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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021colour-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	SWSL_resnext101_32x8d	.891
2	resnext101_32x8d_wsl	.885
3	convnext_femto_ols:d1_in1k	.866
4	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.815
5	pnasnet_large-tf	.812
6	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.811
7	cvt_cvt-13-224-in1k_4_LucyV4	.804
8	pnasnet_large_halfPrecision	.800
9	pnasnet_large	.800
10	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.799
11	vision_transformer_vit_large_patch16_224	.794
12	convnext_base_fb_in22k_ft_in1k	.792
13	effnetb1_272x240	.792
14	effnetv2m_custom384	.788
15	nasnet_large-tf	.788
16	resnext101_32x48d_wsl	.787
17	nasnet_large	.769
18	CLIP-RN50	.769
19	SWSL_resnet50	.766
20	vit_large_patch14_clip_224:laion2b_ft_in1k	.762
21	resnext101_32x32d_wsl	.756
22	resnet50-VITO-8deg-cc	.755
23	CLIP_ViT-B_32	.748
24	convnext_tiny:in12k_ft_in1k	.746
25	CLIP_resnet50_float32	.739
26	CLIP_resnet50	.739
27	resnet_50_v2	.738
28	regnety_032	.737
29	resnet_101_v2	.731
30	cvt_cvt-21-384-in1k_4_LucyV4	.727
31	resnet-152_v2-tf	.721
32	resnet-152_v2_pytorch	.716
33	ViT_L_16_imagenet1k	.715
34	cvt_cvt-21-224-in1k_4_LucyV4	.703
35	resnext101_32x16d_wsl	.696
36	resnet152_imagenet_full	.692
37	resnet_152_v2	.691
38	inception_v3	.689
39	inception_v4	.685
40	efficientnet_b0	.684
41	fixres_resnext101_32x48d_wsl	.675
42	resnet101	.675
43	cvt_cvt-13-384-in1k_4_LucyV4	.670
44	deit3_base_patch16_224_fb_in22k_ft_in1k	.669
45	deit3_base_patch16_224_fb_in1k	.660
46	inception_v3-tf	.657
47	resnet101_imagenet_full	.653
48	focalnet_tiny_lrf_in1k	.647
49	ViT_B_16_imagenet1k	.640
50	tv_efficientnet-b1	.637
51	resnet50_ewconplus_wzc_seed5_2__323	.631
52	resnet50	.631
53	resnet_152_v1	.624
54	xception	.619
55	resnet50_random_l2_perturb	.617
56	ijepa_vith14_linhead	.592
57	inception_v4-tf	.591
58	resnet50_st_wzc_seed3_2_323	.588
59	resnet-50_v2-tf	.587
60	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.587
61	resnet50_imagenet_full	.585
62	antialiased-r50	.574
63	xception-keras	.561
64	vit_relpos_base_patch16_clsgap_224:sw_in1k	.560
65	resnet_101_v1	.551
66	AdvProp_efficientnet-b6	.546
67	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.543
68	vit_base_patch16_clip_224:openai_ft_in1k	.541
69	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.538
70	convnext_tiny_imagenet_full_seed-0	.534
71	antialiased-rnext101_32x8d	.528
72	resnet50_byol	.521
73	AdvProp_efficientnet-b7	.521
74	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.519
75	resnet50_st_wzc_2	.515
76	antialias-resnet152	.512
77	efficientnet-b7	.510
78	resnet50_barlowtwins_linhead	.506
79	mehrer2020_alexnet_training_seed_01_fov4	.506
80	alexnet_fov4	.505
81	vgg_19	.505
82	resnet50_moco_v2	.504
83	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.499
84	Res2Net50_26w_4s	.491
85	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.491
86	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.489
87	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.488
