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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	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.463
48	vit_relpos_base_patch16_clsgap_224:sw_in1k	.463
49	deit_small_imagenet_full_seed-0	.460
50	deit_base_imagenet_full_seed-0	.460
51	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.454
52	focalnet_tiny_lrf_in1k	.436
53	convnext_tiny:in12k_ft_in1k	.435
54	CLIP-RN50	.419
55	convnext_tiny_imagenet_full_seed-0	.419
56	resnet_50_v2	.415
57	pnasnet_large_halfPrecision	.410
58	pnasnet_large	.410
59	ViT_B_16_imagenet1k	.409
60	ViT_L_32_imagenet1k	.406
61	inception_v4	.400
62	resnet_101_v2	.397
63	nasnet_large	.396
64	cvt_cvt-21-384-in1k_4_LucyV4	.391
65	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.385
66	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.382
67	convnext_small_imagenet_full_seed-0	.379
68	convnext_femto_ols:d1_in1k	.379
69	resnet-152_v2_pytorch	.371
70	dinov2_vitl14_lc_res336	.370
71	cvt_cvt-21-224-in1k_4_LucyV4	.368
72	convnext_base_fb_in1k	.366
73	resnet50_st_wzc_seed6_2_323	.365
74	cvt_cvt-13-224-in1k_4_LucyV4	.361
75	dinov2_vitg14_reg_lc	.361
76	regnety_032	.355
77	convnext_base_imagenet_full_seed-0	.354
78	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.352
79	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.338
80	pnasnet_large-tf	.338
81	antialias-resnet152	.326
82	xception-keras	.317
83	cv_18_dagger_408_pretrained	.314
84	resnet101	.313
85	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.311
86	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.306
87	nasnet_large-tf	.305
88	inception_v3-tf	.299
89	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.297
90	inception_v4-tf	.295
91	resnet152_imagenet_full	.290
92	resnet-152_v2-tf	.285
93	seresnext50_32x4d	.274
94	resnet50_byol	.274
95	resnet_152_v1	.270
96	resnet_101_v1	.268
97	antialiased-rnext101_32x8d	.268
98	inception_v3	.260
99	convnext_tiny_sup	.260
100	resnet50_ewconplus_wzc_seed5_2__323	.259
101	AdvProp_efficientnet-b4	.258
102	AT_efficientnet-b4	.258
103	grcnn_109	.252
104	inception_v3_pytorch	.252
105	resnet50	.251
106	resnet50_st_wzc_seed3_2_323	.247
107	ViT_B_32_imagenet1k	.244
108	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.243
109	resnet50_ewconplus_wzc_seed2_2__323	.238
110	resnet50_moco_v2	.232
111	convnext_base_fb_in1k_gram_aligned_dinov3	.230
112	resnet50_ewconplus_wzc	.230
113	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.225
114	AdvProp_efficientnet-b6	.221
115	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.218
116	tv_efficientnet-b1	.215
117	densenet-121-keras	.214
118	antialiased-r50	.214
119	resnet50_imagenet_full	.213
120	voneresnet-50-non_stochastic	.209
121	convnext_small_imagenet_100_seed-0	.207
122	densenet-169-keras	.203
123	AdvProp_efficientnet-b7	.203
124	resnet34_imagenet_full	.203
125	resnet-50_v2-tf	.202
126	densenet-121	.201
127	resnet50_st_wzc_2	.197
128	densenet-201-keras	.197
129	grcnn	.194
130	resnet_50_v1_spiking	.190
131	resnet50-moclr8deg	.187
132	densenet-169	.186
133	mobilenet_v2_1_0_224	.186
134	resnet50_tutorial	.185
135	resnet_50_v1	.185
136	resnet-50-pytorch	.185
137	resnet50-sup	.185
138	efficientnet-b7	.185
139	vgg_19	.184
140	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.180
141	resnet50_hvs_wzc	.179
