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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	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.776
2	vit_large_patch14_clip_224:openai_ft_in1k	.776
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.746
4	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.742
5	vit_large_patch14_clip_336:laion2b_ft_in1k	.734
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.700
7	SWSL_resnext101_32x8d	.699
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.678
9	vit_large_patch14_clip_224:laion2b_ft_in1k	.669
10	CLIP_resnet50	.666
11	CLIP_resnet50_float32	.666
12	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.663
13	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.658
14	convnext_base:clip_laiona_augreg_ft_in1k_384	.658
15	CLIP-RN50	.630
16	convnext_xlarge:fb_in22k_ft_in1k	.594
17	vit_base_patch16_clip_224:openai_ft_in1k	.585
18	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.578
19	fixres_resnext101_32x48d_wsl	.576
20	CLIP_ViT-B_32	.559
21	convnext_large:fb_in22k_ft_in1k	.556
22	resnext101_32x16d_wsl	.539
23	resnext101_32x48d_wsl	.512
24	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.481
25	SWSL_resnet50	.461
26	resnext101_32x32d_wsl	.460
27	effnetv2m_custom384	.452
28	convnext_base_fb_in22k_ft_in1k	.440
29	deit3_base_patch16_224_fb_in22k_ft_in1k	.437
30	resnext101_32x8d_wsl	.425
31	vision_transformer_vit_large_patch16_224	.421
32	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.382
33	convnext_tiny:in12k_ft_in1k	.336
34	cvt_cvt-13-384-in1k_4_LucyV4	.331
35	deit3_base_patch16_224_fb_in1k	.316
36	vit_relpos_base_patch16_clsgap_224:sw_in1k	.314
37	cvt_cvt-21-384-in1k_4_LucyV4	.293
38	convnext_large_imagenet_full_seed-0	.287
39	effnetb1_272x240	.283
40	convnext_small_imagenet_full_seed-0	.278
41	convnext_tiny_imagenet_full_seed-0	.276
42	convnext_base_imagenet_full_seed-0	.274
43	focalnet_tiny_lrf_in1k	.274
44	cv_18_dagger_408_pretrained	.271
45	pnasnet_large_halfPrecision	.267
46	pnasnet_large	.267
47	convnext_base_fb_in1k	.255
48	resnet_152_v2	.253
49	convnext_femto_ols:d1_in1k	.247
50	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.245
51	cvt_cvt-13-224-in1k_4_LucyV4	.242
52	resnet_50_v2	.242
53	cvt_cvt-21-224-in1k_4_LucyV4	.234
54	pnasnet_large-tf	.232
55	resnet50_st_wzc_seed6_2_323	.223
56	nasnet_large	.221
57	resnet-152_v2_pytorch	.220
58	resnet-152_v2-tf	.220
59	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.213
60	resnet50_st_wzc_seed7_2_323	.212
61	inception_v4	.212
62	resnet50_st_wzc_noseed_2_323	.207
63	inception_v3	.207
64	resnet_101_v2	.205
65	xception-keras	.204
66	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.202
67	convnext_tiny_sup	.198
68	resnet50_ewconplus_wzc_2_323	.198
69	deit_large_imagenet_full_seed-0	.198
70	resnet101	.191
71	resnet50_st_wzc_seed5_2_323	.184
72	resnet50_st_wzc_seed3_2_323	.177
73	resnet152_imagenet_full	.177
74	resnet50_ewconplus_wzc_seed3_2_323	.174
75	resnet50_ewconplus_wzc_seed2_2__323	.172
