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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021sketch-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge_clip	.835
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.776
3	vit_large_patch14_clip_224:openai_ft_in1k	.776
4	convnext_large_clip_laion2b_finelayers	.768
5	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.746
6	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.742
7	vit_large_patch14_clip_336:laion2b_ft_in1k	.734
8	vit_huge_clip336_laion	.715
9	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.700
10	SWSL_resnext101_32x8d	.699
11	vit_large_clip336_openai	.693
12	eva02_large_in22k	.689
13	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.678
14	vit_large_patch14_clip_224:laion2b_ft_in1k	.669
15	dinov2_vitg14_reg_lc	.667
16	CLIP_resnet50	.666
17	CLIP_resnet50_float32	.666
18	dinov2_vitl14_lc_res336	.666
19	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.663
20	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.658
21	convnext_base:clip_laiona_augreg_ft_in1k_384	.658
22	CLIP-RN50	.630
23	dinov2_vitl14_reg_lc	.597
24	dinov2_vitl14_lc	.597
25	convnext_xlarge:fb_in22k_ft_in1k	.594
26	vit_base_patch16_clip_224:openai_ft_in1k	.585
27	convnext_large_in22k_supervised	.580
28	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.578
29	fixres_resnext101_32x48d_wsl	.576
30	CLIP_ViT-B_32	.559
31	convnext_large:fb_in22k_ft_in1k	.556
32	dinov2_vitg14_lc	.548
33	resnext101_32x16d_wsl	.539
34	resnext101_32x48d_wsl	.512
35	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.481
36	SWSL_resnet50	.461
37	resnext101_32x32d_wsl	.460
38	effnetv2m_custom384	.452
39	convnext_base_fb_in22k_ft_in1k	.440
40	deit3_base_patch16_224_fb_in22k_ft_in1k	.437
41	resnext101_32x8d_wsl	.425
42	vision_transformer_vit_large_patch16_224	.421
43	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.382
44	convnext_tiny:in12k_ft_in1k	.336
45	cvt_cvt-13-384-in1k_4_LucyV4	.331
46	deit3_base_patch16_224_fb_in1k	.316
47	vit_relpos_base_patch16_clsgap_224:sw_in1k	.314
48	cvt_cvt-21-384-in1k_4_LucyV4	.293
49	convnext_large_imagenet_full_seed-0	.287
50	effnetb1_272x240	.283
51	convnext_small_imagenet_full_seed-0	.278
52	convnext_tiny_imagenet_full_seed-0	.276
53	convnext_base_imagenet_full_seed-0	.274
54	focalnet_tiny_lrf_in1k	.274
55	cv_18_dagger_408_pretrained	.271
56	pnasnet_large_halfPrecision	.267
57	pnasnet_large	.267
58	convnext_base_fb_in1k	.255
59	resnet_152_v2	.253
60	convnext_femto_ols:d1_in1k	.247
61	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.245
62	cvt_cvt-13-224-in1k_4_LucyV4	.242
63	resnet_50_v2	.242
64	cvt_cvt-21-224-in1k_4_LucyV4	.234
65	seresnext50_32x4d	.233
66	pnasnet_large-tf	.232
67	resnet50_st_wzc_seed6_2_323	.223
68	nasnet_large	.221
69	resnet-152_v2_pytorch	.220
70	resnet-152_v2-tf	.220
71	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.213
72	resnet50_st_wzc_seed7_2_323	.212
73	inception_v4	.212
74	inception_v3	.207
75	resnet_101_v2	.205
76	xception-keras	.204
77	regnety_032	.204
78	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.202
79	convnext_tiny_sup	.198
80	deit_large_imagenet_full_seed-0	.198
81	resnet101	.191
