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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021falsecolour-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	cvt_cvt-13-384-in1k_4_LucyV4	.818
2	SWSL_resnext101_32x8d	.804
3	nasnet_large	.780
4	resnext101_32x16d_wsl	.757
5	vision_transformer_vit_large_patch16_224	.756
6	resnext101_32x48d_wsl	.755
7	CLIP-RN50	.754
8	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.752
9	SWSL_resnet50	.752
10	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.739
11	inception_v4	.738
12	resnext101_32x32d_wsl	.735
13	cvt_cvt-21-384-in1k_4_LucyV4	.726
14	regnety_032	.713
15	nasnet_large-tf	.708
16	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.706
17	pnasnet_large_halfPrecision	.702
18	pnasnet_large	.702
19	cvt_cvt-13-224-in1k_4_LucyV4	.699
20	CLIP_resnet50	.688
21	CLIP_resnet50_float32	.688
22	convnext_base_fb_in22k_ft_in1k	.682
23	pnasnet_large-tf	.682
24	resnext101_32x8d_wsl	.668
25	deit3_base_patch16_224_fb_in1k	.668
26	effnetb1_272x240	.667
27	vit_relpos_base_patch16_clsgap_224:sw_in1k	.648
28	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.640
29	convnext_femto_ols:d1_in1k	.633
30	convnext_large_imagenet_full_seed-0	.622
31	resnet_50_v2	.622
32	effnetv2m_custom384	.617
33	resnet50_st_wzc_seed7_2_323	.613
34	focalnet_tiny_lrf_in1k	.610
35	fixres_resnext101_32x48d_wsl	.610
36	convnext_base_fb_in1k	.608
37	resnet50_st_wzc_seed3_2_323	.605
38	CLIP_ViT-B_32	.605
39	resnet50_st_wzc_seed6_2_323	.603
40	xception-keras	.599
41	ViT_B_16_imagenet1k	.588
42	vit_base_patch16_clip_224:openai_ft_in1k	.581
43	resnet50-VITO-8deg-cc	.580
44	resnet101	.580
45	convnext_xlarge:fb_in22k_ft_in1k	.579
46	convnext_large:fb_in22k_ft_in1k	.572
47	resnet_101_v2	.568
48	antialias-resnet152	.566
49	resnet-152_v2_pytorch	.564
50	convnext_tiny_imagenet_full_seed-0	.564
51	convnext_tiny:in12k_ft_in1k	.560
52	resnet152_imagenet_full	.559
53	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.559
54	inception_v3	.558
55	resnet50_ewconplus_wzc_seed5_2__323	.555
56	cvt_cvt-21-224-in1k_4_LucyV4	.554
57	inception_v4-tf	.547
58	resnet_152_v1	.546
59	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.542
60	vit_large_patch14_clip_224:laion2b_ft_in1k	.539
61	resnet_152_v2	.537
62	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.536
63	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.532
64	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.532
65	resnet50_imagenet_full	.531
66	resnet101_imagenet_full	.528
67	dinov2_vitl14_lc	.527
68	convnext_base_imagenet_full_seed-0	.520
69	inception_v3-tf	.519
70	tv_efficientnet-b1	.517
71	antialiased-rnext101_32x8d	.511
72	efficientnet_b0	.507
73	inception_v3_pytorch	.505
74	resnet-152_v2-tf	.504
75	resnet50_random_l2_perturb	.497
76	resnet50_moco_v2	.495
77	convnext_large_in22k_supervised	.495
78	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.493
79	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.493
80	cv_18_dagger_408_pretrained	.492
81	resnet50_ewconplus_wzc_seed2_2__323	.492
82	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.487