88	densenet-201-keras	.479
89	resnet34_imagenet_full	.478
90	resnet-50-pytorch	.474
91	resnet50-sup	.474
92	resnet50_tutorial	.474
93	resnet_50_v1	.474
94	grcnn_109	.474
95	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.472
96	seresnext50_32x4d	.471
97	convnext_large:fb_in22k_ft_in1k	.470
98	AT_efficientnet-b2	.468
99	AdvProp_efficientnet-b2	.468
100	resnet50_ewconplus_wzc	.466
101	resnet50-SIN_IN_IN	.464
102	resnet_SIN_IN_FT_IN	.464
103	ViT_L_32_imagenet1k	.463
104	convnext_small_imagenet_full_seed-0	.462
105	resnet50-moclr8deg	.461
106	densenet-169	.456
107	deit_small_imagenet_full_seed-0	.454
108	AdvProp_efficientnet-b4	.450
109	AT_efficientnet-b4	.450
110	resnet_50_v1_spiking	.448
111	densenet-169-keras	.448
112	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.448
113	densenet-121-keras	.448
114	cornet_s	.445
115	resnet18_imagenet_full	.443
116	densenet_201_pytorch	.442
117	convnext_xlarge:fb_in22k_ft_in1k	.441
118	grcnn	.439
119	densenet-201	.438
120	resnet-101_v1-tf	.432
121	mobilenet_v2_1_3_224	.430
122	efficientnet_b2_imagenet_full	.429
123	vit_large_patch14_clip_224:openai_ft_in1k	.428
124	resnet50_random_linf8_perturb	.427
125	convnext_base:clip_laiona_augreg_ft_in1k_384	.422
126	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.419
127	convnext_base_fb_in1k	.412
128	deit_large_imagenet_full_seed-0	.411
129	resnet50_byol_linhead	.407
130	convnext_small_imagenet_100_seed-0	.406
131	deit_base_imagenet_full_seed-0	.406
132	densenet-121	.404
133	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.403
134	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.403
135	cv_18_dagger_408_pretrained	.400
136	resnet-50_v1-tf	.395
137	convnext_large_imagenet_full_seed-0	.395
138	dinov2_vitl14_lc	.394
139	BiT-S-R50x3	.391
140	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.390
141	vit_large_patch14_clip_336:laion2b_ft_in1k	.387
142	convnext_base_fb_in1k_gram_aligned_dinov3	.385
143	resnet50_hvs_wzc	.381
144	ReAlnet03	.377
145	resnet-152_v1-tf	.373
146	eicircuit_resnet18_bn_20260919	.372
147	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.370
148	ReAlnet01	.370
149	convnext_base_imagenet_full_seed-0	.365
150	vit_huge_clip336_laion	.364
151	mobilenet_v2_1.4_224-tf	.363
152	voneresnet-50-non_stochastic	.361
153	resnet50_vicreg_linhead	.357
154	BiT-S-R152x2	.356
155	dinov2_vitg14_lc	.353
156	custom_model_cv_18_dagger_408	.346
157	resnet50_simsiam_linhead	.344
158	resnet50-SIN_IN	.344
159	inception_v2-tf	.344
160	mobilenet_v2_1.3_224-tf	.343
161	ReAlnet04	.342
162	resnet50_simclr_linhead_01norm	.341
163	vgg_16	.341
164	ReAlnet08	.328
165	ReAlnet09	.325
166	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.324
167	ReAlnet05	.322
168	efficientnet_b0_imagenet_full	.320
169	ViT_B_32_imagenet1k	.320
170	vit_large_clip336_openai	.319
171	convnext_xxlarge_clip	.319
172	ReAlnet07	.316
173	CORnet-S	.314
174	ReAlnet06	.314
175	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.311
176	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.311
177	nasnet_mobile-tf	.309
178	convnext_large_clip_laion2b_finelayers	.307
179	inception_v1	.300