142	BiT-S-R152x4	.175
143	pnasnet_large_pytorch	.175
144	Res2Net50_26w_4s	.174
145	resnet50_ewconplus_wzc_seed6_2_323	.169
146	xception	.168
147	resnet-50_v1-tf	.167
148	resnet101_imagenet_full	.165
149	AT_efficientnet-b2	.165
150	AdvProp_efficientnet-b2	.165
151	resnet18_imagenet_full	.163
152	densenet-201	.161
153	densenet_201_pytorch	.161
154	ReAlnet04	.156
155	custom_model_cv_18_dagger_408	.156
156	resnet-101_v1-tf	.155
157	vonegrcnn_62e_nobn	.153
158	efficientnet_b1_imagenet_full	.153
159	efficientnet_b0	.152
160	eBarlow_lmda_02_1000ep	.147
161	inception_v1-tf	.144
162	deit_small_imagenet_100_seed-0	.143
163	vonegrcnn_47e	.141
164	efficientnet_b2_imagenet_full	.140
165	resnet50_random_linf8_perturb	.140
166	vonegrcnn_52e_full	.139
167	resnet-152_v1-tf	.138
168	mobilenet_v2_1.0_224-tf	.135
169	ReAlnet03	.135
170	nasnet_mobile	.133
171	mobilenet_v2_1.4_224-tf	.133
172	voneresnet-50	.132
173	ReAlnet09	.132
174	eicircuit_resnet18_bn_20260919	.131
175	vonegrcnn_62e_nobn	.130
176	resnet50-SIN_IN	.129
177	BiT-S-R50x3	.129
178	blt_vs	.129
179	mobilenet_v2_1_0_192	.127
180	BiT-S-R101x3	.127
181	ReAlnet07	.127
182	vonegrcnn_52e_full	.126
183	vonegrcnn_47e	.126
184	ReAlnet08	.126
185	resnet50_random_l2_perturb	.126
186	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.125
187	inception_v2-tf	.124
188	cornet_s	.124
189	AdvProp_efficientnet-b8	.123
190	mobilenet_v2_1-4_224_pytorch	.122
191	mobilenet_v2_1_4_224	.122
192	ReAlnet02	.121
193	voneresnet-50-robust	.119
194	mobilenet_v2_0_5_192	.116
195	ReAlnet06	.115
196	nasnet_mobile-tf	.113
197	resnet50-vitoimagevidnet8	.113
198	mobilenet_v1_0.75_224	.112
199	ReAlnet10	.112
200	mobilenet_v2_0_5_224	.111
201	vgg-19-keras	.111
202	resnet50_l2_3_robust	.110
203	resnet50_linf_4_robust	.110
204	inception_v1	.109
205	resnet50-SIN_IN_IN	.109
206	resnet_SIN_IN_FT_IN	.109
207	mobilenet_v2_1.0_160-tf	.109
208	resnet_50_v1_spiking_l4a	.108
209	mobilenet_v2_1_0_160	.108
210	resnet50_linf_8_robust	.107
211	resnet-50-robust	.103
212	imagenet_l2_3_0	.103
213	resnet50_robust_l2_eps3	.103
214	vgg_16	.100
215	ReAlnet01	.100
216	BiT-S-R50x1	.100
217	CORnet-S	.097
218	vgg-16-keras	.097
219	efficientnet_b0_imagenet_full	.096
220	mobilenet_v2_1_3_224	.096
221	mobilenet_v2_0.5_192-tf	.096
222	mobilenet_v2_0.75_192-tf	.095
223	mobilenet_v1_1.0_160	.095
224	ReAlnet05	.094
225	alexnet_fov4	.092
226	mobilenet_v2_1.3_224-tf	.091
227	resnet50_eMMCR_Vanilla	.090
228	regnet_y_400mf	.087
229	imagenet_l2_10_0	.086
230	mobilenet_v2_1.0_192-tf	.085
231	resnet50_imagenet_10_seed-0	.085
232	deit_small_imagenet_10_seed-0	.085
233	deit_small_imagenet_1_seed-0	.085
234	mobilenet_v2_0.75_160-tf	.085
235	mobilenet_v2_0.5_224-tf	.084
236	mobilenet_v2_0_75_160	.084
237	resnet50_robust_l2_eps1	.082
238	mobilenet_v1_0.75_192	.081
239	alexnet_linf_8_robust	.081
240	resnet-18	.081
241	mobilenet_v2_0.75_96	.081
242	resnet-34	.080
243	alexnet_fov16	.080
244	convnext_small_imagenet_10_seed-0	.078
245	mobilenet_v2_1.0_96	.078
246	mobilenet_v2_0_75_192	.077
247	mobilenet_v2_0.35_224	.077
248	mobilenet_v2_0.5_96	.077
249	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
250	alexnet_training_seed_05	.074
251	alexnet_training_seed_01	.074
252	alexnet_training_seed_01_fov4	.074
253	alexnet_training_seed_01_fov12	.074
254	alexnet_training_seed_01_fov16	.074