82	resnet50_st_wzc_seed3_2_323	.177
83	resnet152_imagenet_full	.177
84	resnet50_ewconplus_wzc_seed2_2__323	.172
85	inception_v3-tf	.172
86	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.169
87	mehrer2020_alexnet_training_seed_01_fov4	.164
88	vgg_19	.163
89	resnet101_imagenet_full	.163
90	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.161
91	resnet50_random_l2_perturb	.161
92	nasnet_large-tf	.160
93	antialias-resnet152	.159
94	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.157
95	resnet_101_v1	.155
96	resnet50_imagenet_full	.155
97	deit_base_imagenet_full_seed-0	.153
98	inception_v4-tf	.153
99	resnet50-VITO-8deg-cc	.149
100	densenet-121-keras	.147
101	resnet-50_v2-tf	.145
102	AdvProp_efficientnet-b6	.143
103	resnet50_ewconplus_wzc	.143
104	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.142
105	densenet-121	.141
106	antialiased-rnext101_32x8d	.139
107	AdvProp_efficientnet-b4	.138
108	AT_efficientnet-b4	.138
109	resnet50_ewconplus_wzc_seed5_2__323	.137
110	resnet50_random_linf8_perturb	.136
111	resnet50	.135
112	efficientnet_b0	.132
113	resnet_152_v1	.131
114	resnet50_st_wzc_2	.128
115	resnet_50_v1_spiking	.127
116	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.127
117	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.125
118	efficientnet-b7	.125
119	efficientnet_b0_imagenet_full	.125
120	alexnet_fov4	.124
121	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.124
122	densenet-169-keras	.124
123	densenet-201	.121
124	grcnn_109	.120
125	resnet50_ewconplus_wzc_seed6_2_323	.119
126	Res2Net50_26w_4s	.119
127	densenet-169	.119
128	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.119
129	densenet-201-keras	.118
130	resnet50_byol	.118
131	cornet_s	.117
132	efficientnet_b2_imagenet_full	.117
133	AdvProp_efficientnet-b7	.116
134	AT_efficientnet-b2	.115
135	AdvProp_efficientnet-b2	.115
136	antialiased-r50	.115
137	BiT-S-R101x3	.114
138	resnet50-SIN_IN_IN	.114
139	resnet_SIN_IN_FT_IN	.114
140	resnet-34	.113
141	resnet50_hvs_wzc	.113
142	custom_model_cv_18_dagger_408	.112
143	ijepa_vith14_linhead	.112
144	resnet18_imagenet_full	.112
145	mobilenet_v2_1_0_192	.112
146	resnet34_imagenet_full	.111
147	convnext_small_imagenet_100_seed-0	.111
148	BiT-S-R152x4	.111
149	BiT-S-R50x3	.110
150	vgg_16	.109
151	resnet-152_v1-tf	.107
152	mobilenet_v2_1_0_224	.105
153	nasnet_mobile-tf	.104
154	mobilenet_v2_1_3_224	.104
155	resnet50_tutorial	.103
156	resnet_50_v1	.103
157	resnet-50-pytorch	.103
158	resnet50-sup	.103
159	deit_small_imagenet_full_seed-0	.102
160	BiT-S-R50x1	.102
161	resnet50-SIN_IN	.101
162	tv_efficientnet-b1	.101
163	grcnn	.099
164	mobilenet_v2_1.4_224-tf	.098
165	convnext_base_fb_in1k_gram_aligned_dinov3	.098
166	xception	.097
167	voneresnet-50-non_stochastic	.097
168	resnet50_vicreg_linhead	.097
169	nasnet_mobile	.097
170	ViT_B_16_imagenet1k	.095
171	inception_v1	.095
172	efficientnet_b1_imagenet_full	.094
173	resnet50-moclr8deg	.093
174	ViT_L_32_imagenet1k	.092
175	ReAlnet06	.091
176	mobilenet_v2_0_5_224	.091
177	ReAlnet01	.090
178	mobilenet_v2_1.3_224-tf	.090
179	mobilenet_v1_1.0_224	.088
180	resnet50_moco_v2	.088
181	inception_v2-tf	.088
182	ReAlnet03	.088
183	resnet50-vitoimagevidnet8	.086
