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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	inception_v4-tf	.591
57	resnet50_st_wzc_seed3_2_323	.588
58	resnet-50_v2-tf	.587
59	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.587
60	resnet50_imagenet_full	.585
61	antialiased-r50	.574
62	xception-keras	.561
63	vit_relpos_base_patch16_clsgap_224:sw_in1k	.560
64	resnet_101_v1	.551
65	AdvProp_efficientnet-b6	.546
66	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.543
67	vit_base_patch16_clip_224:openai_ft_in1k	.541
68	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.538
69	convnext_tiny_imagenet_full_seed-0	.534
70	antialiased-rnext101_32x8d	.528
71	resnet50_byol	.521
72	AdvProp_efficientnet-b7	.521
73	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.519
74	resnet50_st_wzc_2	.515
75	antialias-resnet152	.512
76	efficientnet-b7	.510
77	alexnet_fov4	.505
78	vgg_19	.505
79	resnet50_moco_v2	.504
80	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.499
81	Res2Net50_26w_4s	.491
82	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.491
83	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.489
84	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.488
85	densenet-201-keras	.479
86	resnet34_imagenet_full	.478
87	resnet-50-pytorch	.474
88	resnet50-sup	.474
89	resnet50_tutorial	.474
90	resnet_50_v1	.474
91	grcnn_109	.474
92	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.472
93	seresnext50_32x4d	.471
94	convnext_large:fb_in22k_ft_in1k	.470
95	AT_efficientnet-b2	.468
96	AdvProp_efficientnet-b2	.468
97	resnet50_ewconplus_wzc	.466
98	resnet50-SIN_IN_IN	.464
99	resnet_SIN_IN_FT_IN	.464
100	ViT_L_32_imagenet1k	.463
101	convnext_small_imagenet_full_seed-0	.462
102	resnet50-moclr8deg	.461
103	densenet-169	.456
104	deit_small_imagenet_full_seed-0	.454
105	AdvProp_efficientnet-b4	.450
106	AT_efficientnet-b4	.450
107	resnet_50_v1_spiking	.448
108	densenet-169-keras	.448
109	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.448
110	densenet-121-keras	.448
111	cornet_s	.445
112	resnet18_imagenet_full	.443
113	densenet_201_pytorch	.442
114	convnext_xlarge:fb_in22k_ft_in1k	.441
115	grcnn	.439
116	densenet-201	.438
117	resnet-101_v1-tf	.432
118	mobilenet_v2_1_3_224	.430
119	efficientnet_b2_imagenet_full	.429
120	vit_large_patch14_clip_224:openai_ft_in1k	.428
121	resnet50_random_linf8_perturb	.427
122	convnext_base:clip_laiona_augreg_ft_in1k_384	.422
123	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.419
124	convnext_base_fb_in1k	.412
125	deit_large_imagenet_full_seed-0	.411
126	convnext_small_imagenet_100_seed-0	.406
127	deit_base_imagenet_full_seed-0	.406
128	densenet-121	.404
129	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.403
130	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.403
131	cv_18_dagger_408_pretrained	.400
132	resnet-50_v1-tf	.395
133	convnext_large_imagenet_full_seed-0	.395
134	dinov2_vitl14_lc	.394
135	BiT-S-R50x3	.391
136	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.390
137	vit_large_patch14_clip_336:laion2b_ft_in1k	.387
138	convnext_base_fb_in1k_gram_aligned_dinov3	.385
139	resnet50_hvs_wzc	.381
140	ReAlnet03	.377
141	resnet-152_v1-tf	.373
142	eicircuit_resnet18_bn_20260919	.372
143	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.370
144	ReAlnet01	.370
145	convnext_base_imagenet_full_seed-0	.365
146	vit_huge_clip336_laion	.364
147	mobilenet_v2_1.4_224-tf	.363