83	resnet50_ewconplus_wzc_seed6_2_323	.486
84	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.486
85	convnext_small_imagenet_full_seed-0	.483
86	ijepa_vith14_linhead	.475
87	resnet50	.475
88	vgg_19	.471
89	xception	.470
90	grcnn_109	.462
91	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.461
92	deit_large_imagenet_full_seed-0	.453
93	seresnext50_32x4d	.450
94	resnet-50_v2-tf	.449
95	deit_base_imagenet_full_seed-0	.447
96	resnet_101_v1	.440
97	AdvProp_efficientnet-b7	.434
98	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.429
99	resnet50_ewconplus_wzc	.428
100	ViT_L_32_imagenet1k	.419
101	resnet50_st_wzc_2	.418
102	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.416
103	dinov2_vitg14_lc	.414
104	mehrer2020_alexnet_training_seed_01_fov4	.412
105	resnet-152_v1-tf	.409
106	resnet50_byol	.407
107	nasnet_mobile-tf	.401
108	resnet50_barlowtwins_linhead	.394
109	resnet50_byol_linhead	.393
110	resnet50_vicreg_linhead	.392
111	pnasnet_large_pytorch	.392
112	resnet34_imagenet_full	.390
113	alexnet_fov4	.388
114	deit_small_imagenet_full_seed-0	.371
115	ViT_B_32_imagenet1k	.368
116	resnet50-SIN_IN_IN	.367
117	resnet_SIN_IN_FT_IN	.367
118	cornet_s	.364
119	densenet-201-keras	.362
120	resnet-101_v1-tf	.359
121	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.356
122	convnext_large_clip_laion2b_finelayers	.355
123	AdvProp_efficientnet-b4	.353
124	AT_efficientnet-b4	.353
125	Res2Net50_26w_4s	.353
126	resnet_50_v1_spiking	.351
127	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.351
128	resnet50_simclr_linhead_01norm	.350
129	convnext_base_fb_in1k_gram_aligned_dinov3	.349
130	vit_large_patch14_clip_336:laion2b_ft_in1k	.348
131	densenet-121-keras	.346
132	vit_large_clip336_openai	.345
133	dinov2_vitl14_lc_res336	.339
134	AT_efficientnet-b2	.338
135	AdvProp_efficientnet-b2	.338
136	vgg_16	.337
137	vit_large_patch14_clip_224:openai_ft_in1k	.337
138	antialiased-r50	.336
139	AdvProp_efficientnet-b6	.336
140	mobilenet_v2_1.4_224-tf	.336
141	efficientnet-b7	.336
142	densenet-169-keras	.335
143	densenet-201	.333
144	resnet18_imagenet_full	.333
145	resnet50-moclr8deg	.332
146	resnet50_random_linf8_perturb	.326
147	densenet-121	.324
148	resnet50_simsiam_linhead	.322
149	dinov2_vitl14_reg_lc	.316
150	inception_v1	.312
151	resnet50_hvs_wzc	.310
152	resnet50_tutorial	.309
153	resnet_50_v1	.309
154	resnet-50-pytorch	.309
155	resnet50-sup	.309
156	nasnet_mobile	.306
157	BiT-S-R50x3	.300
158	BiT-S-R101x3	.299
159	densenet-169	.299
160	mobilenet_v2_1_3_224	.297
161	inception_v1-tf	.296
162	mobilenet_v2_1.3_224-tf	.295
163	eBarlow_lmda_02_1000ep	.292
164	CORnet-S	.292
165	resnet50-SIN_IN	.291
166	BiT-S-R101x1	.289
167	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.287
168	resnet-34	.282
169	grcnn	.280
170	convnext_xxlarge_clip	.276
171	convnext_tiny_sup	.269
172	eicircuit_resnet18_bn_20260919	.269
173	custom_model_cv_18_dagger_408	.269
174	resnet50_simclr	.268
175	resnet-50_v1-tf	.267
176	resnet50-vitoimagevidnet8	.263
177	inception_v2-tf	.262
178	ReAlnet09	.257
179	ReAlnet01	.257
