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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021silhouette-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_huge_clip336_laion	1.0
2	vit_large_patch14_clip_224:openai_ft_in1k	1.0
3	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
4	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
5	convnext_xxlarge_clip	1.0
6	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
7	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
8	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	1.0
9	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
10	eva02_large_in22k	1.0
11	convnext_large_clip_laion2b_finelayers	1.0
12	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
13	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
14	vit_base_patch16_clip_224:openai_ft_in1k	1.0
15	convnext_large:fb_in22k_ft_in1k	1.0
16	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.993
17	resnext101_32x32d_wsl	.990
18	convnext_base:clip_laiona_augreg_ft_in1k_384	.966
19	resnext101_32x8d_wsl	.966
20	convnext_xlarge:fb_in22k_ft_in1k	.959
21	SWSL_resnext101_32x8d	.936
22	vit_large_clip336_openai	.922
23	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.914
24	resnext101_32x48d_wsl	.908
25	CLIP-RN50	.908
26	fixres_resnext101_32x48d_wsl	.904
27	dinov2_vitl14_lc_res336	.901
28	cvt_cvt-13-384-in1k_4_LucyV4	.900
29	convnext_tiny:in12k_ft_in1k	.897
30	dinov2_vitl14_reg_lc	.896
31	SWSL_resnet50	.891
32	vit_relpos_base_patch16_clsgap_224:sw_in1k	.888
33	convnext_base_fb_in22k_ft_in1k	.886
34	resnext101_32x16d_wsl	.883
35	convnext_large_in22k_supervised	.875
36	dinov2_vitg14_lc	.874
37	convnext_tiny_imagenet_full_seed-0	.870
38	deit3_base_patch16_224_fb_in22k_ft_in1k	.860
39	deit3_base_patch16_224_fb_in1k	.859
40	resnet_152_v2	.856
41	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.848
42	CLIP_resnet50	.841
43	CLIP_resnet50_float32	.841
44	CLIP_ViT-B_32	.840
45	resnet_101_v2	.827
46	resnet-152_v2_pytorch	.825
47	focalnet_tiny_lrf_in1k	.822
48	effnetv2m_custom384	.818
49	pnasnet_large_halfPrecision	.817
50	pnasnet_large	.817
51	pnasnet_large-tf	.810
52	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.793
53	seresnext50_32x4d	.785
54	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.781
55	regnety_032	.778
56	resnet_50_v2	.777
57	resnet50	.773
58	convnext_femto_ols:d1_in1k	.767
59	cvt_cvt-21-384-in1k_4_LucyV4	.763
60	convnext_tiny_sup	.763
61	dinov2_vitl14_lc	.754
62	nasnet_large	.750
63	vision_transformer_vit_large_patch16_224	.749
64	dinov2_vitg14_reg_lc	.739
65	resnet50_random_linf8_perturb	.737
66	convnext_large_imagenet_full_seed-0	.728
67	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.728
68	resnet50_st_wzc_seed3_2_323	.725
69	inception_v4	.718
70	nasnet_large-tf	.706
71	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.704
72	resnet50-VITO-8deg-cc	.701
73	resnet50_st_wzc_seed6_2_323	.686
74	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.685
75	resnet101_imagenet_full	.681