148	voneresnet-50-non_stochastic	.361
149	BiT-S-R152x2	.356
150	dinov2_vitg14_lc	.353
151	custom_model_cv_18_dagger_408	.346
152	resnet50-SIN_IN	.344
153	inception_v2-tf	.344
154	mobilenet_v2_1.3_224-tf	.343
155	ReAlnet04	.342
156	vgg_16	.341
157	ReAlnet08	.328
158	ReAlnet09	.325
159	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.324
160	ReAlnet05	.322
161	efficientnet_b0_imagenet_full	.320
162	ViT_B_32_imagenet1k	.320
163	vit_large_clip336_openai	.319
164	convnext_xxlarge_clip	.319
165	ReAlnet07	.316
166	CORnet-S	.314
167	ReAlnet06	.314
168	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.311
169	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.311
170	nasnet_mobile-tf	.309
171	convnext_large_clip_laion2b_finelayers	.307
172	inception_v1	.300
173	dinov2_vitl14_reg_lc	.300
174	ReAlnet02	.299
175	vonegrcnn_62e_nobn	.298
176	vonegrcnn_62e_nobn	.293
177	efficientnet_b1_imagenet_full	.290
178	ReAlnet10	.290
179	mobilenet_v2_1-4_224_pytorch	.288
180	mobilenet_v2_1_4_224	.288
181	inception_v1-tf	.288
182	nasnet_mobile	.286
183	convnext_large_in22k_supervised	.284
184	vonegrcnn_47e	.284
185	BiT-S-R50x1	.269
186	resnet50_linf_4_robust	.268
187	AdvProp_efficientnet-b8	.263
188	BiT-S-R101x3	.263
189	BiT-S-R152x4	.261
190	resnet-18	.260
191	vonegrcnn_47e	.260
192	AlexNet_SIN_fov4	.260
193	convnext_tiny_sup	.254
194	mobilenet_v2_0_5_224	.253
195	resnet-34	.252
196	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.248
197	regnet_y_400mf	.248
198	mobilenet_v2_1_0_192	.246
199	vonegrcnn_52e_full	.239
200	vonegrcnn_52e_full	.236
201	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.232
202	mobilenet_v2_0_75_224	.231
203	mobilenet_v2_1_0_160	.228
204	voneresnet-50	.218
205	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.216
206	mobilenet_v1_1.0_224	.215
207	blt_vs	.214
208	mobilenet_v2_1_0_224	.214
209	vgg-16-keras	.211
210	mobilenet_v1_0.75_224	.211
211	dinov2_vitl14_lc_res336	.202
212	dinov2_vitg14_reg_lc	.193
213	vgg-19-keras	.188
214	BiT-S-R101x1	.182
215	texture_shape_resnet50_trained_on_SIN	.182
216	voneresnet-50-robust	.180
217	resnet50_eMMCR_Vanilla	.179
218	mobilenet_v2_1.0_160-tf	.177
219	mobilenet_v1_1.0_160	.173
220	resnet50-vitoimagevidnet8	.170
221	mobilenet_v2_1.0_224-tf	.168
222	mobilenet_v2_0_5_192	.165
223	alexnet_random_linf8_perturb	.162
224	mobilenet_v2_1.0_192-tf	.161
225	mobilenet_v2_0.75_224-tf	.159
226	alexnet_random_l2_3_perturb	.152
227	resnet50_robust_l2_eps1	.152
228	mobilenet_v2_0.5_224-tf	.150
229	mobilenet_v2_0_75_192	.150
230	resnet50_l2_3_robust	.146
231	resnet_50_v1_spiking_l4a	.143
232	resnet50_simclr	.143
233	alexnet_reduced_aliasing_early_checkpoint	.137
234	mobilenet_v2_0_75_160	.134
235	alexnet	.134
236	alexnet_ks_torevert	.134
237	konkle_alexnetgn_ipcl_ref01_primary_model	.134
238	mobilenet_v2_0.5_192-tf	.131
239	shufflenet_v2_x1_0	.130
240	mobilenet_v1_0.5_224	.123
241	mobilenet_v2_1_0_128	.122
242	resnet50_imagenet_100_seed-0	.120
243	alexnet_early_checkpoint	.119
244	eva02_large_in22k	.118
245	AdvProp_efficientnet-b0	.115
246	mobilenet_v1_0.75_192	.113
247	resnet50-SIN	.111
248	mobilenet_v2_0.75_160-tf	.108
249	vonealexnet_gaussian_noise_std4_fixed	.104
250	resnet-50-robust	.104
251	imagenet_l2_3_0	.104
252	resnet50_robust_l2_eps3	.104
253	resnet50_linf_8_robust	.104
254	mobilenet_v1_1.0_192	.096
255	mobilenet_v1_0.5_192	.090
256	0.5x_resnet-18_LC_w_sh_1_iter	.084