184	resnet50_byol_linhead	.086
185	AlexNet_SIN_fov4	.086
186	eicircuit_resnet18_bn_20260919	.086
187	resnet-101_v1-tf	.084
188	BiT-S-R152x2	.083
189	ReAlnet04	.082
190	ReAlnet02	.080
191	resnet50_barlowtwins_linhead	.080
192	CORnet-S	.078
193	resnet50_simclr_linhead_01norm	.078
194	mobilenet_v2_1_0_160	.077
195	mobilenet_v2_0_75_224	.076
196	mobilenet_v1_1.0_192	.075
197	ReAlnet09	.075
198	inception_v1-tf	.073
199	vonegrcnn_52e_full	.073
200	mobilenet_v2_1.0_224-tf	.072
201	resnet50_simsiam_linhead	.072
202	resnet-18	.072
203	mobilenet_v1_1.0_160	.070
204	ReAlnet07	.070
205	ReAlnet05	.070
206	ReAlnet08	.069
207	blt_vs	.068
208	vonegrcnn_52e_full	.068
209	vonegrcnn_62e_nobn	.068
210	AdvProp_efficientnet-b8	.068
211	resnet-50_v1-tf	.067
212	ViT_B_32_imagenet1k	.067
213	ReAlnet10	.067
214	regnet_y_400mf	.066
215	mobilenet_v2_0_5_192	.066
216	mobilenet_v2_1-4_224_pytorch	.064
217	mobilenet_v2_1_4_224	.064
218	vonegrcnn_62e_nobn	.064
219	vgg-16-keras	.063
220	resnet_50_v1_spiking_l4a	.063
221	vonegrcnn_47e	.063
222	mobilenet_v2_1.0_192-tf	.062
223	voneresnet-50	.062
224	vonegrcnn_47e	.061
225	mobilenet_v2_0_75_160	.060
226	mobilenet_v2_1.0_160-tf	.058
227	mobilenet_v1_0.75_160	.058
228	mobilenet_v2_0.75_160-tf	.057
229	BiT-S-R101x1	.057
230	resnet50_linf_4_robust	.056
231	mobilenet_v2_0.75_224-tf	.056
232	mobilenet_v2_1_0_128	.055
233	mobilenet_v2_0_75_192	.055
234	squeezenet1_0	.055
235	mobilenet_v1_0.5_224	.054
236	mobilenet_v2_0.35_160	.053
237	mobilenet_v1_0.75_224	.053
238	mobilenet_v2_0.5_192-tf	.053
239	squeezenet1_1	.052
240	mobilenet_v2_0.75_128	.052
241	resnet_50_v1_spiking_l4	.052
242	mobilenet_v2_0.5_224-tf	.051
243	voneresnet-50-robust	.051
244	mobilenet_v2_0.75_192-tf	.049
245	resnet50_imagenet_100_seed-0	.049
246	mobilenet_v2_0.5_160	.049
247	mobilenet_v1_0.75_192	.049
248	mobilenet_v2_0.5_128	.048
249	alexnet_reduced_aliasing_early_checkpoint	.048
250	mobilenet_v1_0.5_192	.047
251	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.047
252	shufflenet_v2_x1_0	.046
253	alexnet_random_l2_3_perturb	.046
254	vonealexnet_gaussian_noise_std4_fixed	.046
255	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.046
256	alexnet_random_linf8_perturb	.045
257	mobilenet_v2_0.35_192	.045
258	resnet50_l2_3_robust	.045
259	resnet50_eMMCR_Vanilla	.044
260	mobilenet_v1_0.75_128	.043
261	resnet50_robust_l2_eps1	.043
262	mobilenet_v2_1.0_96	.043
263	resnet50_linf_8_robust	.042
264	mehrer2020_alexnet_training_seed_03	.042
265	texture_shape_resnet50_trained_on_SIN	.042
266	mobilenet_v2_0.35_224	.042
267	mobilenet_v2_0.35_128	.042
268	mobilenet_v2_1.0_128-tf	.041
269	mehrer2020_alexnet_training_seed_04	.041
270	resnet50_simclr	.041
271	alexnet	.041
272	alexnet_ks_torevert	.041
273	vgg-19-keras	.040
274	alexnet_early_checkpoint	.039
275	mobilenet_v1_0.5_128	.039
276	AdvProp_efficientnet-b0	.039
277	alexnet_robust_correct	.039
278	alexnet_l2_3_robust	.038
279	mobilenet_v2_0.75_96	.038
280	mobilenet_v2_0.35_96	.038
281	mehrer2020_alexnet_training_seed_01	.036
282	alexnet_linf_8_robust	.036
283	mobilenet_v1_0.5_160	.035
284	0.5x_resnet-18_LC_w_sh_1_iter	.034
285	konkle_alexnetgn_ipcl_ref01_primary_model	.034
286	mobilenet_v1_1.0_128	.032