255	mobilenet_v2_0.75_128	.072
256	texture_shape_resnet50_trained_on_SIN	.071
257	alexnet_random_l2_3_perturb	.070
258	alexnet_l2_3_robust	.070
259	mobilenet_v2_0.75_224-tf	.069
260	resnet-50_untrained	.067
261	vonealexnet_gaussian_noise_std4_fixed	.066
262	mobilenet_v2_1_0_128	.065
263	resnet50-SIN	.064
264	alexnet_reduced_aliasing_early_checkpoint	.063
265	mobilenet_v2_0.35_96	.061
266	mobilenet_v2_0_75_224	.061
267	mobilenet_v2_0.35_192	.061
268	alexnet_robust_correct	.060
269	shufflenet_v2_x1_0	.060
270	BiT-S-R152x2	.059
271	texture_shape_alexnet_trained_on_SIN	.059
272	alexnet_training_seed_03	.058
273	alexnet_training_seed_09	.057
274	squeezenet1_1	.057
275	mobilenet_v1_0.75_128	.056
276	alexnet_ks_torevert	.056
277	alexnet	.056
278	AdvProp_efficientnet-b0	.055
279	mobilenet_v1_0.5_224	.055
280	resnet50-simclr-vissl	.054
281	AlexNet_SIN	.054
282	barlow-twins-resnet50	.052
283	alexnet_random_linf8_perturb	.049
284	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.049
285	resnet50_simclr	.047
286	mobilenet_v1_1.0_224	.045
287	mobilenet_v1_1.0_192	.045
288	mobilenet_v2_0.35_128	.044
289	BiT-S-R101x1	.044
290	alexnet_early_checkpoint	.043
291	AlexNet_SIN_fov4	.040
292	resnet50-vicreg	.038
293	resnet50-vicregl0p9	.038
294	mobilenet_v2_1.0_128-tf	.037
295	alexnet_fov12	.034
296	artResNet18_1	.032
297	resnet_50_v1_spiking_l4	.032
298	alexnet_training_seed_02	.031
299	alexnet_training_seed_08	.031
300	alexnet_training_seed_04	.031
301	alexnet_training_seed_10	.031
302	mobilenet_v2_0.5_160	.030
303	AlexNet_SIN_fov16	.029
304	mobilenet_v2_0.35_160	.029
305	0.5x_resnet-18_LC_w_sh_1_iter	.028
306	mobilenet_v1_0.25_160	.026
307	resnet50_FractalDB	.026
308	resnet50_imagenet_1_seed-0	.025
309	resnet_50_v1_spiking_l3	.024
310	alexnet_training_seed_06	.024
311	mobilenet_v1_0.25_224	.022
312	mobilenet_v2_0.5_128	.020
313	mobilenet_v1_0.25_192	.019
314	mobilenet_v1_0.25_128	.017
315	mobilenet_v1_1.0_128	.016
316	squeezenet1_0	.014
317	mobilenet_v1_0.5_192	.013
318	alexnet_training_seed_07	.013
319	mobilevit_small	.013
320	mobilenet_v1_0.75_160	.013
321	konkle_alexnetgn_ipcl_ref01_primary_model	.013
322	resnet50_imagenet_100_seed-0	.007
323	mobilenet_v1_0.5_160	.006
324	resnet50-barlow	.006
325	convnext_small_imagenet_1_seed-0	.005
326	AlexNet_SIN_fov12	.004
327	mobilenet_v1_0.5_128	.003
328	resnet50-vicregl0p75	.003
329	resnet-18-LC_w_sh_100_iter_conv_init_m
330	ViT-B/32
331	BiT-M-R50x3
332	BiT-M-R50x1
333	BiT-M-R152x2
334	resnet-18-LC_w_sh_1_iter_conv_init_m
335	resnet-18-LC_w_sh_10_iter_m
336	resnet-18-LC_w_sh_100_iter_m
337	resnet-18-LC_w_sh_10_iter_conv_init_m
338	resnet-18-LC_w_sh_1_iter_m
339	FrankRobWobv0
340	0.5x_resnet-18_LC
341	CORnetZ_CIFAR10
342	resnet18-local_aggregation
343	resnet18-deepcluster
344	r3m_resnet18
345	CORnet-Z
346	resnet18-instance_recognition
347	vggface
348	my-model
349	0.5x_resnet-18_LC_w_sh_10_iter
350	r3m_resnet50
351	resnet18-colorization
352	r3m_resnet34
353	resnet-18-LC_m
354	r3m_resnet50_nocrop
355	resnet18-supervised
356	resnet-18-LC_1st_conv_m
357	resnet-18-LC_conv_init_m
358	resnet18-contrastive_multiview
359	0.5x_resnet-18
360	RN50
361	0.5x_resnet-18_LC_w_sh_100_iter
362	RN50
363	resnet18-relative_position
364	resnet18-autoencoder
365	resnet18-simclr
366	ViT_L_32
367	ViT_B_32
368	resnet18-depth_prediction
