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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021contrast-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnext101_32x16d_wsl	.771
2	effnetv2m_custom384	.731
3	CLIP_resnet50	.718
4	CLIP_resnet50_float32	.718
5	resnet-152_v2-tf	.709
6	CLIP_ViT-B_32	.708
7	SWSL_resnet50	.696
8	nasnet_large-tf	.688
9	resnet50_st_wzc_seed7_2_323	.676
10	ViT_B_16_imagenet1k	.658
11	resnet_50_v2	.647
12	ViT_L_32_imagenet1k	.635
13	effnetb1_272x240	.632
14	CLIP-RN50	.631
15	inception_v4	.623
16	resnext101_32x8d_wsl	.621
17	ViT_L_16_imagenet1k	.617
18	pnasnet_large-tf	.617
19	inception_v4-tf	.606
20	resnet50_ewconplus_wzc_seed5_2__323	.602
21	nasnet_large	.598
22	vision_transformer_vit_large_patch16_224	.590
23	resnet50_ewconplus_wzc_seed2_2__323	.584
24	resnext101_32x48d_wsl	.581
25	seresnext50_32x4d	.580
26	resnext101_32x32d_wsl	.577
27	xception-keras	.574
28	convnext_base_fb_in1k_gram_aligned_dinov3	.570
29	vit_large_patch14_clip_224:laion2b_ft_in1k	.568
30	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.565
31	resnet-50_v2-tf	.563
32	resnet_101_v2	.562
33	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.555
34	pnasnet_large_pytorch	.554
35	SWSL_resnext101_32x8d	.547
36	deit3_base_patch16_224_fb_in22k_ft_in1k	.546
37	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.544
38	pnasnet_large_halfPrecision	.544
39	pnasnet_large	.544
40	regnety_032	.542
41	xception	.540
42	resnet50_st_wzc_seed3_2_323	.537
43	ViT_B_32_imagenet1k	.533
44	resnet50_ewconplus_wzc_seed6_2_323	.513
45	inception_v3-tf	.511
46	cvt_cvt-13-224-in1k_4_LucyV4	.507
47	focalnet_tiny_lrf_in1k	.506
48	convnext_base_fb_in1k	.506
49	convnext_femto_ols:d1_in1k	.503
50	convnext_tiny:in12k_ft_in1k	.503
51	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.499
52	resnet-152_v2_pytorch	.496
53	tv_efficientnet-b1	.492
54	resnet50_ewconplus_wzc	.490
55	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.481
56	convnext_tiny_sup	.478
57	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.476
58	cvt_cvt-21-224-in1k_4_LucyV4	.460
59	convnext_small_imagenet_100_seed-0	.456
60	convnext_small_imagenet_full_seed-0	.452
61	cvt_cvt-21-384-in1k_4_LucyV4	.445
62	convnext_tiny_imagenet_full_seed-0	.433
63	resnet50_st_wzc_2	.432
64	cvt_cvt-13-384-in1k_4_LucyV4	.431
65	resnet50-VITO-8deg-cc	.430
66	vit_relpos_base_patch16_clsgap_224:sw_in1k	.429
67	vit_base_patch16_clip_224:openai_ft_in1k	.418
68	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.416
69	vit_large_patch14_clip_336:laion2b_ft_in1k	.413
70	resnet50_hvs_wzc	.403
71	resnet50-moclr8deg	.403
72	resnet50_moco_v2	.400
73	resnet101	.399
74	BiT-S-R50x3	.397
75	convnext_base_fb_in22k_ft_in1k	.390
76	resnet_152_v2	.376
77	resnet50_simclr_linhead_01norm	.372
78	antialias-resnet152	.370
79	resnet50_byol	.367
80	inception_v3	.351
81	convnext_base:clip_laiona_augreg_ft_in1k_384	.349
82	antialiased-rnext101_32x8d	.347
83	convnext_base_imagenet_full_seed-0	.347
84	resnet50	.345
85	fixres_resnext101_32x48d_wsl	.344
86	resnet152_imagenet_full	.340
87	resnet50_imagenet_full	.335
88	cv_18_dagger_408_pretrained	.332
89	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.329