257	mobilenet_v2_0.75_192-tf	.072
258	mobilenet_v2_0.75_96	.072
259	texture_shape_alexnet_trained_on_SIN	.071
260	mobilenet_v1_0.75_160	.068
261	mobilenet_v1_1.0_128	.068
262	squeezenet1_0	.067
263	AlexNet_SIN	.065
264	mobilenet_v2_0.75_128	.062
265	mobilenet_v2_1.0_128-tf	.061
266	alexnet_linf_8_robust	.060
267	alexnet_l2_3_robust	.060
268	mobilenet_v2_0.35_160	.058
269	alexnet_training_seed_07	.050
270	alexnet_training_seed_02	.049
271	alexnet_training_seed_04	.049
272	alexnet_training_seed_08	.049
273	alexnet_training_seed_10	.049
274	mobilenet_v2_0.35_192	.048
275	squeezenet1_1	.047
276	mobilenet_v1_0.25_192	.045
277	mobilenet_v1_0.25_224	.044
278	alexnet_robust_correct	.043
279	resnet50-vicreg	.043
280	imagenet_l2_10_0	.041
281	mobilenet_v1_0.75_128	.039
282	mobilenet_v2_0.35_128	.038
283	alexnet_fov12	.038
284	mobilenet_v2_0.5_128	.037
285	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.037
286	mobilenet_v1_0.5_160	.036
287	mobilenet_v2_0.35_96	.036
288	mobilenet_v2_0.35_224	.035
289	deit_small_imagenet_100_seed-0	.035
290	resnet50-vicregl0p9	.031
291	mobilenet_v1_0.25_128	.030
292	mobilenet_v2_1.0_96	.030
293	convnext_small_imagenet_10_seed-0	.030
294	deit_small_imagenet_10_seed-0	.027
295	resnet50_imagenet_10_seed-0	.027
296	deit_small_imagenet_1_seed-0	.027
297	alexnet_fov16	.026
298	alexnet_training_seed_03	.025
299	mobilenet_v2_0.5_160	.025
300	mobilenet_v2_0.5_96	.025
301	alexnet_training_seed_06	.022
302	AlexNet_SIN_fov12	.020
303	resnet50-barlow	.020
304	mobilenet_v1_0.5_128	.020
305	alexnet_training_seed_05	.020
306	alexnet_training_seed_01	.020
307	alexnet_training_seed_01_fov4	.020
308	alexnet_training_seed_01_fov12	.020
309	alexnet_training_seed_01_fov16	.020
310	resnet_50_v1_spiking_l4	.019
311	artResNet18_1	.015
312	my-model	.014
313	resnet50-vicregl0p75	.014
314	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.012
315	resnet_50_v1_spiking_l3	.012
316	AlexNet_SIN_fov16	.011
317	barlow-twins-resnet50	.009
318	resnet-50_untrained	.009
319	convnext_small_imagenet_1_seed-0	.009
320	alexnet_training_seed_09	.007
321	mobilenet_v1_0.25_160	.006
322	resnet50_FractalDB	.004
323	mobilevit_small	.004
324	resnet50_imagenet_1_seed-0	.003
325	resnet50-simclr-vissl	.002
326	resnet-18-LC_w_sh_100_iter_conv_init_m
327	ViT-B/32
328	BiT-M-R50x3
329	BiT-M-R152x4
330	BiT-M-R50x1
331	BiT-M-R152x2
332	resnet-18-LC_w_sh_1_iter_conv_init_m
333	resnet-18-LC_w_sh_1_iter_m
334	resnet-18-LC_w_sh_10_iter_m
335	resnet-18-LC_w_sh_100_iter_m
336	resnet-18-LC_w_sh_10_iter_conv_init_m
337	FrankRobWobv0
338	resnet18-local_aggregation
339	0.5x_resnet-18_LC
340	CORnetZ_CIFAR10
341	resnet18-colorization
342	resnet18-deepcluster
343	r3m_resnet18
344	resnet18-instance_recognition
345	CORnet-Z
346	my-model
347	vggface
348	0.5x_resnet-18_LC_w_sh_10_iter
349	r3m_resnet50
350	resnet18-relative_position
351	r3m_resnet34
352	resnet-18-LC_m
353	r3m_resnet50_nocrop
354	resnet18-supervised
355	resnet-18-LC_1st_conv_m
356	resnet-18-LC_conv_init_m
357	resnet18-contrastive_multiview
358	0.5x_resnet-18
359	RN50
360	0.5x_resnet-18_LC_w_sh_100_iter
361	RN50
362	resnet18-autoencoder
363	resnet18-simclr
364	ViT_L_32
365	ViT_B_32
366	resnet18-depth_prediction
367	ViT_B_16
368	r3m_resnet34_nocrop
369	resnet18-contrastive_predictive
370	omnivore_swinT
371	resnet-18-LC_untrained
372	resnet-18_untrained
373	resnet-50x2_untrained
374	dcgan
375	v1-pyr-nodown
376	unet_entire