180	dinov2_vitl14_reg_lc	.300
181	ReAlnet02	.299
182	vonegrcnn_62e_nobn	.298
183	vonegrcnn_62e_nobn	.293
184	efficientnet_b1_imagenet_full	.290
185	ReAlnet10	.290
186	mobilenet_v2_1-4_224_pytorch	.288
187	mobilenet_v2_1_4_224	.288
188	inception_v1-tf	.288
189	nasnet_mobile	.286
190	convnext_large_in22k_supervised	.284
191	vonegrcnn_47e	.284
192	BiT-S-R50x1	.269
193	resnet50_linf_4_robust	.268
194	AdvProp_efficientnet-b8	.263
195	BiT-S-R101x3	.263
196	BiT-S-R152x4	.261
197	resnet-18	.260
198	vonegrcnn_47e	.260
199	AlexNet_SIN_fov4	.260
200	convnext_tiny_sup	.254
201	mobilenet_v2_0_5_224	.253
202	resnet-34	.252
203	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.248
204	regnet_y_400mf	.248
205	mobilenet_v2_1_0_192	.246
206	vonegrcnn_52e_full	.239
207	vonegrcnn_52e_full	.236
208	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.232
209	mobilenet_v2_0_75_224	.231
210	mobilenet_v2_1_0_160	.228
211	voneresnet-50	.218
212	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.216
213	mobilenet_v1_1.0_224	.215
214	blt_vs	.214
215	mobilenet_v2_1_0_224	.214
216	vgg-16-keras	.211
217	mobilenet_v1_0.75_224	.211
218	dinov2_vitl14_lc_res336	.202
219	dinov2_vitg14_reg_lc	.193
220	vgg-19-keras	.188
221	BiT-S-R101x1	.182
222	texture_shape_resnet50_trained_on_SIN	.182
223	voneresnet-50-robust	.180
224	mehrer2020_alexnet_training_seed_01	.180
225	resnet50_eMMCR_Vanilla	.179
226	mobilenet_v2_1.0_160-tf	.177
227	mobilenet_v1_1.0_160	.173
228	resnet50-vitoimagevidnet8	.170
229	mobilenet_v2_1.0_224-tf	.168
230	mobilenet_v2_0_5_192	.165
231	alexnet_random_linf8_perturb	.162
232	mobilenet_v2_1.0_192-tf	.161
233	mehrer2020_alexnet_training_seed_05	.160
234	mobilenet_v2_0.75_224-tf	.159
235	alexnet_random_l2_3_perturb	.152
236	resnet50_robust_l2_eps1	.152
237	mobilenet_v2_0.5_224-tf	.150
238	mobilenet_v2_0_75_192	.150
239	mehrer2020_alexnet_training_seed_03	.147
240	resnet50_l2_3_robust	.146
241	resnet_50_v1_spiking_l4a	.143
242	resnet50_simclr	.143
243	alexnet_reduced_aliasing_early_checkpoint	.137
244	mobilenet_v2_0_75_160	.134
245	alexnet	.134
246	alexnet_ks_torevert	.134
247	konkle_alexnetgn_ipcl_ref01_primary_model	.134
248	mobilenet_v2_0.5_192-tf	.131
249	shufflenet_v2_x1_0	.130
250	mehrer2020_alexnet_training_seed_04	.130
251	mobilenet_v1_0.5_224	.123
252	mobilenet_v2_1_0_128	.122
253	mehrer2020_alexnet_training_seed_02	.121
254	resnet50_imagenet_100_seed-0	.120
255	alexnet_early_checkpoint	.119
256	eva02_large_in22k	.118
257	AdvProp_efficientnet-b0	.115
258	mobilenet_v1_0.75_192	.113
259	resnet50-SIN	.111
260	mobilenet_v2_0.75_160-tf	.108
261	vonealexnet_gaussian_noise_std4_fixed	.104
262	resnet-50-robust	.104
263	imagenet_l2_3_0	.104
264	resnet50_robust_l2_eps3	.104
265	resnet50_linf_8_robust	.104
266	mobilenet_v1_1.0_192	.096
267	mobilenet_v1_0.5_192	.090
268	0.5x_resnet-18_LC_w_sh_1_iter	.084
269	mobilenet_v2_0.75_192-tf	.072
270	mobilenet_v2_0.75_96	.072
271	texture_shape_alexnet_trained_on_SIN	.071
272	mobilenet_v1_0.75_160	.068
273	mobilenet_v1_1.0_128	.068
274	squeezenet1_0	.067
275	AlexNet_SIN	.065
276	mobilenet_v2_0.75_128	.062