76	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.675
77	pnasnet_large_pytorch	.674
78	cvt_cvt-13-224-in1k_4_LucyV4	.668
79	inception_v3-tf	.663
80	convnext_small_imagenet_full_seed-0	.660
81	inception_v4-tf	.658
82	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.658
83	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.648
84	antialiased-rnext101_32x8d	.648
85	resnet-152_v2-tf	.647
86	resnet50_st_wzc_seed7_2_323	.647
87	resnet50_imagenet_full	.646
88	resnet34_imagenet_full	.640
89	resnet101	.628
90	cvt_cvt-21-224-in1k_4_LucyV4	.618
91	antialias-resnet152	.615
92	effnetb1_272x240	.614
93	inception_v3	.610
94	AdvProp_efficientnet-b6	.610
95	convnext_base_imagenet_full_seed-0	.608
96	voneresnet-50-non_stochastic	.602
97	resnet50_ewconplus_wzc_seed5_2__323	.601
98	xception-keras	.601
99	vonegrcnn_62e_nobn	.584
100	convnext_base_fb_in1k	.582
101	grcnn_109	.578
102	mehrer2020_alexnet_training_seed_01_fov4	.576
103	antialiased-r50	.574
104	resnet50_st_wzc_2	.562
105	resnet152_imagenet_full	.560
106	resnet-34	.558
107	vonegrcnn_62e_nobn	.554
108	AT_efficientnet-b2	.553
109	AdvProp_efficientnet-b2	.553
110	resnet_50_v1_spiking	.551
111	resnet_101_v1	.549
112	resnet50_hvs_wzc	.549
113	inception_v3_pytorch	.548
114	resnet50_tutorial	.546
115	resnet_50_v1	.546
116	resnet-50-pytorch	.546
117	resnet50-sup	.546
118	efficientnet_b0	.544
119	resnet50_random_l2_perturb	.535
120	mobilenet_v2_1.4_224-tf	.534
121	densenet-169-keras	.531
122	vonegrcnn_52e_full	.524
123	cv_18_dagger_408_pretrained	.523
124	AdvProp_efficientnet-b4	.521
125	AT_efficientnet-b4	.521
126	inception_v2-tf	.520
127	vonegrcnn_52e_full	.520
128	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.511
129	tv_efficientnet-b1	.510
130	densenet-121-keras	.510
131	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.509
132	vonegrcnn_47e	.500
133	AdvProp_efficientnet-b7	.497
134	resnet-152_v1-tf	.492
135	resnet50-SIN_IN_IN	.492
136	resnet_SIN_IN_FT_IN	.492
137	deit_base_imagenet_full_seed-0	.492
138	resnet-50_v2-tf	.491
139	resnet18_imagenet_full	.491
140	blt_vs	.491
141	grcnn	.482
142	resnet50_ewconplus_wzc	.482
143	vonegrcnn_47e	.482
144	BiT-S-R50x3	.478
145	densenet-169	.474
146	resnet-50_v1-tf	.474
147	convnext_small_imagenet_100_seed-0	.469
148	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.469
149	densenet-121	.468
150	resnet50_byol	.465
151	voneresnet-50	.463
152	alexnet_fov4	.461
153	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.458
154	inception_v1	.451
155	resnet-101_v1-tf	.450
156	efficientnet-b7	.449
157	resnet_152_v1	.445
158	mobilenet_v2_1-4_224_pytorch	.439
159	mobilenet_v2_1_4_224	.439
160	mobilenet_v1_0.75_224	.438
161	mobilenet_v2_1_0_224	.437
162	deit_large_imagenet_full_seed-0	.434
163	AlexNet_SIN_fov4	.428
164	resnet50_linf_4_robust	.421
165	nasnet_mobile	.418
166	ReAlnet03	.417
167	densenet-201-keras	.409
168	resnet50-moclr8deg	.395
169	BiT-S-R50x1	.394
170	custom_model_cv_18_dagger_408	.392
171	Res2Net50_26w_4s	.390
172	resnet50-SIN_IN	.388
173	mobilenet_v2_1.0_192-tf	.384
174	vgg_19	.379
