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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021highpass-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	.875
2	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.858
3	convnext_xlarge:fb_in22k_ft_in1k	.851
4	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.827
5	vit_large_patch14_clip_224:laion2b_ft_in1k	.812
6	vit_large_patch14_clip_224:openai_ft_in1k	.807
7	convnext_large:fb_in22k_ft_in1k	.806
8	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.793
9	dinov2_vitl14_reg_lc	.769
10	convnext_large_in22k_supervised	.723
11	vit_large_patch14_clip_336:laion2b_ft_in1k	.722
12	dinov2_vitl14_lc	.721
13	fixres_resnext101_32x48d_wsl	.716
14	convnext_base:clip_laiona_augreg_ft_in1k_384	.709
15	dinov2_vitg14_lc	.677
16	vit_huge_clip336_laion	.652
17	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.652
18	dinov2_vitg14_reg_lc	.638
19	vit_large_clip336_openai	.636
20	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.592
21	convnext_base_fb_in22k_ft_in1k	.584
22	CLIP_resnet50	.550
23	CLIP_resnet50_float32	.550
24	vit_base_patch16_clip_224:openai_ft_in1k	.506
25	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.493
26	convnext_tiny:in12k_ft_in1k	.457
27	convnext_tiny_imagenet_full_seed-0	.442
28	convnext_xxlarge_clip	.437
29	CLIP-RN50	.422
30	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.419
31	effnetv2m_custom384	.410
32	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.404
33	convnext_large_clip_laion2b_finelayers	.386
34	SWSL_resnext101_32x8d	.380
35	resnext101_32x48d_wsl	.367
36	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.364
37	convnext_large_imagenet_full_seed-0	.355
38	dinov2_vitl14_lc_res336	.353
39	convnext_small_imagenet_full_seed-0	.330
40	convnext_base_fb_in1k	.327
41	cvt_cvt-13-384-in1k_4_LucyV4	.305
42	resnet_152_v2	.303
43	resnext101_32x16d_wsl	.294
44	cv_18_dagger_408_pretrained	.293
45	resnext101_32x32d_wsl	.291
46	convnext_base_imagenet_full_seed-0	.287
47	resnet50-VITO-8deg-cc	.285
48	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.262
49	vision_transformer_vit_large_patch16_224	.248
50	eva02_large_in22k	.234
51	convnext_tiny_sup	.226
52	focalnet_tiny_lrf_in1k	.220
53	resnet-152_v2_pytorch	.202
54	cvt_cvt-21-384-in1k_4_LucyV4	.200
55	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.196
56	cvt_cvt-21-224-in1k_4_LucyV4	.195
57	vit_relpos_base_patch16_clsgap_224:sw_in1k	.189
58	pnasnet_large_halfPrecision	.177
59	pnasnet_large	.177
60	resnext101_32x8d_wsl	.176
61	convnext_base_fb_in1k_gram_aligned_dinov3	.175
62	convnext_femto_ols:d1_in1k	.175
63	AlexNet_SIN_fov4	.169
64	regnety_032	.160
65	SWSL_resnet50	.154
66	cvt_cvt-13-224-in1k_4_LucyV4	.151
67	pnasnet_large_pytorch	.150
68	nasnet_large	.149
69	inception_v3	.143
70	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.142
71	CLIP_ViT-B_32	.139
72	inception_v4	.139
73	pnasnet_large-tf	.139
74	inception_v3_pytorch	.139
75	mehrer2020_alexnet_training_seed_01_fov4	.138
76	inception_v3-tf	.135
77	densenet-169	.132
78	convnext_small_imagenet_100_seed-0	.131
79	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.127
80	resnet_101_v2	.123