90	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.328
91	mehrer2020_alexnet_training_seed_01_fov4	.328
92	densenet-169-keras	.324
93	convnext_large_imagenet_full_seed-0	.322
94	densenet-121-keras	.317
95	deit_base_imagenet_full_seed-0	.309
96	antialiased-r50	.308
97	deit_small_imagenet_full_seed-0	.308
98	densenet-201-keras	.302
99	resnet_101_v1	.301
100	BiT-S-R152x4	.294
101	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.290
102	ijepa_vith14_linhead	.290
103	blt_vs	.283
104	resnet34_imagenet_full	.276
105	resnet50_random_l2_perturb	.274
106	resnet50_byol_linhead	.273
107	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.271
108	AlexNet_SIN_fov4	.270
109	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.269
110	inception_v2-tf	.265
111	BiT-S-R101x3	.261
112	resnet50_simclr	.260
113	densenet-169	.254
114	densenet-201	.253
115	densenet_201_pytorch	.253
116	densenet-121	.250
117	resnet_152_v1	.246
118	inception_v1-tf	.242
119	vit_large_patch14_clip_224:openai_ft_in1k	.241
120	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.240
121	nasnet_mobile	.237
122	resnet50_barlowtwins_linhead	.234
123	resnet50-SIN_IN_IN	.229
124	resnet_SIN_IN_FT_IN	.229
125	Res2Net50_26w_4s	.228
126	resnet50_simsiam_linhead	.222
127	resnet-50-pytorch	.221
128	resnet50-sup	.221
129	resnet50_tutorial	.221
130	resnet_50_v1	.221
131	grcnn_109	.220
132	resnet50_vicreg_linhead	.219
133	efficientnet_b0	.219
134	resnet-101_v1-tf	.216
135	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.215
136	deit_large_imagenet_full_seed-0	.206
137	convnext_large:fb_in22k_ft_in1k	.204
138	alexnet_fov4	.204
139	AT_efficientnet-b2	.200
140	AdvProp_efficientnet-b2	.200
141	dinov2_vitl14_lc	.197
142	dinov2_vitl14_reg_lc	.193
143	resnet50-SIN_IN	.193
144	BiT-S-R152x2	.191
145	resnet_50_v1_spiking	.190
146	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.186
147	grcnn	.184
148	resnet-50_v1-tf	.182
149	resnet-152_v1-tf	.182
150	BiT-S-R101x1	.181
151	AdvProp_efficientnet-b6	.179
152	vgg_19	.178
153	dinov2_vitg14_lc	.177
154	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.176
155	mobilenet_v2_0_5_224	.176
156	resnet101_imagenet_full	.171
157	vonegrcnn_52e_full	.171
158	efficientnet-b7	.166
159	efficientnet_b2_imagenet_full	.166
160	mobilenet_v2_1-4_224_pytorch	.166
161	mobilenet_v2_1_4_224	.166
162	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.163
163	BiT-S-R50x1	.158
164	eicircuit_resnet18_bn_20260919	.158
165	nasnet_mobile-tf	.158
166	alexnet_training_seed_02	.156
167	alexnet_training_seed_04	.156
168	alexnet_training_seed_10	.156
169	vgg-16-keras	.155
170	alexnet_random_linf8_perturb	.155
171	AdvProp_efficientnet-b4	.155
172	AT_efficientnet-b4	.155
173	ReAlnet05	.154
174	mobilenet_v2_0.5_224-tf	.152
175	mobilenet_v1_0.25_128	.152
176	vonegrcnn_47e	.151
177	alexnet_random_l2_3_perturb	.148
178	ReAlnet02	.147
179	resnet50-vitoimagevidnet8	.147
180	resnet-18	.147
181	convnext_xlarge:fb_in22k_ft_in1k	.145
182	ReAlnet04	.144
183	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.143
184	mobilenet_v2_1_0_224	.140
185	voneresnet-50-non_stochastic	.140
186	convnext_large_in22k_supervised	.140
187	AdvProp_efficientnet-b7	.139
188	cornet_s	.139
189	ReAlnet08	.135
190	ReAlnet03	.133