180	BiT-S-R152x2	.256
181	convnext_base:clip_laiona_augreg_ft_in1k_384	.256
182	convnext_small_imagenet_100_seed-0	.255
183	ReAlnet06	.253
184	vonegrcnn_62e_nobn	.252
185	mobilenet_v2_1_0_224	.251
186	ReAlnet03	.251
187	efficientnet_b2_imagenet_full	.249
188	ReAlnet04	.246
189	efficientnet_b0_imagenet_full	.240
190	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.238
191	BiT-S-R152x4	.237
192	mobilenet_v2_1_0_192	.233
193	voneresnet-50-non_stochastic	.231
194	AdvProp_efficientnet-b8	.230
195	vonegrcnn_47e	.228
196	vonegrcnn_52e_full	.226
197	mobilenet_v2_1.0_224-tf	.225
198	BiT-S-R50x1	.225
199	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.223
200	vonegrcnn_62e_nobn	.221
201	AlexNet_SIN_fov4	.221
202	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.220
203	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.219
204	vit_huge_clip336_laion	.219
205	ReAlnet02	.219
206	resnet50_eMMCR_Vanilla	.218
207	vonegrcnn_47e	.218
208	mobilenet_v2_0_75_224	.216
209	vonegrcnn_52e_full	.215
210	resnet-18	.212
211	ReAlnet07	.212
212	mobilenet_v2_0.75_224-tf	.212
213	ReAlnet10	.209
214	dinov2_vitg14_reg_lc	.202
215	eva02_large_in22k	.197
216	ReAlnet08	.195
217	mobilenet_v2_1-4_224_pytorch	.193
218	mobilenet_v2_1_4_224	.193
219	blt_vs	.188
220	mobilenet_v2_1.0_192-tf	.187
221	ReAlnet05	.183
222	efficientnet_b1_imagenet_full	.181
223	regnet_y_400mf	.179
224	mobilenet_v2_1_0_160	.175
225	mobilenet_v2_0_5_224	.174
226	mobilenet_v1_0.75_224	.164
227	mobilenet_v2_0_75_192	.163
228	mobilenet_v2_0_5_192	.157
229	mobilenet_v2_1.0_160-tf	.157
230	vgg-16-keras	.155
231	voneresnet-50	.152
232	mobilenet_v2_0.5_224-tf	.145
233	resnet_50_v1_spiking_l4a	.144
234	mobilenet_v1_1.0_224	.143
235	mobilenet_v2_0_75_160	.139
236	mobilenet_v1_1.0_192	.137
237	resnet50_linf_4_robust	.136
238	mobilenet_v2_0.5_192-tf	.123
239	texture_shape_resnet50_trained_on_SIN	.119
240	konkle_alexnetgn_ipcl_ref01_primary_model	.116
241	mobilenet_v1_0.75_192	.114
242	resnet50_imagenet_100_seed-0	.113
243	shufflenet_v2_x1_0	.107
244	vgg-19-keras	.107
245	squeezenet1_1	.106
246	mobilenet_v1_0.5_192	.104
247	mobilenet_v1_1.0_160	.103
248	mobilenet_v2_0.75_160-tf	.101
249	mobilenet_v2_0.75_128	.101
250	mobilenet_v2_0.75_192-tf	.100
251	mobilenet_v2_0.35_192	.092
252	resnet50_robust_l2_eps1	.088
253	squeezenet1_0	.087
254	alexnet_random_linf8_perturb	.086
255	AdvProp_efficientnet-b0	.085
256	mobilenet_v1_0.5_224	.073
257	alexnet_early_checkpoint	.073
258	mehrer2020_alexnet_training_seed_03	.071
259	mobilenet_v1_0.5_160	.070
260	mobilenet_v2_0.35_224	.069
261	mobilenet_v2_0.5_128	.068
262	mobilenet_v2_1.0_96	.067
263	mobilenet_v2_0.75_96	.066
264	resnet50_l2_3_robust	.065
265	resnet50_linf_8_robust	.064
266	voneresnet-50-robust	.064
267	resnet_50_v1_spiking_l4	.064
268	mobilenet_v2_0.35_160	.063
269	mehrer2020_alexnet_training_seed_01	.059
270	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.056
271	mobilenet_v2_0.5_160	.055
272	alexnet	.055
273	alexnet_ks_torevert	.055
274	mobilenet_v1_0.75_160	.054
275	mehrer2020_alexnet_training_seed_02	.051
