untrained
390	dcgan
391	unet_entire
392	v1-pyr-nodown
393	CORnetZ_CIFAR10_bs32_20_04
394	pixels
395	dorinet_cornet_z
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	yudixie_resnet50_random_0_240908
403	yudixie_resnet50_imagenet1kpret_0_240908
404	yudixie_resnet50_cat_obj_class_all_latents_0_240908
405	yudixie_resnet50_imagenet1kpret_0_240312
406	yudixie_resnet50_category_class_0_240908
407	resnet18_imagenet21kP
408	yudixie_resnet50_distance_reg_0_240908
409	ConvLSTM
410	PredRNN
411	SimVP
412	TAU
413	MIM
414	hmax
415	ReAlnet01_cornet
416	yolos_tiny
417	resnet152_ecoset_full
418	compact_resnet50_V4
419	yudixie_resnet18_translation_reg_0_240719
420	yudixie_resnet18_distance_reg_0_240719
421	ReAlnet03_cornet
422	yudixie_resnet18_rotation_reg_0_240719
423	ReAlnet02_cornet
424	yudixie_resnet18_imagenet1kpret_0_240719
425	vit_base_patch16_dinov3-lvd1689m
426	resnet34_ecoset_full
427	compact_resnet50_IT
428	resnet50_ecoset_full
429	vit_base_patch14_dinov2-lvd142m
430	vit_base_patch14_reg4_dinov2-lvd142m
431	resnet101_ecoset_full
432	compact_resnet50_robust_V4
433	ReAlnet01_cornet_fov4
434	yudixie_resnet50_distance_translation_0_240908
435	omnivore_swinB
436	yudixie_resnet18_distance_rotation_0_240719
437	yudixie_resnet50_distance_rotation_0_240908
438	yudixie_resnet18_category_class_0_240719
439	yudixie_resnet18_random_0_240719
440	ReAlnet05_cornet
441	yudixie_resnet18_cat_obj_class_all_latents_0_240719
442	yudixie_resnet50_rotation_reg_0_240908
443	resnet-18_test_m
444	compact_vgg19_V4
445	yudixie_resnet18_distance_translation_rotation_0_240719
446	yudixie_resnet18_object_class_0_240719
447	SeLaVi-AVE
448	r3d_18
449	ReAlnet06_cornet
450	yudixie_resnet50_translation_reg_0_240908
451	yudixie_resnet50_translation_rotation_0_240908
452	ReAlnet01_ALL
453	mc3_18
454	s3d
455	mvit_v1_b
456	ReAlnet08_cornet
457	ReAlnet01_cornet_fov16
458	ReAlnet02_ALL
459	ReAlnet03_ALL
460	VOneCORnet-S
461	compact_cornets_V4
462	ReAlnet04_ALL
463	ReAlnet09_cornet
464	SeLaVi-Kinetics400
465	compact_cornets_IT
466	SeLaVi-VGG-Sound
467	ReAlnet05_ALL
468	SeLaVi-Kinetics-Sound
469	compact_vgg19_IT
470	omnivore_swinS
471	mvit_v2_s
472	compact_resnet50_robust_IT
473	ReAlnet06_ALL
474	r2plus1d_18
475	ReAlnet07_ALL
476	resnet18_ecoset_full
477	yudixie_resnet50_distance_translation_rotation_0_240908
478	ReAlnet08_ALL
479	yudixie_resnet18_translation_rotation_0_240719
480	yudixie_resnet18_distance_translation_0_240719
481	resnet50_primary_visual_cortex
482	ReAlnet04_cornet
483	ReAlnet09_ALL
484	yudixie_resnet50_object_class_0_240908
485	briaai_rmbg_1_4
486	ReAlnet10_ALL
487	ReAlnet01_cornet_fov12
488	ReAlnet07_cornet
489	ReAlnet10_cornet
490	resnet18_fair
491	predictive_coding_pc
492	yudixie_wbh_object_class_scaling_0415_run_0
493	yudixie_wbh_object_class_scaling_0415_run_3
494	yudixie_wbh_object_class_scaling_0415_imagenet
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_entropy_4x4_v2
503	gabor_filter_entropy_4x4_v2_forcedCosine
504	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

0.47.

Note that scores are relative to this ceiling.

Data: Geirhos2021lowpass

Metric: error_consistency