369	ViT_B_16
370	r3m_resnet34_nocrop
371	resnet18-contrastive_predictive
372	omnivore_swinT
373	resnet-18-LC_untrained
374	resnet-18_untrained
375	resnet-50x2_untrained
376	dcgan
377	unet_entire
378	v1-pyr-nodown
379	CORnetZ_CIFAR10_bs32_20_04
380	pixels
381	dorinet_cornet_z
382	my-model
383	openclip
384	resnet50-cifar
385	resnet50_pretrained_with_retinal_waves
386	resnet50_ImageNet
387	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
388	yudixie_resnet50_random_0_240908
389	yudixie_resnet50_imagenet1kpret_0_240908
390	yudixie_resnet50_cat_obj_class_all_latents_0_240908
391	yudixie_resnet50_imagenet1kpret_0_240312
392	yudixie_resnet50_category_class_0_240908
393	resnet18_imagenet21kP
394	yudixie_resnet50_distance_reg_0_240908
395	ConvLSTM
396	PredRNN
397	SimVP
398	TAU
399	MIM
400	hmax
401	ReAlnet01_cornet
402	yolos_tiny
403	resnet152_ecoset_full
404	compact_resnet50_V4
405	yudixie_resnet18_translation_reg_0_240719
406	yudixie_resnet18_distance_reg_0_240719
407	ReAlnet03_cornet
408	yudixie_resnet18_rotation_reg_0_240719
409	ReAlnet02_cornet
410	yudixie_resnet18_imagenet1kpret_0_240719
411	vit_base_patch16_dinov3-lvd1689m
412	resnet34_ecoset_full
413	compact_resnet50_IT
414	resnet50_ecoset_full
415	vit_base_patch14_dinov2-lvd142m
416	vit_base_patch14_reg4_dinov2-lvd142m
417	resnet101_ecoset_full
418	compact_resnet50_robust_V4
419	ReAlnet01_cornet_fov4
420	yudixie_resnet50_distance_translation_0_240908
421	ReAlnet01_cornet_fov12
422	omnivore_swinB
423	yudixie_resnet18_distance_rotation_0_240719
424	yudixie_resnet50_distance_rotation_0_240908
425	yudixie_resnet18_category_class_0_240719
426	yudixie_resnet18_random_0_240719
427	ReAlnet05_cornet
428	yudixie_resnet18_cat_obj_class_all_latents_0_240719
429	yudixie_resnet50_rotation_reg_0_240908
430	resnet-18_test_m
431	compact_vgg19_V4
432	yudixie_resnet18_distance_translation_rotation_0_240719
433	yudixie_resnet18_object_class_0_240719
434	SeLaVi-AVE
435	r3d_18
436	ReAlnet06_cornet
437	yudixie_resnet50_translation_reg_0_240908
438	yudixie_resnet50_translation_rotation_0_240908
439	ReAlnet01_ALL
440	mc3_18
441	ReAlnet07_cornet
442	s3d
443	mvit_v1_b
444	ReAlnet08_cornet
445	ReAlnet01_cornet_fov16
446	ReAlnet02_ALL
447	ReAlnet03_ALL
448	VOneCORnet-S
449	compact_cornets_V4
450	ReAlnet04_ALL
451	ReAlnet09_cornet
452	SeLaVi-Kinetics400
453	compact_cornets_IT
454	SeLaVi-VGG-Sound
455	ReAlnet05_ALL
456	SeLaVi-Kinetics-Sound
457	compact_vgg19_IT
458	omnivore_swinS
459	mvit_v2_s
460	compact_resnet50_robust_IT
461	ReAlnet06_ALL
462	r2plus1d_18
463	ReAlnet10_cornet
464	ReAlnet07_ALL
465	resnet18_ecoset_full
466	yudixie_resnet50_distance_translation_rotation_0_240908
467	ReAlnet08_ALL
468	yudixie_resnet18_translation_rotation_0_240719
469	yudixie_resnet18_distance_translation_0_240719
470	resnet50_primary_visual_cortex
471	ReAlnet04_cornet
472	ReAlnet09_ALL
473	yudixie_resnet50_object_class_0_240908
474	briaai_rmbg_1_4
475	ReAlnet10_ALL
476	resnet18_fair
477	predictive_coding_pc
478	yudixie_wbh_object_class_scaling_0415_run_0
479	yudixie_wbh_object_class_scaling_0415_run_3
480	yudixie_wbh_object_class_scaling_0415_imagenet
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_entropy_4x4_v2
489	gabor_filter_entropy_4x4_v2_forcedCosine
490	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