175	densenet-201	.378
176	densenet_201_pytorch	.378
177	resnet50_vicreg_linhead	.376
178	cornet_s	.375
179	ReAlnet07	.373
180	mobilenet_v2_0_5_224	.369
181	ReAlnet04	.369
182	ReAlnet01	.365
183	ReAlnet10	.364
184	inception_v1-tf	.362
185	mobilenet_v2_1.0_224-tf	.360
186	mobilenet_v2_1.3_224-tf	.358
187	texture_shape_resnet50_trained_on_SIN	.358
188	efficientnet_b0_imagenet_full	.357
189	CORnet-S	.353
190	mobilenet_v2_1_0_192	.353
191	vgg_16	.352
192	resnet50_linf_8_robust	.349
193	mobilenet_v2_0.5_224-tf	.336
194	mobilenet_v2_1_3_224	.336
195	deit_small_imagenet_full_seed-0	.335
196	resnet-18	.333
197	BiT-S-R152x2	.332
198	nasnet_mobile-tf	.328
199	eicircuit_resnet18_bn_20260919	.320
200	ReAlnet09	.317
201	mobilenet_v2_0.5_192-tf	.315
202	ReAlnet08	.314
203	texture_shape_alexnet_trained_on_SIN	.310
204	mobilenet_v2_0_75_160	.309
205	ReAlnet02	.304
206	vgg-16-keras	.298
207	resnet50_l2_3_robust	.297
208	mobilenet_v2_1.0_160-tf	.296
209	mobilenet_v2_0_5_192	.296
210	resnet_50_v1_spiking_l4a	.287
211	mobilenet_v2_1_0_160	.287
212	BiT-S-R101x1	.286
213	resnet50_moco_v2	.285
214	ReAlnet05	.280
215	mobilenet_v1_1.0_224	.279
216	mobilenet_v2_0.75_128	.276
217	convnext_base_fb_in1k_gram_aligned_dinov3	.271
218	mobilenet_v1_1.0_160	.270
219	mobilenet_v2_0.75_224-tf	.266
220	AlexNet_SIN	.263
221	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.262
222	alexnet_random_linf8_perturb	.257
223	mobilenet_v2_0_75_224	.256
224	BiT-S-R152x4	.255
225	mobilenet_v2_0.35_160	.252
226	resnet50-vitoimagevidnet8	.252
227	BiT-S-R101x3	.249
228	alexnet_random_l2_3_perturb	.247
229	resnet50-SIN	.245
230	AdvProp_efficientnet-b0	.243
231	mobilenet_v2_1_0_128	.240
232	mobilenet_v2_0.5_160	.236
233	xception	.236
234	resnet50_robust_l2_eps1	.231
235	mobilenet_v2_0.75_192-tf	.231
236	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.228
237	resnet50_byol_linhead	.225
238	ReAlnet06	.220
239	efficientnet_b2_imagenet_full	.214
240	alexnet_l2_3_robust	.214
241	resnet50_barlowtwins_linhead	.213
242	voneresnet-50-robust	.205
243	resnet50_simsiam_linhead	.205
244	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.204
245	mobilenet_v2_0.75_160-tf	.204
246	alexnet_ks_torevert	.203
247	alexnet	.203
248	squeezenet1_1	.194
249	mobilenet_v1_0.5_224	.194
250	mehrer2020_alexnet_training_seed_05	.193
251	mobilenet_v1_0.75_160	.193
252	mobilenet_v2_0_75_192	.192
253	mehrer2020_alexnet_training_seed_01	.187
254	mobilenet_v2_1.0_128-tf	.186
255	resnet50_simclr	.185
256	mobilenet_v2_0.35_192	.185
257	mobilenet_v2_1.0_96	.185
258	mehrer2020_alexnet_training_seed_04	.183
259	mobilenet_v1_1.0_192	.180
260	resnet50_simclr_linhead_01norm	.179
261	efficientnet_b1_imagenet_full	.176
262	konkle_alexnetgn_ipcl_ref01_primary_model	.169
263	eBarlow_lmda_02_1000ep	.167
264	mobilenet_v2_0.75_96	.166
265	mobilenet_v1_0.5_192	.164
266	mobilenet_v1_0.75_128	.163
267	alexnet_linf_8_robust	.161
268	AlexNet_SIN_fov12	.159
269	mobilenet_v1_0.5_160	.154
270	regnet_y_400mf	.150
271	resnet-50-robust	.149
272	imagenet_l2_3_0	.149
273	resnet50_robust_l2_eps3	.149