191	alexnet_reduced_aliasing_early_checkpoint	.131
192	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.131
193	mehrer2020_alexnet_training_seed_04	.130
194	vonegrcnn_52e_full	.125
195	alexnet_ks_torevert	.123
196	alexnet	.123
197	vit_large_clip336_openai	.122
198	texture_shape_resnet50_trained_on_SIN	.122
199	resnet50_l2_3_robust	.121
200	vgg_16	.121
201	mobilenet_v1_0.25_192	.120
202	vonegrcnn_62e_nobn	.120
203	mobilenet_v2_0.5_128	.119
204	voneresnet-50-robust	.119
205	resnet50_linf_4_robust	.119
206	mobilevit_small	.118
207	alexnet_fov16	.118
208	vit_huge_clip336_laion	.117
209	alexnet_robust_correct	.117
210	resnet50_linf_8_robust	.116
211	dinov2_vitg14_reg_lc	.116
212	alexnet_l2_3_robust	.115
213	vgg-19-keras	.114
214	vonegrcnn_62e_nobn	.113
215	resnet-50-robust	.113
216	imagenet_l2_3_0	.113
217	resnet50_robust_l2_eps3	.113
218	resnet50_robust_l2_eps1	.113
219	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.110
220	alexnet_linf_8_robust	.109
221	convnext_large_clip_laion2b_finelayers	.109
222	imagenet_l2_10_0	.108
223	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.108
224	ReAlnet09	.107
225	mobilenet_v2_1_0_128	.107
226	ReAlnet07	.107
227	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.106
228	resnet50_imagenet_10_seed-0	.106
229	deit_small_imagenet_10_seed-0	.106
230	deit_small_imagenet_1_seed-0	.106
231	mobilenet_v2_0_5_192	.105
232	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.103
233	ReAlnet06	.102
234	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.102
235	vonealexnet_gaussian_noise_std4_fixed	.101
236	alexnet_training_seed_05	.101
237	alexnet_training_seed_01	.101
238	alexnet_training_seed_01_fov4	.101
239	alexnet_training_seed_01_fov12	.101
240	alexnet_training_seed_01_fov16	.101
241	barlow-twins-resnet50	.099
242	ReAlnet10	.097
243	alexnet_fov12	.097
244	vonegrcnn_47e	.096
245	konkle_alexnetgn_ipcl_ref01_primary_model	.094
246	resnet50-vicreg	.094
247	mobilenet_v1_0.5_192	.094
248	mobilenet_v2_1.0_96	.093
249	mobilenet_v2_0.35_128	.091
250	mehrer2020_alexnet_training_seed_03	.089
251	mobilenet_v2_1_0_160	.088
252	mobilenet_v2_0.35_192	.088
253	resnet18_imagenet_full	.087
254	eva02_large_in22k	.086
255	resnet50-SIN	.085
256	mehrer2020_alexnet_training_seed_01	.083
257	mobilenet_v1_0.5_128	.083
258	mobilenet_v1_1.0_224	.081
259	mobilenet_v2_0.35_160	.081
260	squeezenet1_0	.081
261	mobilenet_v2_1.0_128-tf	.080
262	AdvProp_efficientnet-b8	.079
263	resnet50_eMMCR_Vanilla	.079
264	alexnet_early_checkpoint	.075
265	inception_v1	.074
266	dinov2_vitl14_lc_res336	.073
267	resnet50-vicregl0p9	.072
268	mobilenet_v1_0.5_160	.072
269	mobilenet_v2_1_0_192	.071
270	mobilenet_v2_1.0_160-tf	.070
271	resnet50_FractalDB	.070
272	ReAlnet01	.070
273	mobilenet_v2_1.0_224-tf	.070
274	efficientnet_b0_imagenet_full	.069
275	voneresnet-50	.069
276	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.064
277	mehrer2020_alexnet_training_seed_01_fov12	.060
278	alexnet_training_seed_09	.058
279	mehrer2020_alexnet_training_seed_01_fov16	.056
280	mobilenet_v2_1.0_192-tf	.056
281	mehrer2020_alexnet_training_seed_05	.056
282	alexnet_training_seed_07	.054
283	CORnet-S	.052
284	mobilenet_v2_0.5_192-tf	.052
285	mobilenet_v2_1.4_224-tf	.050