277	mobilenet_v2_1.0_128-tf	.061
278	alexnet_linf_8_robust	.060
279	alexnet_l2_3_robust	.060
280	mobilenet_v2_0.35_160	.058
281	alexnet_training_seed_07	.050
282	alexnet_training_seed_02	.049
283	alexnet_training_seed_04	.049
284	alexnet_training_seed_08	.049
285	alexnet_training_seed_10	.049
286	mobilenet_v2_0.35_192	.048
287	squeezenet1_1	.047
288	mehrer2020_alexnet_training_seed_01_fov16	.046
289	mobilenet_v1_0.25_192	.045
290	mobilenet_v1_0.25_224	.044
291	alexnet_robust_correct	.043
292	resnet50-vicreg	.043
293	imagenet_l2_10_0	.041
294	mobilenet_v1_0.75_128	.039
295	mobilenet_v2_0.35_128	.038
296	alexnet_fov12	.038
297	mobilenet_v2_0.5_128	.037
298	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.037
299	mobilenet_v1_0.5_160	.036
300	mobilenet_v2_0.35_96	.036
301	mobilenet_v2_0.35_224	.035
302	deit_small_imagenet_100_seed-0	.035
303	mehrer2020_alexnet_training_seed_01_fov12	.035
304	resnet50-vicregl0p9	.031
305	mobilenet_v1_0.25_128	.030
306	mobilenet_v2_1.0_96	.030
307	convnext_small_imagenet_10_seed-0	.030
308	deit_small_imagenet_10_seed-0	.027
309	resnet50_imagenet_10_seed-0	.027
310	deit_small_imagenet_1_seed-0	.027
311	alexnet_fov16	.026
312	alexnet_training_seed_03	.025
313	mobilenet_v2_0.5_160	.025
314	mobilenet_v2_0.5_96	.025
315	alexnet_training_seed_06	.022
316	AlexNet_SIN_fov12	.020
317	resnet50-barlow	.020
318	mobilenet_v1_0.5_128	.020
319	alexnet_training_seed_05	.020
320	alexnet_training_seed_01	.020
321	alexnet_training_seed_01_fov4	.020
322	alexnet_training_seed_01_fov12	.020
323	alexnet_training_seed_01_fov16	.020
324	resnet_50_v1_spiking_l4	.019
325	artResNet18_1	.015
326	my-model	.014
327	resnet50-vicregl0p75	.014
328	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.012
329	resnet_50_v1_spiking_l3	.012
330	AlexNet_SIN_fov16	.011
331	barlow-twins-resnet50	.009
332	resnet-50_untrained	.009
333	convnext_small_imagenet_1_seed-0	.009
334	alexnet_training_seed_09	.007
335	mobilenet_v1_0.25_160	.006
336	resnet50_FractalDB	.004
337	mobilevit_small	.004
338	resnet50_imagenet_1_seed-0	.003
339	resnet50-simclr-vissl	.002
340	resnet-18-LC_w_sh_100_iter_conv_init_m
341	ViT-B/32
342	BiT-M-R50x3
343	BiT-M-R152x4
344	BiT-M-R50x1
345	BiT-M-R152x2
346	resnet-18-LC_w_sh_1_iter_conv_init_m
347	resnet-18-LC_w_sh_1_iter_m
348	resnet-18-LC_w_sh_10_iter_m
349	resnet-18-LC_w_sh_100_iter_m
350	resnet-18-LC_w_sh_10_iter_conv_init_m
351	FrankRobWobv0
352	resnet18-local_aggregation
353	0.5x_resnet-18_LC
354	CORnetZ_CIFAR10
355	resnet18-colorization
356	resnet18-deepcluster
357	r3m_resnet18
358	resnet18-instance_recognition
359	CORnet-Z
360	my-model
361	vggface
362	0.5x_resnet-18_LC_w_sh_10_iter
363	r3m_resnet50
364	resnet18-relative_position
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-autoencoder
377	resnet18-simclr
378	ViT_L_32
379	ViT_B_32
380	resnet18-depth_prediction
381	ViT_B_16
382	r3m_resnet34_nocrop
383	resnet18-contrastive_predictive
384	omnivore_swinT
385	resnet-18-LC_untrained
386	resnet-18_untrained
387	resnet-50x2_untrained
388	dcgan
389	v1-pyr-nodown
390	unet_entire
391	CORnetZ_CIFAR10_bs32_20_04