81	resnet50_st_wzc_seed6_2_323	.121
82	resnet-152_v2-tf	.120
83	xception	.118
84	tv_efficientnet-b1	.116
85	densenet-169-keras	.116
86	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.116
87	resnet50_ewconplus_wzc_seed6_2_323	.115
88	ViT_B_16_imagenet1k	.111
89	xception-keras	.110
90	seresnext50_32x4d	.103
91	resnet34_imagenet_full	.101
92	resnet_50_v2	.100
93	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.100
94	BiT-S-R50x3	.100
95	alexnet_training_seed_05	.096
96	alexnet_training_seed_01	.096
97	alexnet_training_seed_01_fov4	.096
98	alexnet_training_seed_01_fov12	.096
99	alexnet_training_seed_01_fov16	.096
100	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.095
101	deit_small_imagenet_1_seed-0	.095
102	deit_small_imagenet_10_seed-0	.095
103	resnet50_imagenet_10_seed-0	.095
104	imagenet_l2_10_0	.094
105	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.093
106	BiT-S-R152x2	.093
107	resnet50_FractalDB	.092
108	resnet50_ewconplus_wzc_seed5_2__323	.092
109	resnet50-vicregl0p9	.091
110	barlow-twins-resnet50	.091
111	alexnet_linf_8_robust	.090
112	alexnet_l2_3_robust	.090
113	resnet50_linf_8_robust	.089
114	inception_v4-tf	.089
115	resnet50_ewconplus_wzc_seed2_2__323	.088
116	alexnet_training_seed_07	.088
117	effnetb1_272x240	.088
118	alexnet_robust_correct	.086
119	custom_model_cv_18_dagger_408	.085
120	AdvProp_efficientnet-b4	.083
121	AT_efficientnet-b4	.083
122	mobilenet_v2_0_5_224	.082
123	blt_vs	.081
124	vonealexnet_gaussian_noise_std4_fixed	.081
125	mobilenet_v1_0.5_192	.080
126	resnet50_linf_4_robust	.079
127	densenet-201-keras	.078
128	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.078
129	resnet50_random_l2_perturb	.077
130	mobilenet_v1_0.25_128	.075
131	alexnet_training_seed_02	.075
132	alexnet_training_seed_04	.075
133	alexnet_training_seed_08	.075
134	alexnet_training_seed_10	.075
135	artResNet18_1	.075
136	resnet101	.075
137	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.075
138	resnet_50_v1_spiking_l4a	.074
139	alexnet_fov12	.074
140	BiT-S-R101x3	.074
141	convnext_small_imagenet_10_seed-0	.073
142	resnet50_byol	.073
143	mehrer2020_alexnet_training_seed_01_fov12	.073
144	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.073
145	texture_shape_alexnet_trained_on_SIN	.073
146	mehrer2020_alexnet_training_seed_01_fov16	.073
147	alexnet_training_seed_03	.072
148	mobilenet_v1_0.75_160	.072
149	vgg-19-keras	.072
150	nasnet_large-tf	.071
151	resnet50-vicreg	.071
152	alexnet_fov16	.067
153	alexnet_fov4	.067
154	BiT-S-R152x4	.066
155	voneresnet-50-robust	.066
156	vgg-16-keras	.066
157	mobilenet_v1_0.25_192	.065
158	antialias-resnet152	.064
159	mehrer2020_alexnet_training_seed_04	.064
160	mobilenet_v1_1.0_224	.064
161	AdvProp_efficientnet-b8	.064
162	resnet50-moclr8deg	.063
163	mobilenet_v2_0_5_192	.062
164	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.061
165	resnet50-SIN_IN_IN	.060
166	resnet_SIN_IN_FT_IN	.060
167	resnet50_robust_l2_eps1	.060
168	resnet_101_v1	.059
169	mobilenet_v1_0.75_128	.059
170	alexnet_reduced_aliasing_early_checkpoint	.059
171	konkle_alexnetgn_ipcl_ref01_primary_model	.059
172	AdvProp_efficientnet-b0	.056
173	resnet50_l2_3_robust	.056