274	0.5x_resnet-18_LC_w_sh_1_iter	.148
275	AdvProp_efficientnet-b8	.147
276	mobilenet_v1_0.75_192	.146
277	deit_small_imagenet_100_seed-0	.145
278	alexnet_reduced_aliasing_early_checkpoint	.143
279	alexnet_early_checkpoint	.139
280	alexnet_training_seed_05	.139
281	alexnet_training_seed_06	.139
282	alexnet_training_seed_01	.139
283	alexnet_training_seed_01_fov4	.139
284	alexnet_training_seed_01_fov12	.139
285	alexnet_training_seed_01_fov16	.139
286	resnet50-barlow	.139
287	alexnet_robust_correct	.135
288	vonealexnet_gaussian_noise_std4_fixed	.134
289	mobilenet_v2_0.35_128	.129
290	mehrer2020_alexnet_training_seed_03	.129
291	mobilenet_v1_0.5_128	.127
292	ijepa_vith14_linhead	.123
293	mehrer2020_alexnet_training_seed_02	.118
294	alexnet_fov12	.118
295	AlexNet_SIN_fov16	.117
296	mobilenet_v1_0.25_192	.117
297	resnet50_imagenet_100_seed-0	.112
298	artResNet18_1	.109
299	mobilenet_v2_0.35_224	.107
300	mobilenet_v2_0.5_128	.106
301	mobilenet_v2_0.35_96	.102
302	resnet50_imagenet_10_seed-0	.102
303	mobilenet_v1_0.25_160	.098
304	alexnet_training_seed_03	.090
305	resnet50_FractalDB	.089
306	mobilenet_v1_1.0_128	.089
307	convnext_small_imagenet_10_seed-0	.084
308	deit_small_imagenet_10_seed-0	.084
309	deit_small_imagenet_1_seed-0	.084
310	shufflenet_v2_x1_0	.083
311	mobilenet_v1_0.25_128	.082
312	convnext_small_imagenet_1_seed-0	.082
313	vgg-19-keras	.081
314	alexnet_training_seed_02	.077
315	alexnet_training_seed_08	.077
316	alexnet_training_seed_04	.077
317	alexnet_training_seed_10	.077
318	alexnet_training_seed_07	.077
319	imagenet_l2_10_0	.073
320	resnet-50_untrained	.070
321	mehrer2020_alexnet_training_seed_01_fov16	.068
322	mobilenet_v2_0.5_96	.066
323	resnet50-simclr-vissl	.065
324	ViT_B_32_imagenet1k	.056
325	barlow-twins-resnet50	.054
326	squeezenet1_0	.053
327	resnet50_eMMCR_Vanilla	.052
328	ViT_L_32_imagenet1k	.051
329	alexnet_fov16	.050
330	alexnet_training_seed_09	.049
331	resnet50_imagenet_1_seed-0	.046
332	resnet50-vicregl0p75	.043
333	resnet_50_v1_spiking_l4	.042
334	mobilenet_v1_0.25_224	.041
335	resnet50-vicregl0p9	.033
336	mobilevit_small	.023
337	ViT_B_16_imagenet1k	.023
338	resnet50-vicreg	.012
339	mehrer2020_alexnet_training_seed_01_fov12	.006
340	resnet_50_v1_spiking_l3	.004
341	ReAlnet10_ALL
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	0.5x_resnet-18_LC
354	CORnetZ_CIFAR10
355	resnet18-local_aggregation
356	resnet18-deepcluster
357	r3m_resnet18
358	CORnet-Z
359	vggface
360	my-model
361	resnet18-instance_recognition
362	0.5x_resnet-18_LC_w_sh_10_iter
363	r3m_resnet50
364	r3m_resnet34
365	resnet-18-LC_m
366	r3m_resnet50_nocrop
367	resnet18-supervised
368	resnet-18-LC_1st_conv_m
369	resnet-18-LC_conv_init_m
370	resnet18-contrastive_multiview
371	0.5x_resnet-18
372	resnet18-colorization
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	omnivore_swinT
380	ViT_L_32
381	ViT_B_32
382	resnet18-depth_prediction
383	ViT_B_16
384	r3m_resnet34_nocrop
385	resnet18-contrastive_predictive
386	resnet-18-LC_untrained
387	resnet-18_untrained