76	resnet50_st_wzc_2_323	.172
77	inception_v3-tf	.172
78	resnet50_st_wzc_seed4_2_323	.171
79	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.169
80	resnet50_ewconplus_noseed_2_323	.164
81	vgg_19	.163
82	resnet101_imagenet_full	.163
83	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.161
84	resnet50_random_l2_perturb	.161
85	nasnet_large-tf	.160
86	antialias-resnet152	.159
87	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.157
88	resnet_101_v1	.155
89	resnet50_imagenet_full	.155
90	deit_base_imagenet_full_seed-0	.153
91	inception_v4-tf	.153
92	resnet50-VITO-8deg-cc	.149
93	densenet-121-keras	.147
94	resnet50_ewconplus_wzc_seed4_2_323	.145
95	resnet-50_v2-tf	.145
96	AdvProp_efficientnet-b6	.143
97	resnet50_ewconplus_wzc	.143
98	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.142
99	densenet-121	.141
100	resnet50_ewconplus_wzc_seed7_2_323	.140
101	antialiased-rnext101_32x8d	.139
102	AdvProp_efficientnet-b4	.138
103	AT_efficientnet-b4	.138
104	resnet50_ewconplus_wzc_seed5_2__323	.137
105	resnet50_random_linf8_perturb	.136
106	resnet50	.135
107	efficientnet_b0	.132
108	resnet_152_v1	.131
109	resnet50_st_wzc_2	.128
110	resnet_50_v1_spiking	.127
111	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.127
112	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.125
113	efficientnet-b7	.125
114	efficientnet_b0_imagenet_full	.125
115	alexnet_fov4	.124
116	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.124
117	densenet-169-keras	.124
118	densenet-201	.121
119	grcnn_109	.120
120	resnet50_ewconplus_wzc_seed6_2_323	.119
121	Res2Net50_26w_4s	.119
122	densenet-169	.119
123	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.119
124	densenet-201-keras	.118
125	resnet50_byol	.118
126	cornet_s	.117
127	efficientnet_b2_imagenet_full	.117
128	AdvProp_efficientnet-b7	.116
129	AT_efficientnet-b2	.115
130	AdvProp_efficientnet-b2	.115
131	antialiased-r50	.115
132	BiT-S-R101x3	.114
133	resnet50-SIN_IN_IN	.114
134	resnet_SIN_IN_FT_IN	.114
135	resnet-34	.113
136	custom_model_cv_18_dagger_408	.112
137	resnet18_imagenet_full	.112
138	mobilenet_v2_1_0_192	.112
139	resnet34_imagenet_full	.111
140	convnext_small_imagenet_100_seed-0	.111
141	BiT-S-R152x4	.111
142	BiT-S-R50x3	.110
143	vgg_16	.109
144	resnet-152_v1-tf	.107
145	mobilenet_v2_1_0_224	.105
146	nasnet_mobile-tf	.104
147	mobilenet_v2_1_3_224	.104
148	resnet50_tutorial	.103
149	resnet_50_v1	.103
150	resnet-50-pytorch	.103
151	resnet50-sup	.103
152	deit_small_imagenet_full_seed-0	.102
153	BiT-S-R50x1	.102
154	resnet50-SIN_IN	.101
155	tv_efficientnet-b1	.101
156	grcnn	.099
157	mobilenet_v2_1.4_224-tf	.098
158	convnext_base_fb_in1k_gram_aligned_dinov3	.098
159	xception	.097
160	voneresnet-50-non_stochastic	.097
161	nasnet_mobile	.097
162	ViT_B_16_imagenet1k	.095
163	inception_v1	.095
164	efficientnet_b1_imagenet_full	.094
165	resnet50-moclr8deg	.093
166	ViT_L_32_imagenet1k	.092
167	ReAlnet06	.091
168	mobilenet_v2_0_5_224	.091
169	ReAlnet01	.090
170	mobilenet_v2_1.3_224-tf	.090
171	mobilenet_v1_1.0_224	.088
