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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021uniformnoise-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.781
2	resnext101_32x32d_wsl	.754
3	resnext101_32x48d_wsl	.743
4	vit_base_patch16_clip_224:openai_ft_in1k	.734
5	resnext101_32x16d_wsl	.731
6	deit3_base_patch16_224_fb_in1k	.730
7	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.728
8	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.723
9	fixres_resnext101_32x48d_wsl	.720
10	vit_large_patch14_clip_224:laion2b_ft_in1k	.719
11	convnext_large:fb_in22k_ft_in1k	.686
12	vision_transformer_vit_large_patch16_224	.685
13	SWSL_resnext101_32x8d	.675
14	resnet-152_v2_pytorch	.674
15	dinov2_vitl14_lc	.672
16	resnet_152_v2	.670
17	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.661
18	convnext_base_fb_in22k_ft_in1k	.652
19	resnet_101_v2	.647
20	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.647
21	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.645
22	vit_large_patch14_clip_224:openai_ft_in1k	.639
23	resnext101_32x8d_wsl	.637
24	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.635
25	dinov2_vitg14_lc	.630
26	CLIP_resnet50	.627
27	CLIP_resnet50_float32	.627
28	convnext_large_clip_laion2b_finelayers	.626
29	convnext_large_in22k_supervised	.619
30	convnext_femto_ols:d1_in1k	.617
31	dinov2_vitl14_reg_lc	.616
32	cvt_cvt-13-384-in1k_4_LucyV4	.614
33	vit_large_patch14_clip_336:laion2b_ft_in1k	.604
34	convnext_xlarge:fb_in22k_ft_in1k	.601
35	focalnet_tiny_lrf_in1k	.601
36	SWSL_resnet50	.599
37	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.591
38	convnext_tiny:in12k_ft_in1k	.590
39	cvt_cvt-13-224-in1k_4_LucyV4	.587
40	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.583
41	vit_large_clip336_openai	.580
42	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.577
43	convnext_base:clip_laiona_augreg_ft_in1k_384	.576
44	vit_relpos_base_patch16_clsgap_224:sw_in1k	.576
45	CLIP_ViT-B_32	.572
46	nasnet_large	.555
47	convnext_base_fb_in1k	.537
48	CLIP-RN50	.537
49	ViT_L_32_imagenet1k	.524
50	convnext_tiny_imagenet_full_seed-0	.522
51	vit_huge_clip336_laion	.521
52	convnext_base_imagenet_full_seed-0	.520
53	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.520
54	cvt_cvt-21-384-in1k_4_LucyV4	.515
55	dinov2_vitg14_reg_lc	.513
56	convnext_small_imagenet_full_seed-0	.509
57	pnasnet_large_halfPrecision	.499
58	cvt_cvt-21-224-in1k_4_LucyV4	.493
59	pnasnet_large	.493
60	eva02_large_in22k	.481
61	ViT_B_16_imagenet1k	.476
62	effnetv2m_custom384	.475
63	pnasnet_large-tf	.473
64	dinov2_vitl14_lc_res336	.472
65	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.462
66	regnety_032	.462
67	resnet_50_v2	.458
68	ViT_B_32_imagenet1k	.455
69	convnext_xxlarge_clip	.447
70	convnext_large_imagenet_full_seed-0	.443
71	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.441
72	seresnext50_32x4d	.439
73	nasnet_large-tf	.418
74	deit3_base_patch16_224_fb_in22k_ft_in1k	.410
75	inception_v4	.404
76	AdvProp_efficientnet-b6	.401
77	resnet50_st_wzc_seed7_2_323	.388
78	resnet-152_v2-tf	.386
79	resnet50-VITO-8deg-cc	.381
80	inception_v3	.377
81	resnet50_ewconplus_wzc_seed5_2__323	.356
82	cv_18_dagger_408_pretrained	.354
83	convnext_base_fb_in1k_gram_aligned_dinov3	.354
84	resnet50_ewconplus_wzc_seed2_2__323	.350
85	inception_v3-tf	.348
86	xception-keras	.344
87	resnet101	.340
88	tv_efficientnet-b1	.338
89	inception_v4-tf	.330
90	deit_large_imagenet_full_seed-0	.328
91	xception	.322
92	resnet50_st_wzc_seed6_2_323	.317
93	resnet50_st_wzc_seed3_2_323	.313
94	AdvProp_efficientnet-b4	.309
95	AT_efficientnet-b4	.309
96	antialias-resnet152	.309
97	resnet50_st_wzc_2	.291
98	densenet-201	.289
99	densenet_201_pytorch	.289
100	effnetb1_272x240	.285
101	resnet-50_v2-tf	.284
102	resnet50_ewconplus_wzc	.282
103	antialiased-rnext101_32x8d	.279
104	densenet-201-keras	.272
105	resnet50-moclr8deg	.266
106	BiT-S-R50x3	.265
107	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.262
108	AdvProp_efficientnet-b7	.260
109	deit_base_imagenet_full_seed-0	.257
110	deit_small_imagenet_full_seed-0	.257
111	efficientnet-b7	.254
112	resnet_101_v1	.253
113	AT_efficientnet-b2	.250
114	AdvProp_efficientnet-b2	.250
115	efficientnet_b0	.249
116	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.248