174	mehrer2020_alexnet_training_seed_05	.056
175	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.056
176	AlexNet_SIN	.055
177	resnet-50-robust	.055
178	imagenet_l2_3_0	.055
179	resnet50_robust_l2_eps3	.055
180	mobilenet_v2_1.0_160-tf	.055
181	mobilenet_v1_0.25_160	.055
182	densenet-201	.054
183	densenet_201_pytorch	.054
184	efficientnet_b0	.054
185	mobilenet_v2_1_0_128	.054
186	vonegrcnn_62e_nobn	.053
187	alexnet_training_seed_06	.053
188	AlexNet_SIN_fov16	.053
189	AdvProp_efficientnet-b7	.053
190	mobilenet_v1_0.5_224	.053
191	AlexNet_SIN_fov12	.053
192	vonegrcnn_52e_full	.052
193	mehrer2020_alexnet_training_seed_02	.052
194	vonegrcnn_47e	.052
195	squeezenet1_0	.051
196	convnext_small_imagenet_1_seed-0	.051
197	CORnet-S	.051
198	mobilenet_v1_1.0_128	.051
199	deit_small_imagenet_100_seed-0	.050
200	mobilenet_v2_1_0_224	.050
201	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.050
202	ReAlnet07	.050
203	mobilenet_v2_1.0_224-tf	.050
204	mobilevit_small	.049
205	resnet50-SIN	.049
206	resnet50_eMMCR_Vanilla	.048
207	ReAlnet06	.048
208	resnet152_imagenet_full	.048
209	resnet50_st_wzc_2	.048
210	ReAlnet08	.047
211	cornet_s	.046
212	ReAlnet10	.046
213	mehrer2020_alexnet_training_seed_03	.046
214	resnet-18	.046
215	resnet50_imagenet_full	.045
216	alexnet_ks_torevert	.045
217	alexnet	.045
218	mobilenet_v2_0_75_192	.045
219	resnet50-simclr-vissl	.044
220	resnet50_st_wzc_seed7_2_323	.044
221	resnet50_st_wzc_seed3_2_323	.043
222	vonegrcnn_52e_full	.043
223	nasnet_mobile	.043
224	mobilenet_v2_1_3_224	.043
225	resnet101_imagenet_full	.043
226	efficientnet-b7	.043
227	vonegrcnn_47e	.043
228	mobilenet_v1_0.5_160	.042
229	resnet50-SIN_IN	.042
230	regnet_y_400mf	.042
231	resnet50_moco_v2	.041
232	nasnet_mobile-tf	.041
233	Res2Net50_26w_4s	.040
234	resnet50	.040
235	mobilenet_v1_1.0_160	.040
236	mobilenet_v2_0.75_96	.039
237	mobilenet_v1_0.5_128	.038
238	mobilenet_v1_0.25_224	.038
239	squeezenet1_1	.038
240	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.038
241	alexnet_random_linf8_perturb	.037
242	voneresnet-50	.037
243	vonegrcnn_62e_nobn	.037
244	mobilenet_v2_0.75_224-tf	.036
245	inception_v1	.036
246	mehrer2020_alexnet_training_seed_01	.036
247	deit_large_imagenet_full_seed-0	.036
248	mobilenet_v2_1_0_160	.036
249	mobilenet_v2_1.3_224-tf	.035
250	mobilenet_v2_1_0_192	.035
251	alexnet_early_checkpoint	.035
252	mobilenet_v2_1.0_192-tf	.034
253	texture_shape_resnet50_trained_on_SIN	.033
254	alexnet_training_seed_09	.033
255	mobilenet_v2_0_75_160	.033
256	mobilenet_v2_0.5_96	.033
257	resnet-50_untrained	.033
258	ReAlnet05	.032
259	resnet_152_v1	.031
260	resnet50_imagenet_1_seed-0	.031
261	ReAlnet01	.031
262	resnet-50-pytorch	.030
263	resnet50-sup	.030
264	resnet50_tutorial	.030
265	resnet_50_v1	.030
266	resnet-34	.030
267	inception_v1-tf	.030
268	BiT-S-R50x1	.028
269	resnet50_ewconplus_wzc	.027
270	ReAlnet03	.027
271	resnet_50_v1_spiking_l3	.027
272	resnet_50_v1_spiking	.026
273	ReAlnet02	.026
274	mobilenet_v2_0.35_96	.026
275	ViT_B_32_imagenet1k	.024
276	resnet50_random_linf8_perturb	.024
277	BiT-S-R101x1	.023
278	resnet50-barlow	.023
279	mobilenet_v2_0.75_160-tf	.023
280	mobilenet_v1_0.75_192	.023