388	resnet-50x2_untrained
389	dcgan
390	unet_entire
391	omnivore_swinS
392	v1-pyr-nodown
393	CORnetZ_CIFAR10_bs32_20_04
394	pixels
395	dorinet_cornet_z
396	my-model
397	openclip
398	resnet50-cifar
399	resnet50_pretrained_with_retinal_waves
400	resnet50_ImageNet
401	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
402	yudixie_resnet50_random_0_240908
403	yudixie_resnet50_imagenet1kpret_0_240312
404	yudixie_resnet50_imagenet1kpret_0_240908
405	yudixie_resnet50_cat_obj_class_all_latents_0_240908
406	yudixie_resnet50_object_class_0_240908
407	yudixie_resnet50_category_class_0_240908
408	resnet18_imagenet21kP
409	ConvLSTM
410	yudixie_resnet50_distance_reg_0_240908
411	PredRNN
412	SimVP
413	TAU
414	MIM
415	hmax
416	briaai_rmbg_1_4
417	yolos_tiny
418	vit_base_patch14_reg4_dinov2-lvd142m
419	ReAlnet01_cornet
420	yudixie_resnet18_translation_reg_0_240719
421	compact_resnet50_V4
422	ReAlnet02_cornet
423	yudixie_resnet18_distance_reg_0_240719
424	yudixie_resnet18_imagenet1kpret_0_240719
425	vit_base_patch16_dinov3-lvd1689m
426	resnet18_ecoset_full
427	ReAlnet01_cornet_fov4
428	resnet50_ecoset_full
429	compact_resnet50_IT
430	compact_resnet50_robust_V4
431	yudixie_resnet50_rotation_reg_0_240908
432	yudixie_resnet50_distance_translation_0_240908
433	yudixie_resnet18_distance_translation_0_240719
434	ReAlnet04_cornet
435	yudixie_resnet18_distance_rotation_0_240719
436	yudixie_resnet18_category_class_0_240719
437	yudixie_resnet50_distance_rotation_0_240908
438	compact_vgg19_V4
439	vit_base_patch14_dinov2-lvd142m
440	resnet-18_test_m
441	yudixie_resnet18_random_0_240719
442	SeLaVi-AVE
443	r3d_18
444	ReAlnet01_cornet_fov16
445	compact_vgg19_IT
446	yudixie_resnet50_translation_reg_0_240908
447	yudixie_resnet50_translation_rotation_0_240908
448	ReAlnet01_ALL
449	mc3_18
450	ReAlnet07_cornet
451	s3d
452	mvit_v1_b
453	yudixie_resnet18_rotation_reg_0_240719
454	ReAlnet02_ALL
455	ReAlnet03_ALL
456	omnivore_swinB
457	compact_cornets_V4
458	ReAlnet04_ALL
459	SeLaVi-Kinetics400
460	compact_cornets_IT
461	SeLaVi-VGG-Sound
462	ReAlnet05_ALL
463	resnet152_ecoset_full
464	ReAlnet06_ALL
465	r2plus1d_18
466	mvit_v2_s
467	SeLaVi-Kinetics-Sound
468	compact_resnet50_robust_IT
469	ReAlnet10_cornet
470	resnet101_ecoset_full
471	ReAlnet07_ALL
472	yudixie_resnet18_object_class_0_240719
473	yudixie_resnet18_cat_obj_class_all_latents_0_240719
474	yudixie_resnet50_distance_translation_rotation_0_240908
475	yudixie_resnet18_distance_translation_rotation_0_240719
476	yudixie_resnet18_translation_rotation_0_240719
477	ReAlnet05_cornet
478	ReAlnet09_ALL
479	resnet50_primary_visual_cortex
480	ReAlnet08_ALL
481	resnet18_fair
482	ReAlnet01_cornet_fov12
483	ReAlnet06_cornet
484	ReAlnet03_cornet
485	ReAlnet09_cornet
486	VOneCORnet-S
487	ReAlnet08_cornet
488	resnet34_ecoset_full
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_mean_abs_4x4_v2
502	gabor_filter_entropy_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

0.48.

Note that scores are relative to this ceiling.

Data: Geirhos2021silhouette

Metric: error_consistency