287	mobilenet_v2_0.5_96	.032
288	mehrer2020_alexnet_training_seed_05	.032
289	deit_small_imagenet_100_seed-0	.032
290	mobilenet_v1_0.25_192	.032
291	resnet50-vicreg	.032
292	mobilenet_v1_0.25_224	.031
293	mehrer2020_alexnet_training_seed_02	.031
294	AlexNet_SIN	.031
295	texture_shape_alexnet_trained_on_SIN	.031
296	resnet-50-robust	.030
297	imagenet_l2_3_0	.030
298	resnet50_robust_l2_eps3	.030
299	mobilenet_v1_0.25_160	.029
300	imagenet_l2_10_0	.028
301	AlexNet_SIN_fov12	.027
302	alexnet_fov12	.027
303	AlexNet_SIN_fov16	.026
304	resnet50-simclr-vissl	.026
305	deit_small_imagenet_10_seed-0	.025
306	convnext_small_imagenet_10_seed-0	.025
307	deit_small_imagenet_1_seed-0	.025
308	mehrer2020_alexnet_training_seed_01_fov16	.025
309	alexnet_training_seed_02	.024
310	alexnet_training_seed_04	.024
311	alexnet_training_seed_08	.024
312	alexnet_training_seed_10	.024
313	alexnet_training_seed_07	.024
314	alexnet_training_seed_09	.023
315	alexnet_fov16	.023
316	resnet_50_v1_spiking_l3	.023
317	mehrer2020_alexnet_training_seed_01_fov12	.022
318	resnet-50_untrained	.022
319	resnet50-SIN	.022
320	mobilenet_v1_0.25_128	.021
321	resnet50_imagenet_10_seed-0	.020
322	convnext_small_imagenet_1_seed-0	.020
323	barlow-twins-resnet50	.014
324	resnet50-vicregl0p9	.014
325	artResNet18_1	.014
326	resnet50_FractalDB	.011
327	alexnet_training_seed_06	.009
328	alexnet_training_seed_03	.005
329	resnet50_imagenet_1_seed-0	.003
330	resnet50-vicregl0p75	.003
331	alexnet_training_seed_05	.002
332	alexnet_training_seed_01	.002
333	alexnet_training_seed_01_fov4	.002
334	alexnet_training_seed_01_fov12	.002
335	alexnet_training_seed_01_fov16	.002
336	resnet50-barlow	.001
337	resnet-18-LC_w_sh_100_iter_conv_init_m
338	ViT-B/32
339	BiT-M-R50x3
340	BiT-M-R50x1
341	BiT-M-R152x2
342	resnet-18-LC_w_sh_1_iter_conv_init_m
343	resnet-18-LC_w_sh_1_iter_m
344	resnet-18-LC_w_sh_10_iter_m
345	resnet-18_test_m
346	resnet-18-LC_w_sh_100_iter_m
347	resnet-18-LC_w_sh_10_iter_conv_init_m
348	FrankRobWobv0
349	0.5x_resnet-18_LC
350	CORnetZ_CIFAR10
351	resnet18-local_aggregation
352	resnet18-deepcluster
353	r3m_resnet18
354	CORnet-Z
355	vggface
356	my-model
357	resnet18-instance_recognition
358	0.5x_resnet-18_LC_w_sh_10_iter
359	r3m_resnet50
360	r3m_resnet34
361	resnet-18-LC_m
362	r3m_resnet50_nocrop
363	resnet18-supervised
364	resnet-18-LC_1st_conv_m
365	resnet-18-LC_conv_init_m
366	resnet18-contrastive_multiview
367	0.5x_resnet-18
368	resnet18-colorization
369	RN50
370	0.5x_resnet-18_LC_w_sh_100_iter
371	RN50
372	resnet18-relative_position
373	resnet18-autoencoder
374	resnet18-simclr
375	omnivore_swinT
376	ViT_L_32
377	ViT_B_32
378	resnet18-depth_prediction
379	ViT_B_16
380	r3m_resnet34_nocrop
381	resnet18-contrastive_predictive
382	resnet-18-LC_untrained
383	resnet-18_untrained
384	resnet-50x2_untrained
385	dcgan
386	unet_entire
387	omnivore_swinS
388	v1-pyr-nodown
389	CORnetZ_CIFAR10_bs32_20_04
390	pixels
391	dorinet_cornet_z
392	my-model
393	openclip
394	resnet50-cifar
395	resnet50_pretrained_with_retinal_waves
396	resnet50_ImageNet
397	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
398	yudixie_resnet50_random_0_240908
399	yudixie_resnet50_imagenet1kpret_0_240908