281	mobilenet_v2_0.35_128	.022
282	ReAlnet09	.022
283	resnet-50_v1-tf	.022
284	mobilenet_v2_0_75_224	.022
285	antialiased-rnext101_32x8d	.022
286	inception_v2-tf	.022
287	mobilenet_v2_0.5_160	.021
288	mobilenet_v2_1.0_96	.021
289	mobilenet_v1_1.0_192	.020
290	antialiased-r50	.020
291	mobilenet_v2_0.75_192-tf	.019
292	deit_small_imagenet_full_seed-0	.019
293	mobilenet_v2_1.4_224-tf	.019
294	resnet_50_v1_spiking_l4	.019
295	mobilenet_v2_0.5_224-tf	.018
296	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.016
297	resnet50-vicregl0p75	.016
298	resnet50_imagenet_100_seed-0	.015
299	efficientnet_b0_imagenet_full	.015
300	resnet18_imagenet_full	.015
301	eicircuit_resnet18_bn_20260919	.015
302	resnet-152_v1-tf	.015
303	densenet-121-keras	.015
304	grcnn_109	.015
305	mobilenet_v2_1-4_224_pytorch	.015
306	mobilenet_v2_1_4_224	.015
307	0.5x_resnet-18_LC_w_sh_1_iter	.014
308	AdvProp_efficientnet-b6	.014
309	mobilenet_v1_0.75_224	.014
310	deit_base_imagenet_full_seed-0	.013
311	resnet50_simclr	.013
312	mobilenet_v2_0.5_192-tf	.013
313	mobilenet_v2_0.35_160	.012
314	mobilenet_v2_1.0_128-tf	.012
315	AT_efficientnet-b2	.010
316	AdvProp_efficientnet-b2	.010
317	mobilenet_v2_0.35_192	.010
318	vgg_16	.010
319	mobilenet_v2_0.35_224	.010
320	mobilenet_v2_0.5_128	.010
321	grcnn	.009
322	resnet-50_v2-tf	.007
323	resnet50_hvs_wzc	.006
324	mobilenet_v2_0.75_128	.005
325	resnet-101_v1-tf	.004
326	ReAlnet04	.004
327	alexnet_random_l2_3_perturb	.004
328	shufflenet_v2_x1_0	.004
329	vgg_19	.003
330	densenet-121	.003
331	resnet50-vitoimagevidnet8	.003
332	efficientnet_b2_imagenet_full	.002
333	ViT_L_32_imagenet1k	.002
334	efficientnet_b1_imagenet_full	.001
335	voneresnet-50-non_stochastic	.000
336	resnet-18-LC_w_sh_100_iter_conv_init_m
337	ViT-B/32
338	BiT-M-R50x3
339	BiT-M-R50x1
340	BiT-M-R152x2
341	resnet-18-LC_w_sh_1_iter_conv_init_m
342	resnet-18-LC_w_sh_10_iter_m
343	resnet-18-LC_w_sh_100_iter_m
344	resnet-18-LC_w_sh_10_iter_conv_init_m
345	resnet-18-LC_w_sh_1_iter_m
346	FrankRobWobv0
347	0.5x_resnet-18_LC
348	CORnetZ_CIFAR10
349	resnet18-local_aggregation
350	resnet18-deepcluster
351	r3m_resnet18
352	CORnet-Z
353	resnet18-instance_recognition
354	vggface
355	my-model
356	0.5x_resnet-18_LC_w_sh_10_iter
357	r3m_resnet50
358	resnet18-colorization
359	r3m_resnet34
360	resnet-18-LC_m
361	r3m_resnet50_nocrop
362	resnet18-supervised
363	resnet-18-LC_1st_conv_m
364	resnet-18-LC_conv_init_m
365	resnet18-contrastive_multiview
366	0.5x_resnet-18
367	RN50
368	0.5x_resnet-18_LC_w_sh_100_iter
369	RN50
370	resnet18-relative_position
371	resnet18-autoencoder
372	resnet18-simclr
373	ViT_L_32
374	ViT_B_32
375	resnet18-depth_prediction
376	ViT_B_16
377	r3m_resnet34_nocrop
378	resnet18-contrastive_predictive
379	omnivore_swinT
380	resnet-18-LC_untrained
381	resnet-18_untrained
382	resnet-50x2_untrained
383	dcgan
384	v1-pyr-nodown
385	unet_entire
386	CORnetZ_CIFAR10_bs32_20_04
387	pixels
388	dorinet_cornet_z
389	my-model
390	openclip
391	resnet50-cifar
392	resnet50_pretrained_with_retinal_waves
393	resnet50_ImageNet
394	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
395	ReAlnet07_ALL
396	yudixie_resnet50_distance_translation_rotation_0_240908