172	resnet50_moco_v2	.088
173	inception_v2-tf	.088
174	ReAlnet03	.088
175	resnet50-vitoimagevidnet8	.086
176	AlexNet_SIN_fov4	.086
177	resnet-101_v1-tf	.084
178	BiT-S-R152x2	.083
179	ReAlnet04	.082
180	ReAlnet02	.080
181	CORnet-S	.078
182	mobilenet_v2_1_0_160	.077
183	mobilenet_v2_0_75_224	.076
184	mobilenet_v1_1.0_192	.075
185	ReAlnet09	.075
186	inception_v1-tf	.073
187	vonegrcnn_52e_full	.073
188	mobilenet_v2_1.0_224-tf	.072
189	resnet-18	.072
190	mobilenet_v1_1.0_160	.070
191	ReAlnet07	.070
192	ReAlnet05	.070
193	ReAlnet08	.069
194	blt_vs	.068
195	vonegrcnn_52e_full	.068
196	vonegrcnn_62e_nobn	.068
197	AdvProp_efficientnet-b8	.068
198	resnet-50_v1-tf	.067
199	ViT_B_32_imagenet1k	.067
200	ReAlnet10	.067
201	regnet_y_400mf	.066
202	mobilenet_v2_0_5_192	.066
203	mobilenet_v2_1-4_224_pytorch	.064
204	mobilenet_v2_1_4_224	.064
205	vonegrcnn_62e_nobn	.064
206	vgg-16-keras	.063
207	resnet_50_v1_spiking_l4a	.063
208	vonegrcnn_47e	.063
209	mobilenet_v2_1.0_192-tf	.062
210	voneresnet-50	.062
211	vonegrcnn_47e	.061
212	mobilenet_v2_0_75_160	.060
213	mobilenet_v2_1.0_160-tf	.058
214	mobilenet_v1_0.75_160	.058
215	mobilenet_v2_0.75_160-tf	.057
216	BiT-S-R101x1	.057
217	resnet50_linf_4_robust	.056
218	mobilenet_v2_0.75_224-tf	.056
219	mobilenet_v2_1_0_128	.055
220	mobilenet_v2_0_75_192	.055
221	squeezenet1_0	.055
222	mobilenet_v1_0.5_224	.054
223	mobilenet_v2_0.35_160	.053
224	mobilenet_v1_0.75_224	.053
225	mobilenet_v2_0.5_192-tf	.053
226	squeezenet1_1	.052
227	mobilenet_v2_0.75_128	.052
228	resnet_50_v1_spiking_l4	.052
229	mobilenet_v2_0.5_224-tf	.051
230	voneresnet-50-robust	.051
231	mobilenet_v2_0.75_192-tf	.049
232	resnet50_imagenet_100_seed-0	.049
233	mobilenet_v2_0.5_160	.049
234	mobilenet_v1_0.75_192	.049
235	mobilenet_v2_0.5_128	.048
236	alexnet_reduced_aliasing_early_checkpoint	.048
237	mobilenet_v1_0.5_192	.047
238	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.047
239	shufflenet_v2_x1_0	.046
240	alexnet_random_l2_3_perturb	.046
241	vonealexnet_gaussian_noise_std4_fixed	.046
242	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.046
243	alexnet_random_linf8_perturb	.045
244	mobilenet_v2_0.35_192	.045
245	resnet50_l2_3_robust	.045
246	resnet50_eMMCR_Vanilla	.044
247	mobilenet_v1_0.75_128	.043
248	resnet50_robust_l2_eps1	.043
249	mobilenet_v2_1.0_96	.043
250	resnet50_linf_8_robust	.042
251	texture_shape_resnet50_trained_on_SIN	.042
252	mobilenet_v2_0.35_224	.042
253	mobilenet_v2_0.35_128	.042
254	mobilenet_v2_1.0_128-tf	.041
255	resnet50_simclr	.041
256	alexnet	.041
257	alexnet_ks_torevert	.041
258	vgg-19-keras	.040
259	alexnet_early_checkpoint	.039
260	mobilenet_v1_0.5_128	.039
261	AdvProp_efficientnet-b0	.039
262	alexnet_robust_correct	.039
263	alexnet_l2_3_robust	.038
264	mobilenet_v2_0.75_96	.038
265	mobilenet_v2_0.35_96	.038
266	alexnet_linf_8_robust	.036
267	mobilenet_v1_0.5_160	.035
268	0.5x_resnet-18_LC_w_sh_1_iter	.034
269	konkle_alexnetgn_ipcl_ref01_primary_model	.034
270	mobilenet_v1_1.0_128	.032
271	mobilenet_v2_0.5_96	.032