286	mobilenet_v1_0.75_160	.050
287	resnet_50_v1_spiking_l4	.049
288	mobilenet_v2_0.5_160	.049
289	resnet50_imagenet_1_seed-0	.048
290	resnet-34	.047
291	mobilenet_v1_1.0_160	.046
292	mobilenet_v1_1.0_192	.045
293	resnet50-vicregl0p75	.044
294	efficientnet_b1_imagenet_full	.044
295	AdvProp_efficientnet-b0	.044
296	mobilenet_v2_0_75_192	.044
297	custom_model_cv_18_dagger_408	.044
298	mobilenet_v2_0.35_224	.043
299	mobilenet_v1_0.5_224	.043
300	resnet_50_v1_spiking_l3	.038
301	resnet50-barlow	.037
302	resnet50_imagenet_100_seed-0	.035
303	resnet_50_v1_spiking_l4a	.033
304	mobilenet_v2_0_75_160	.033
305	mobilenet_v1_0.75_128	.033
306	mobilenet_v2_0.75_128	.032
307	my-model	.030
308	AlexNet_SIN_fov12	.027
309	mobilenet_v2_1_3_224	.025
310	convnext_small_imagenet_10_seed-0	.025
311	mobilenet_v1_0.75_192	.024
312	mobilenet_v2_0_75_224	.024
313	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.024
314	AlexNet_SIN_fov16	.023
315	AlexNet_SIN	.022
316	alexnet_training_seed_03	.022
317	mobilenet_v1_0.25_224	.022
318	deit_small_imagenet_100_seed-0	.021
319	mobilenet_v2_0.75_96	.020
320	squeezenet1_1	.020
321	convnext_small_imagenet_1_seed-0	.020
322	alexnet_training_seed_08	.020
323	mobilenet_v2_1.3_224-tf	.019
324	mobilenet_v2_0.75_160-tf	.018
325	artResNet18_1	.018
326	resnet50_random_linf8_perturb	.017
327	mobilenet_v2_0.5_96	.017
328	mobilenet_v1_1.0_128	.016
329	mobilenet_v1_0.25_160	.016
330	alexnet_training_seed_06	.016
331	texture_shape_alexnet_trained_on_SIN	.015
332	mobilenet_v2_0.35_96	.015
333	mobilenet_v2_0.75_224-tf	.014
334	mobilenet_v2_0.75_192-tf	.013
335	regnet_y_400mf	.013
336	resnet-50_untrained	.012
337	mobilenet_v1_0.75_224	.011
338	resnet50-simclr-vissl	.008
339	shufflenet_v2_x1_0	.006
340	0.5x_resnet-18_LC_w_sh_1_iter	.006
341	mehrer2020_alexnet_training_seed_02	.004
342	resnet-18-LC_w_sh_100_iter_conv_init_m
343	ViT-B/32
344	BiT-M-R50x3
345	BiT-M-R50x1
346	BiT-M-R152x2
347	resnet-18-LC_w_sh_1_iter_conv_init_m
348	resnet-18-LC_w_sh_1_iter_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	FrankRobWobv0
353	resnet18-local_aggregation
354	0.5x_resnet-18_LC
355	CORnetZ_CIFAR10
356	resnet18-deepcluster
357	resnet18-colorization
358	r3m_resnet18
359	CORnet-Z
360	resnet18-instance_recognition
361	my-model
362	vggface
363	0.5x_resnet-18_LC_w_sh_10_iter
364	r3m_resnet50
365	r3m_resnet34
366	resnet-18-LC_m
367	r3m_resnet50_nocrop
368	resnet18-supervised
369	resnet-18-LC_1st_conv_m
370	resnet-18-LC_conv_init_m
371	resnet18-contrastive_multiview
372	0.5x_resnet-18
373	RN50
374	0.5x_resnet-18_LC_w_sh_100_iter
375	RN50
376	resnet18-relative_position
377	resnet18-autoencoder
378	resnet18-simclr
379	ViT_L_32
380	ViT_B_32
381	resnet18-depth_prediction
382	ViT_B_16
383	r3m_resnet34_nocrop
384	hmax
385	resnet18-contrastive_predictive
386	omnivore_swinT
387	resnet-18-LC_untrained
388	resnet-18_untrained
389	resnet-50x2_untrained
390	dcgan
391	v1-pyr-nodown
392	unet_entire
393	CORnetZ_CIFAR10_bs32_20_04
394	pixels
395	dorinet_cornet_z
396	openclip
397	resnet50-cifar
398	resnet50_pretrained_with_retinal_waves
399	resnet50_ImageNet
400	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
401	yudixie_resnet50_random_0_240908
402	yudixie_resnet50_imagenet1kpret_0_240908