377	CORnetZ_CIFAR10_bs32_20_04
378	pixels
379	dorinet_cornet_z
380	openclip
381	resnet50-cifar
382	resnet50_pretrained_with_retinal_waves
383	resnet50_ImageNet
384	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
385	yudixie_resnet50_random_0_240908
386	yudixie_resnet50_imagenet1kpret_0_240908
387	yudixie_resnet50_cat_obj_class_all_latents_0_240908
388	yudixie_resnet50_object_class_0_240908
389	yudixie_resnet50_category_class_0_240908
390	resnet18_imagenet21kP
391	ConvLSTM
392	PredRNN
393	yudixie_resnet50_distance_reg_0_240908
394	SimVP
395	TAU
396	MIM
397	hmax
398	ReAlnet01_cornet
399	pnasnet_large_pytorch
400	inception_v3_pytorch
401	briaai_rmbg_1_4
402	yudixie_resnet50_imagenet1kpret_0_240312
403	yudixie_resnet18_translation_reg_0_240719
404	yudixie_resnet18_rotation_reg_0_240719
405	compact_resnet50_V4
406	yudixie_resnet18_imagenet1kpret_0_240719
407	ReAlnet02_cornet
408	eBarlow_lmda_02_1000ep
409	resnet18_ecoset_full
410	compact_resnet50_IT
411	ReAlnet01_cornet_fov4
412	vit_base_patch14_reg4_dinov2-lvd142m
413	vit_base_patch14_dinov2-lvd142m
414	resnet50_ecoset_full
415	resnet101_ecoset_full
416	yudixie_resnet50_distance_rotation_0_240908
417	yudixie_resnet50_rotation_reg_0_240908
418	resnet152_ecoset_full
419	yudixie_resnet18_distance_translation_0_240719
420	ReAlnet04_cornet
421	yudixie_resnet50_distance_translation_0_240908
422	ReAlnet01_cornet_fov12
423	yudixie_resnet18_translation_rotation_0_240719
424	compact_resnet50_robust_V4
425	compact_vgg19_V4
426	ReAlnet05_cornet
427	yudixie_resnet18_random_0_240719
428	vit_base_patch16_dinov3-lvd1689m
429	yudixie_resnet18_cat_obj_class_all_latents_0_240719
430	resnet-18_test_m
431	SeLaVi-AVE
432	yudixie_resnet18_distance_reg_0_240719
433	r3d_18
434	ReAlnet06_cornet
435	yudixie_resnet50_translation_reg_0_240908
436	compact_vgg19_IT
437	ReAlnet01_ALL
438	mc3_18
439	ReAlnet07_cornet
440	yudixie_resnet50_translation_rotation_0_240908
441	s3d
442	ReAlnet01_cornet_fov16
443	mvit_v1_b
444	ReAlnet08_cornet
445	compact_cornets_V4
446	ReAlnet02_ALL
447	ReAlnet03_ALL
448	VOneCORnet-S
449	ReAlnet04_ALL
450	omnivore_swinB
451	SeLaVi-Kinetics400
452	ReAlnet09_cornet
453	SeLaVi-VGG-Sound
454	compact_cornets_IT
455	ReAlnet05_ALL
456	SeLaVi-Kinetics-Sound
457	omnivore_swinS
458	ReAlnet06_ALL
459	mvit_v2_s
460	compact_resnet50_robust_IT
461	r2plus1d_18
462	ReAlnet07_ALL
463	resnet34_ecoset_full
464	yudixie_resnet18_object_class_0_240719
465	yudixie_resnet18_category_class_0_240719
466	ReAlnet08_ALL
467	yudixie_resnet50_distance_translation_rotation_0_240908
468	yudixie_resnet18_distance_translation_rotation_0_240719
469	yudixie_resnet18_distance_rotation_0_240719
470	ReAlnet03_cornet
471	ReAlnet09_ALL
472	ReAlnet10_cornet
473	resnet50_primary_visual_cortex
474	ReAlnet10_ALL
475	yolos_tiny
476	resnet18_fair
477	pr1_stl10_disentangled_alpha04
478	predictive_coding_pc
479	yudixie_wbh_object_class_scaling_0415_run_0
480	yudixie_wbh_object_class_scaling_0415_run_3
481	yudixie_wbh_object_class_scaling_0415_imagenet
482	yudixie_wbh_object_class_scaling_0415_run_2
483	yudixie_wbh_object_class_scaling_0415_run_1
484	deepeisnn_ei_cifar10_vgg19
485	deepeisnn_ei_cifar10_resnet18
486	deepeisnn_ei_imagenet_resnet18
487	dinov2_vitl14_reg_lc_featread
488	gabor_filter_entropy_4x4
489	gabor_filter_entropy_4x4_v2
490	gabor_filter_entropy_4x4_v2_forcedCosine
491	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