272	deit_small_imagenet_100_seed-0	.032
273	mobilenet_v1_0.25_192	.032
274	resnet50-vicreg	.032
275	mobilenet_v1_0.25_224	.031
276	AlexNet_SIN	.031
277	texture_shape_alexnet_trained_on_SIN	.031
278	resnet-50-robust	.030
279	imagenet_l2_3_0	.030
280	resnet50_robust_l2_eps3	.030
281	mobilenet_v1_0.25_160	.029
282	imagenet_l2_10_0	.028
283	AlexNet_SIN_fov12	.027
284	alexnet_fov12	.027
285	AlexNet_SIN_fov16	.026
286	resnet50-simclr-vissl	.026
287	deit_small_imagenet_10_seed-0	.025
288	convnext_small_imagenet_10_seed-0	.025
289	deit_small_imagenet_1_seed-0	.025
290	alexnet_training_seed_02	.024
291	alexnet_training_seed_04	.024
292	alexnet_training_seed_08	.024
293	alexnet_training_seed_10	.024
294	alexnet_training_seed_07	.024
295	alexnet_training_seed_09	.023
296	alexnet_fov16	.023
297	resnet_50_v1_spiking_l3	.023
298	resnet50-meshes-lt-100-original-pretrained	.023
299	resnet-50_untrained	.022
300	resnet50-SIN	.022
301	mobilenet_v1_0.25_128	.021
302	resnet50_imagenet_10_seed-0	.020
303	convnext_small_imagenet_1_seed-0	.020
304	resnet50-meshes-lt-100-original-scratch	.018
305	barlow-twins-resnet50	.014
306	resnet50-vicregl0p9	.014
307	artResNet18_1	.014
308	resnet50_FractalDB	.011
309	alexnet_training_seed_06	.009
310	alexnet_training_seed_03	.005
311	resnet50_imagenet_1_seed-0	.003
312	resnet50-vicregl0p75	.003
313	alexnet_training_seed_05	.002
314	alexnet_training_seed_01	.002
315	alexnet_training_seed_01_fov4	.002
316	alexnet_training_seed_01_fov12	.002
317	alexnet_training_seed_01_fov16	.002
318	resnet50-barlow	.001
319	resnet-18-LC_w_sh_100_iter_conv_init_m
320	ViT-B/32
321	BiT-M-R50x3
322	BiT-M-R50x1
323	BiT-M-R152x2
324	resnet-18-LC_w_sh_1_iter_conv_init_m
325	resnet-18-LC_w_sh_1_iter_m
326	resnet-18-LC_w_sh_10_iter_m
327	resnet-18_test_m
328	resnet-18-LC_w_sh_100_iter_m
329	resnet-18-LC_w_sh_10_iter_conv_init_m
330	FrankRobWobv0
331	0.5x_resnet-18_LC
332	CORnetZ_CIFAR10
333	resnet18-local_aggregation
334	resnet18-deepcluster
335	r3m_resnet18
336	CORnet-Z
337	vggface
338	my-model
339	resnet18-instance_recognition
340	0.5x_resnet-18_LC_w_sh_10_iter
341	r3m_resnet50
342	r3m_resnet34
343	resnet-18-LC_m
344	r3m_resnet50_nocrop
345	resnet18-supervised
346	resnet-18-LC_1st_conv_m
347	resnet-18-LC_conv_init_m
348	resnet18-contrastive_multiview
349	0.5x_resnet-18
350	resnet18-colorization
351	RN50
352	0.5x_resnet-18_LC_w_sh_100_iter
353	RN50
354	resnet18-relative_position
355	resnet18-autoencoder
356	resnet18-simclr
357	omnivore_swinT
358	ViT_L_32
359	ViT_B_32
360	resnet18-depth_prediction
361	ViT_B_16
362	r3m_resnet34_nocrop
363	resnet18-contrastive_predictive
364	resnet-18-LC_untrained
365	resnet-18_untrained
366	resnet-50x2_untrained
367	dcgan
368	unet_entire
369	omnivore_swinS
370	v1-pyr-nodown
371	CORnetZ_CIFAR10_bs32_20_04
372	pixels
373	dorinet_cornet_z
374	my-model
375	resnet50
376	openclip
377	resnet50-cifar
378	resnet50_pretrained_with_retinal_waves
379	resnet50_ImageNet
380	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
381	yudixie_resnet50_random_0_240908