403	yudixie_resnet50_cat_obj_class_all_latents_0_240908
404	yudixie_resnet50_object_class_0_240908
405	yudixie_resnet50_category_class_0_240908
406	resnet18_imagenet21kP
407	ConvLSTM
408	PredRNN
409	yudixie_resnet50_distance_reg_0_240908
410	SimVP
411	TAU
412	MIM
413	vit_base_patch14_reg4_dinov2-lvd142m
414	inception_v3_pytorch
415	yolos_tiny
416	yudixie_resnet50_imagenet1kpret_0_240312
417	yudixie_resnet18_translation_reg_0_240719
418	briaai_rmbg_1_4
419	yudixie_resnet18_distance_reg_0_240719
420	ReAlnet03_cornet
421	yudixie_resnet18_rotation_reg_0_240719
422	yudixie_resnet18_imagenet1kpret_0_240719
423	eBarlow_lmda_02_1000ep
424	compact_resnet50_V4
425	ReAlnet02_cornet
426	vit_base_patch16_dinov3-lvd1689m
427	resnet18_ecoset_full
428	resnet34_ecoset_full
429	vit_base_patch14_dinov2-lvd142m
430	VOneCORnet-S
431	resnet50_ecoset_full
432	compact_resnet50_robust_V4
433	resnet101_ecoset_full
434	ReAlnet01_cornet_fov12
435	yudixie_resnet50_distance_translation_0_240908
436	yudixie_resnet18_distance_translation_0_240719
437	ReAlnet04_cornet
438	yudixie_resnet18_translation_rotation_0_240719
439	yudixie_resnet18_category_class_0_240719
440	yudixie_resnet50_distance_rotation_0_240908
441	compact_vgg19_V4
442	compact_resnet50_IT
443	yudixie_resnet50_rotation_reg_0_240908
444	yudixie_resnet18_random_0_240719
445	yudixie_resnet18_cat_obj_class_all_latents_0_240719
446	resnet-18_test_m
447	ReAlnet01_cornet_fov4
448	SeLaVi-AVE
449	yudixie_resnet18_object_class_0_240719
450	yudixie_resnet50_translation_reg_0_240908
451	ReAlnet06_cornet
452	ReAlnet01_cornet_fov16
453	compact_vgg19_IT
454	r3d_18
455	yudixie_resnet50_translation_rotation_0_240908
456	mc3_18
457	ReAlnet01_ALL
458	s3d
459	mvit_v1_b
460	ReAlnet02_ALL
461	ReAlnet08_cornet
462	compact_cornets_V4
463	omnivore_swinB
464	ReAlnet04_ALL
465	SeLaVi-Kinetics400
466	ReAlnet09_cornet
467	SeLaVi-VGG-Sound
468	compact_cornets_IT
469	ReAlnet05_ALL
470	SeLaVi-Kinetics-Sound
471	omnivore_swinS
472	r2plus1d_18
473	mvit_v2_s
474	compact_resnet50_robust_IT
475	ReAlnet10_cornet
476	ReAlnet07_ALL
477	yudixie_resnet18_distance_rotation_0_240719
478	ReAlnet08_ALL
479	yudixie_resnet50_distance_translation_rotation_0_240908
480	yudixie_resnet18_distance_translation_rotation_0_240719
481	ReAlnet09_ALL
482	resnet50_primary_visual_cortex
483	ReAlnet10_ALL
484	ReAlnet03_ALL
485	ReAlnet06_ALL
486	resnet18_fair
487	ReAlnet01_cornet
488	ReAlnet05_cornet
489	ReAlnet07_cornet
490	resnet152_ecoset_full
491	pr1_stl10_disentangled_alpha04
492	predictive_coding_pc
493	yudixie_wbh_object_class_scaling_0415_run_0
494	yudixie_wbh_object_class_scaling_0415_run_3
495	yudixie_wbh_object_class_scaling_0415_imagenet
496	yudixie_wbh_object_class_scaling_0415_run_2
497	yudixie_wbh_object_class_scaling_0415_run_1
498	deepeisnn_ei_cifar10_vgg19
499	deepeisnn_ei_cifar10_resnet18
500	deepeisnn_ei_imagenet_resnet18
501	dinov2_vitl14_reg_lc_featread
502	convnext_xxlarge_clip
503	gabor_filter_entropy_4x4
504	gabor_filter_entropy_4x4_v2
505	gabor_filter_mean_abs_4x4_v2
506	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

0.44.

Note that scores are relative to this ceiling.

Data: Geirhos2021contrast

Metric: error_consistency