400	yudixie_resnet50_imagenet1kpret_0_240312
401	yudixie_resnet50_object_class_0_240908
402	yudixie_resnet50_category_class_0_240908
403	ConvLSTM
404	yudixie_resnet50_distance_reg_0_240908
405	PredRNN
406	SimVP
407	TAU
408	briaai_rmbg_1_4
409	MIM
410	hmax
411	densenet_201_pytorch
412	pnasnet_large_pytorch
413	ReAlnet01_cornet
414	inception_v3_pytorch
415	yolos_tiny
416	ReAlnet03_cornet
417	yudixie_resnet18_imagenet1kpret_0_240719
418	eBarlow_lmda_02_1000ep
419	compact_resnet50_V4
420	vit_base_patch16_dinov3-lvd1689m
421	vit_base_patch14_reg4_dinov2-lvd142m
422	ReAlnet01_cornet_fov16
423	resnet18_ecoset_full
424	resnet34_ecoset_full
425	ReAlnet01_cornet_fov4
426	resnet50_ecoset_full
427	compact_resnet50_robust_V4
428	yudixie_resnet50_distance_translation_0_240908
429	yudixie_resnet18_distance_translation_0_240719
430	yudixie_resnet18_translation_rotation_0_240719
431	yudixie_resnet18_distance_rotation_0_240719
432	compact_resnet50_IT
433	ReAlnet01_cornet_fov12
434	yudixie_resnet18_category_class_0_240719
435	vit_base_patch14_dinov2-lvd142m
436	yudixie_resnet50_distance_rotation_0_240908
437	ReAlnet05_cornet
438	yudixie_resnet50_rotation_reg_0_240908
439	yudixie_resnet18_random_0_240719
440	compact_vgg19_V4
441	yudixie_resnet18_distance_translation_rotation_0_240719
442	yudixie_resnet18_object_class_0_240719
443	SeLaVi-AVE
444	yudixie_resnet18_translation_reg_0_240719
445	yudixie_resnet18_distance_reg_0_240719
446	ReAlnet06_cornet
447	yudixie_resnet50_translation_reg_0_240908
448	r3d_18
449	compact_vgg19_IT
450	ReAlnet01_ALL
451	mc3_18
452	yudixie_resnet50_translation_rotation_0_240908
453	s3d
454	ReAlnet08_cornet
455	mvit_v1_b
456	ReAlnet02_ALL
457	yudixie_resnet18_rotation_reg_0_240719
458	omnivore_swinB
459	VOneCORnet-S
460	compact_cornets_V4
461	resnet18_imagenet21kP
462	ReAlnet03_ALL
463	ReAlnet09_cornet
464	ReAlnet04_ALL
465	SeLaVi-Kinetics400
466	compact_cornets_IT
467	SeLaVi-VGG-Sound
468	ReAlnet05_ALL
469	r2plus1d_18
470	ReAlnet06_ALL
471	ReAlnet10_cornet
472	SeLaVi-Kinetics-Sound
473	mvit_v2_s
474	yudixie_resnet50_distance_translation_rotation_0_240908
475	ReAlnet07_ALL
476	compact_resnet50_robust_IT
477	ReAlnet08_ALL
478	yudixie_resnet18_cat_obj_class_all_latents_0_240719
479	resnet50_primary_visual_cortex
480	ReAlnet09_ALL
481	yudixie_resnet50_cat_obj_class_all_latents_0_240908
482	ReAlnet10_ALL
483	ReAlnet02_cornet
484	ReAlnet04_cornet
485	ReAlnet07_cornet
486	resnet101_ecoset_full
487	resnet152_ecoset_full
488	resnet18_fair
489	pr1_stl10_disentangled_alpha04
490	predictive_coding_pc
491	yudixie_wbh_object_class_scaling_0415_run_0
492	yudixie_wbh_object_class_scaling_0415_run_3
493	yudixie_wbh_object_class_scaling_0415_imagenet
494	yudixie_wbh_object_class_scaling_0415_run_2
495	yudixie_wbh_object_class_scaling_0415_run_1
496	deepeisnn_ei_cifar10_vgg19
497	deepeisnn_ei_cifar10_resnet18
498	deepeisnn_ei_imagenet_resnet18
499	dinov2_vitl14_reg_lc_featread
500	gabor_filter_entropy_4x4
501	gabor_filter_entropy_4x4_v2
502	gabor_filter_mean_abs_4x4_v2
503	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

0.37.

Note that scores are relative to this ceiling.

Data: Geirhos2021sketch

Metric: error_consistency