382	yudixie_resnet50_imagenet1kpret_0_240908
383	yudixie_resnet50_imagenet1kpret_0_240312
384	yudixie_resnet50_object_class_0_240908
385	yudixie_resnet50_category_class_0_240908
386	ConvLSTM
387	yudixie_resnet50_distance_reg_0_240908
388	PredRNN
389	SimVP
390	TAU
391	briaai_rmbg_1_4
392	MIM
393	hmax
394	densenet_201_pytorch
395	pnasnet_large_pytorch
396	ReAlnet01_cornet
397	inception_v3_pytorch
398	yolos_tiny
399	ReAlnet03_cornet
400	yudixie_resnet18_imagenet1kpret_0_240719
401	eBarlow_lmda_02_1000ep
402	ReAlnet02_cornet
403	compact_resnet50_V4
404	vit_base_patch16_dinov3-lvd1689m
405	vit_base_patch14_reg4_dinov2-lvd142m
406	ReAlnet01_cornet_fov16
407	resnet18_ecoset_full
408	resnet34_ecoset_full
409	ReAlnet01_cornet_fov4
410	resnet50_ecoset_full
411	resnet101_ecoset_full
412	compact_resnet50_robust_V4
413	ReAlnet04_cornet
414	resnet152_ecoset_full
415	yudixie_resnet50_distance_translation_0_240908
416	yudixie_resnet18_distance_translation_0_240719
417	yudixie_resnet18_translation_rotation_0_240719
418	yudixie_resnet18_distance_rotation_0_240719
419	compact_resnet50_IT
420	ReAlnet01_cornet_fov12
421	yudixie_resnet18_category_class_0_240719
422	vit_base_patch14_dinov2-lvd142m
423	yudixie_resnet50_distance_rotation_0_240908
424	ReAlnet05_cornet
425	yudixie_resnet50_rotation_reg_0_240908
426	yudixie_resnet18_random_0_240719
427	compact_vgg19_V4
428	yudixie_resnet18_distance_translation_rotation_0_240719
429	yudixie_resnet18_object_class_0_240719
430	aughost_fair_resnet18
431	SeLaVi-AVE
432	yudixie_resnet18_translation_reg_0_240719
433	yudixie_resnet18_distance_reg_0_240719
434	ReAlnet06_cornet
435	yudixie_resnet50_translation_reg_0_240908
436	r3d_18
437	compact_vgg19_IT
438	ReAlnet01_ALL
439	mc3_18
440	ReAlnet07_cornet
441	yudixie_resnet50_translation_rotation_0_240908
442	s3d
443	ReAlnet08_cornet
444	mvit_v1_b
445	ReAlnet02_ALL
446	yudixie_resnet18_rotation_reg_0_240719
447	omnivore_swinB
448	VOneCORnet-S
449	compact_cornets_V4
450	resnet18_imagenet21kP
451	ReAlnet03_ALL
452	ReAlnet09_cornet
453	ReAlnet04_ALL
454	SeLaVi-Kinetics400
455	compact_cornets_IT
456	SeLaVi-VGG-Sound
457	ReAlnet05_ALL
458	r2plus1d_18
459	ReAlnet06_ALL
460	ReAlnet10_cornet
461	SeLaVi-Kinetics-Sound
462	mvit_v2_s
463	yudixie_resnet50_distance_translation_rotation_0_240908
464	ReAlnet07_ALL
465	compact_resnet50_robust_IT
466	ReAlnet08_ALL
467	yudixie_resnet18_cat_obj_class_all_latents_0_240719
468	resnet50_primary_visual_cortex
469	ReAlnet09_ALL
470	yudixie_resnet50_cat_obj_class_all_latents_0_240908
471	ReAlnet10_ALL
472	resnet18_fair
473	pr1_stl10_disentangled_alpha04
474	predictive_coding_pc
475	yudixie_wbh_object_class_scaling_0415_run_0
476	yudixie_wbh_object_class_scaling_0415_run_3
477	yudixie_wbh_object_class_scaling_0415_imagenet
478	yudixie_wbh_object_class_scaling_0415_run_2
479	yudixie_wbh_object_class_scaling_0415_run_1
480	deepeisnn_ei_cifar10_vgg19
481	deepeisnn_ei_cifar10_resnet18
482	deepeisnn_ei_imagenet_resnet18

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