397	yudixie_resnet50_imagenet1kpret_0_240312
398	yudixie_resnet50_random_0_240908
399	yudixie_resnet50_imagenet1kpret_0_240908
400	yudixie_resnet50_cat_obj_class_all_latents_0_240908
401	yudixie_resnet50_object_class_0_240908
402	yudixie_resnet50_category_class_0_240908
403	resnet18_imagenet21kP
404	ConvLSTM
405	PredRNN
406	yudixie_resnet50_distance_reg_0_240908
407	SimVP
408	TAU
409	MIM
410	hmax
411	vit_base_patch16_dinov3-lvd1689m
412	ReAlnet01_cornet
413	briaai_rmbg_1_4
414	compact_resnet50_V4
415	yudixie_resnet18_translation_reg_0_240719
416	yudixie_resnet18_distance_reg_0_240719
417	yolos_tiny
418	yudixie_resnet18_rotation_reg_0_240719
419	ReAlnet02_cornet
420	yudixie_resnet18_imagenet1kpret_0_240719
421	eBarlow_lmda_02_1000ep
422	ReAlnet03_cornet
423	compact_resnet50_IT
424	vit_base_patch14_dinov2-lvd142m
425	resnet18_ecoset_full
426	resnet34_ecoset_full
427	ReAlnet01_cornet_fov4
428	VOneCORnet-S
429	resnet101_ecoset_full
430	resnet152_ecoset_full
431	yudixie_resnet50_rotation_reg_0_240908
432	yudixie_resnet50_distance_translation_0_240908
433	yudixie_resnet50_distance_rotation_0_240908
434	compact_vgg19_V4
435	yudixie_resnet18_distance_translation_0_240719
436	yudixie_resnet18_translation_rotation_0_240719
437	vit_base_patch14_reg4_dinov2-lvd142m
438	yudixie_resnet18_category_class_0_240719
439	yudixie_resnet18_random_0_240719
440	yudixie_resnet18_cat_obj_class_all_latents_0_240719
441	resnet-18_test_m
442	SeLaVi-AVE
443	yudixie_resnet18_distance_translation_rotation_0_240719
444	yudixie_resnet18_object_class_0_240719
445	compact_resnet50_robust_V4
446	compact_vgg19_IT
447	r3d_18
448	yudixie_resnet50_translation_reg_0_240908
449	omnivore_swinS
450	mc3_18
451	yudixie_resnet50_translation_rotation_0_240908
452	ReAlnet07_cornet
453	s3d
454	ReAlnet02_ALL
455	mvit_v1_b
456	ReAlnet04_ALL
457	ReAlnet01_cornet_fov16
458	compact_cornets_V4
459	ReAlnet08_cornet
460	ReAlnet03_ALL
461	omnivore_swinB
462	compact_cornets_IT
463	SeLaVi-Kinetics400
464	ReAlnet05_ALL
465	ReAlnet09_cornet
466	SeLaVi-VGG-Sound
467	ReAlnet06_ALL
468	SeLaVi-Kinetics-Sound
469	compact_resnet50_robust_IT
470	r2plus1d_18
471	mvit_v2_s
472	ReAlnet10_cornet
473	resnet50_ecoset_full
474	ReAlnet08_ALL
475	yudixie_resnet18_distance_rotation_0_240719
476	ReAlnet09_ALL
477	ReAlnet04_cornet
478	ReAlnet05_cornet
479	resnet50_primary_visual_cortex
480	ReAlnet10_ALL
481	ReAlnet01_ALL
482	ReAlnet01_cornet_fov12
483	ReAlnet06_cornet
484	resnet18_fair
485	pr1_stl10_disentangled_alpha04
486	deit3_base_patch16_224_fb_in22k_ft_in1k
487	yudixie_wbh_object_class_scaling_0415_run_0
488	yudixie_wbh_object_class_scaling_0415_run_3
489	yudixie_wbh_object_class_scaling_0415_imagenet
490	yudixie_wbh_object_class_scaling_0415_run_2
491	yudixie_wbh_object_class_scaling_0415_run_1
492	deepeisnn_ei_cifar10_vgg19
493	deepeisnn_ei_cifar10_resnet18
494	deepeisnn_ei_imagenet_resnet18
495	dinov2_vitl14_reg_lc_featread
496	gabor_filter_entropy_4x4
497	gabor_filter_entropy_4x4_v2
498	gabor_filter_entropy_4x4_v2_forcedCosine
499	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

0.44.

Note that scores are relative to this ceiling.

Data: Geirhos2021highpass

Metric: error_consistency