276	mobilenet_v1_0.25_128	.051
277	alexnet_random_l2_3_perturb	.049
278	resnet50-SIN	.048
279	mehrer2020_alexnet_training_seed_05	.046
280	mobilenet_v2_1_0_128	.045
281	vonealexnet_gaussian_noise_std4_fixed	.045
282	mobilenet_v2_1.0_128-tf	.043
283	alexnet_training_seed_05	.043
284	alexnet_training_seed_01	.043
285	alexnet_training_seed_01_fov4	.043
286	alexnet_training_seed_01_fov12	.043
287	alexnet_training_seed_01_fov16	.043
288	convnext_small_imagenet_1_seed-0	.039
289	mehrer2020_alexnet_training_seed_01_fov16	.038
290	mobilenet_v1_0.25_192	.038
291	resnet50-vicregl0p9	.037
292	alexnet_reduced_aliasing_early_checkpoint	.036
293	mobilenet_v1_0.25_160	.035
294	mehrer2020_alexnet_training_seed_04	.035
295	mobilenet_v1_1.0_128	.035
296	resnet-50-robust	.034
297	imagenet_l2_3_0	.034
298	resnet50_robust_l2_eps3	.034
299	alexnet_training_seed_06	.034
300	deit_small_imagenet_100_seed-0	.033
301	mobilenet_v1_0.75_128	.031
302	resnet50_imagenet_10_seed-0	.029
303	alexnet_training_seed_09	.027
304	texture_shape_alexnet_trained_on_SIN	.027
305	AlexNet_SIN	.025
306	alexnet_fov16	.021
307	my-model	.019
308	resnet50-vicregl0p75	.019
309	resnet50_FractalDB	.019
310	AlexNet_SIN_fov16	.018
311	imagenet_l2_10_0	.017
312	alexnet_fov12	.017
313	resnet50-vicreg	.016
314	deit_small_imagenet_10_seed-0	.016
315	deit_small_imagenet_1_seed-0	.016
316	mobilenet_v2_0.5_96	.016
317	resnet50_imagenet_1_seed-0	.015
318	mobilenet_v2_0.35_96	.015
319	mobilenet_v1_0.25_224	.014
320	resnet_50_v1_spiking_l3	.013
321	alexnet_training_seed_07	.013
322	convnext_small_imagenet_10_seed-0	.012
323	mobilenet_v1_0.5_128	.011
324	AlexNet_SIN_fov12	.011
325	mobilenet_v2_0.35_128	.011
326	mehrer2020_alexnet_training_seed_01_fov12	.011
327	alexnet_training_seed_02	.010
328	alexnet_training_seed_04	.010
329	alexnet_training_seed_08	.010
330	alexnet_training_seed_10	.010
331	mobilevit_small	.010
332	alexnet_linf_8_robust	.010
333	alexnet_training_seed_03	.009
334	0.5x_resnet-18_LC_w_sh_1_iter	.009
335	resnet50-barlow	.009
336	barlow-twins-resnet50	.004
337	artResNet18_1	.004
338	alexnet_robust_correct	.003
339	resnet-50_untrained	.003
340	alexnet_l2_3_robust	.003
341	resnet50-simclr-vissl	.001
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_10_iter_m
349	resnet-18-LC_w_sh_1_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	resnet18-instance_recognition
360	my-model
361	vggface
362	0.5x_resnet-18_LC_w_sh_10_iter
363	r3m_resnet50
364	resnet18-colorization
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	resnet18-contrastive_predictive
385	omnivore_swinT
386	resnet-18-LC_untrained
387	resnet-18_untrained
388	resnet-50x2_untrained
389	dcgan
390	v1-pyr-nodown
391	unet_entire
392	CORnetZ_CIFAR10_bs32_20_04
393	pixels
394	dorinet_cornet_z
395	openclip
396	resnet50-cifar
397	resnet50_pretrained_with_retinal_waves
398	resnet50_ImageNet
399	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
400	ReAlnet09_ALL
401	yudixie_resnet50_imagenet1kpret_0_240312
402	yudixie_resnet50_random_0_240908
403	yudixie_resnet50_imagenet1kpret_0_240908