392	pixels
393	dorinet_cornet_z
394	openclip
395	resnet50-cifar
396	resnet50_pretrained_with_retinal_waves
397	resnet50_ImageNet
398	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
399	yudixie_resnet50_random_0_240908
400	yudixie_resnet50_imagenet1kpret_0_240908
401	yudixie_resnet50_cat_obj_class_all_latents_0_240908
402	yudixie_resnet50_object_class_0_240908
403	yudixie_resnet50_category_class_0_240908
404	resnet18_imagenet21kP
405	ConvLSTM
406	PredRNN
407	yudixie_resnet50_distance_reg_0_240908
408	SimVP
409	TAU
410	MIM
411	hmax
412	ReAlnet01_cornet
413	pnasnet_large_pytorch
414	inception_v3_pytorch
415	briaai_rmbg_1_4
416	yudixie_resnet50_imagenet1kpret_0_240312
417	yudixie_resnet18_translation_reg_0_240719
418	yudixie_resnet18_rotation_reg_0_240719
419	compact_resnet50_V4
420	yudixie_resnet18_imagenet1kpret_0_240719
421	eBarlow_lmda_02_1000ep
422	resnet18_ecoset_full
423	compact_resnet50_IT
424	vit_base_patch14_reg4_dinov2-lvd142m
425	vit_base_patch14_dinov2-lvd142m
426	resnet50_ecoset_full
427	yudixie_resnet50_distance_rotation_0_240908
428	yudixie_resnet50_rotation_reg_0_240908
429	yudixie_resnet18_distance_translation_0_240719
430	ReAlnet04_cornet
431	yudixie_resnet50_distance_translation_0_240908
432	ReAlnet01_cornet_fov12
433	yudixie_resnet18_translation_rotation_0_240719
434	compact_resnet50_robust_V4
435	compact_vgg19_V4
436	ReAlnet05_cornet
437	yudixie_resnet18_random_0_240719
438	vit_base_patch16_dinov3-lvd1689m
439	yudixie_resnet18_cat_obj_class_all_latents_0_240719
440	resnet-18_test_m
441	SeLaVi-AVE
442	yudixie_resnet18_distance_reg_0_240719
443	r3d_18
444	yudixie_resnet50_translation_reg_0_240908
445	compact_vgg19_IT
446	ReAlnet01_ALL
447	mc3_18
448	yudixie_resnet50_translation_rotation_0_240908
449	s3d
450	ReAlnet01_cornet_fov16
451	mvit_v1_b
452	compact_cornets_V4
453	ReAlnet02_ALL
454	ReAlnet03_ALL
455	VOneCORnet-S
456	ReAlnet04_ALL
457	omnivore_swinB
458	SeLaVi-Kinetics400
459	SeLaVi-VGG-Sound
460	compact_cornets_IT
461	ReAlnet05_ALL
462	SeLaVi-Kinetics-Sound
463	omnivore_swinS
464	ReAlnet06_ALL
465	mvit_v2_s
466	compact_resnet50_robust_IT
467	r2plus1d_18
468	ReAlnet07_ALL
469	yudixie_resnet18_object_class_0_240719
470	yudixie_resnet18_category_class_0_240719
471	ReAlnet08_ALL
472	yudixie_resnet50_distance_translation_rotation_0_240908
473	yudixie_resnet18_distance_translation_rotation_0_240719
474	yudixie_resnet18_distance_rotation_0_240719
475	ReAlnet03_cornet
476	ReAlnet09_ALL
477	ReAlnet10_cornet
478	resnet50_primary_visual_cortex
479	ReAlnet10_ALL
480	yolos_tiny
481	ReAlnet02_cornet
482	ReAlnet01_cornet_fov4
483	ReAlnet06_cornet
484	ReAlnet07_cornet
485	ReAlnet09_cornet
486	ReAlnet08_cornet
487	resnet101_ecoset_full
488	resnet152_ecoset_full
489	resnet34_ecoset_full
490	resnet18_fair
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	gabor_filter_entropy_4x4
503	gabor_filter_entropy_4x4_v2
504	gabor_filter_entropy_4x4_v2_forcedCosine
505	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

0.42.

Note that scores are relative to this ceiling.

Data: Geirhos2021colour

Metric: error_consistency