404	yudixie_resnet50_cat_obj_class_all_latents_0_240908
405	yudixie_resnet50_object_class_0_240908
406	yudixie_resnet50_category_class_0_240908
407	resnet18_imagenet21kP
408	ConvLSTM
409	yudixie_resnet50_distance_reg_0_240908
410	PredRNN
411	SimVP
412	TAU
413	MIM
414	densenet_201_pytorch
415	vit_base_patch16_dinov3-lvd1689m
416	ReAlnet01_cornet
417	compact_resnet50_V4
418	yudixie_resnet18_translation_reg_0_240719
419	yudixie_resnet18_distance_reg_0_240719
420	yolos_tiny
421	yudixie_resnet18_rotation_reg_0_240719
422	ReAlnet02_cornet
423	ReAlnet03_cornet
424	vit_base_patch14_dinov2-lvd142m
425	resnet18_ecoset_full
426	resnet34_ecoset_full
427	VOneCORnet-S
428	resnet50_ecoset_full
429	compact_resnet50_IT
430	vit_base_patch14_reg4_dinov2-lvd142m
431	yudixie_resnet50_rotation_reg_0_240908
432	resnet101_ecoset_full
433	compact_resnet50_robust_V4
434	yudixie_resnet50_distance_translation_0_240908
435	ReAlnet01_cornet_fov12
436	yudixie_resnet18_distance_translation_0_240719
437	yudixie_resnet18_translation_rotation_0_240719
438	yudixie_resnet18_distance_rotation_0_240719
439	compact_vgg19_V4
440	yudixie_resnet18_category_class_0_240719
441	resnet-18_test_m
442	yudixie_resnet18_random_0_240719
443	yudixie_resnet18_cat_obj_class_all_latents_0_240719
444	ReAlnet05_cornet
445	yudixie_resnet50_distance_rotation_0_240908
446	SeLaVi-AVE
447	yudixie_resnet18_distance_translation_rotation_0_240719
448	yudixie_resnet18_object_class_0_240719
449	hmax
450	yudixie_resnet50_translation_reg_0_240908
451	compact_vgg19_IT
452	r3d_18
453	yudixie_resnet50_translation_rotation_0_240908
454	ReAlnet01_ALL
455	mc3_18
456	ReAlnet07_cornet
457	s3d
458	mvit_v1_b
459	ReAlnet08_cornet
460	ReAlnet02_ALL
461	ReAlnet03_ALL
462	ReAlnet04_ALL
463	compact_cornets_V4
464	omnivore_swinB
465	SeLaVi-Kinetics400
466	ReAlnet09_cornet
467	SeLaVi-VGG-Sound
468	ReAlnet05_ALL
469	compact_cornets_IT
470	SeLaVi-Kinetics-Sound
471	r2plus1d_18
472	ReAlnet06_ALL
473	omnivore_swinS
474	mvit_v2_s
475	compact_resnet50_robust_IT
476	ReAlnet10_cornet
477	ReAlnet07_ALL
478	ReAlnet08_ALL
479	yudixie_resnet18_imagenet1kpret_0_240719
480	ReAlnet04_cornet
481	ReAlnet06_cornet
482	yudixie_resnet50_distance_translation_rotation_0_240908
483	resnet50_primary_visual_cortex
484	briaai_rmbg_1_4
485	ReAlnet10_ALL
486	ReAlnet01_cornet_fov16
487	ReAlnet01_cornet_fov4
488	resnet152_ecoset_full
489	resnet18_fair
490	pr1_stl10_disentangled_alpha04
491	predictive_coding_pc
492	yudixie_wbh_object_class_scaling_0415_run_0
493	yudixie_wbh_object_class_scaling_0415_run_3
494	yudixie_wbh_object_class_scaling_0415_imagenet
495	yudixie_wbh_object_class_scaling_0415_run_2
496	yudixie_wbh_object_class_scaling_0415_run_1
497	deepeisnn_ei_cifar10_vgg19
498	deepeisnn_ei_cifar10_resnet18
499	deepeisnn_ei_imagenet_resnet18
500	dinov2_vitl14_reg_lc_featread
501	gabor_filter_entropy_4x4
502	gabor_filter_entropy_4x4_v2
503	gabor_filter_entropy_4x4_v2_forcedCosine
504	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

0.44.

Note that scores are relative to this ceiling.

Data: Geirhos2021falsecolour

Metric: error_consistency