117	resnet50_random_l2_perturb	.245
118	resnet50	.244
119	Res2Net50_26w_4s	.243
120	resnet50_byol	.231
121	resnet_152_v1	.231
122	antialiased-r50	.224
123	resnet50_ewconplus_wzc_seed6_2_323	.219
124	resnet_50_v1_spiking	.209
125	resnet50_moco_v2	.209
126	convnext_small_imagenet_100_seed-0	.202
127	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.196
128	BiT-S-R101x3	.194
129	resnet-50-pytorch	.194
130	resnet50-sup	.194
131	resnet50_tutorial	.194
132	resnet_50_v1	.194
133	resnet50_hvs_wzc	.193
134	BiT-S-R152x2	.188
135	convnext_tiny_sup	.188
136	vonegrcnn_62e_nobn	.183
137	grcnn	.182
138	AdvProp_efficientnet-b8	.180
139	nasnet_mobile	.179
140	vonegrcnn_47e	.174
141	densenet-121-keras	.173
142	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.172
143	BiT-S-R152x4	.172
144	densenet-121	.166
145	resnet50-SIN_IN_IN	.162
146	resnet_SIN_IN_FT_IN	.162
147	vonegrcnn_62e_nobn	.157
148	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.157
149	grcnn_109	.156
150	densenet-169	.153
151	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.149
152	vonegrcnn_52e_full	.144
153	densenet-169-keras	.143
154	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.137
155	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.136
156	BiT-S-R101x1	.134
157	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.133
158	voneresnet-50-non_stochastic	.132
159	resnet101_imagenet_full	.131
160	alexnet_training_seed_05	.130
161	alexnet_training_seed_01	.130
162	alexnet_training_seed_01_fov4	.130
163	alexnet_training_seed_01_fov12	.130
164	alexnet_training_seed_01_fov16	.130
165	resnet152_imagenet_full	.129
166	vonegrcnn_47e	.127
167	resnet50-simclr-vissl	.127
168	vonegrcnn_52e_full	.125
169	resnet50_random_linf8_perturb	.122
170	BiT-S-R50x1	.121
171	voneresnet-50-robust	.121
172	mobilenet_v2_1_0_224	.121
173	resnet50-vitoimagevidnet8	.119
174	blt_vs	.119
175	eBarlow_lmda_02_1000ep	.118
176	resnet50-SIN_IN	.116
177	inception_v2-tf	.112
178	imagenet_l2_10_0	.105
179	resnet50_imagenet_full	.105
180	resnet50_simclr	.103
181	alexnet_fov16	.102
182	alexnet_fov12	.101
183	alexnet_robust_correct	.099
184	alexnet_l2_3_robust	.098
185	custom_model_cv_18_dagger_408	.097
186	eicircuit_resnet18_bn_20260919	.092
187	vgg-19-keras	.091
188	mobilenet_v1_0.25_128	.090
189	resnet50_imagenet_10_seed-0	.089
190	deit_small_imagenet_10_seed-0	.089
191	deit_small_imagenet_1_seed-0	.089
192	resnet34_imagenet_full	.088
193	alexnet_training_seed_02	.088
194	alexnet_training_seed_04	.088
195	alexnet_training_seed_08	.088
196	alexnet_training_seed_10	.088
197	vgg_19	.088
198	inception_v1	.080
199	voneresnet-50	.079
200	konkle_alexnetgn_ipcl_ref01_primary_model	.079
201	nasnet_mobile-tf	.078
202	mobilenet_v2_0.5_160	.078
203	mobilenet_v1_0.5_128	.078
204	alexnet_training_seed_07	.077
205	mobilenet_v2_1_3_224	.076
206	mobilenet_v2_0.5_128	.075
207	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
208	mobilenet_v2_1_0_192	.075
209	deit_small_imagenet_100_seed-0	.073
210	AdvProp_efficientnet-b0	.073
211	ReAlnet04	.071
212	mobilenet_v2_0.35_160	.069
213	mobilenet_v2_0.35_192	.068
214	ReAlnet08	.068
215	inception_v1-tf	.067
216	mobilenet_v1_0.5_160	.067
217	ReAlnet03	.067
218	ReAlnet09	.064
219	mobilenet_v2_0.35_128	.062
220	alexnet_fov4	.061
221	resnet50_eMMCR_Vanilla	.061
222	mobilenet_v1_0.75_128	.061
223	squeezenet1_0	.059
224	mobilenet_v1_0.5_224	.059
225	mobilenet_v2_0.75_96	.058
226	convnext_small_imagenet_1_seed-0	.058
227	AlexNet_SIN_fov4	.058
228	resnet50-vicregl0p9	.057
229	resnet50-barlow	.057
230	mobilenet_v2_0.5_192-tf	.057
231	mobilenet_v2_1-4_224_pytorch	.057
232	mobilenet_v2_1_4_224	.057
233	ReAlnet05	.056
234	mobilenet_v2_0.5_224-tf	.056
235	resnet50_imagenet_1_seed-0	.054
236	mobilenet_v1_0.25_192	.054
237	resnet50_linf_4_robust	.050
238	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.049
239	mobilenet_v1_0.25_160	.049
240	ReAlnet01	.049
241	ReAlnet06	.049
242	mobilenet_v2_0.35_224	.048
243	mobilenet_v2_0.75_192-tf	.048
244	ReAlnet07	.048
245	mobilenet_v2_1_0_160	.048
246	mobilenet_v2_0.75_224-tf	.047
247	alexnet_random_l2_3_perturb	.047
248	resnet-34	.047
249	mobilenet_v1_0.5_192	.046
250	mobilenet_v2_1.0_224-tf	.046
251	mobilenet_v1_0.75_160	.046
252	resnet50_l2_3_robust	.046
253	resnet_50_v1_spiking_l4	.046
254	resnet-152_v1-tf	.045
255	vgg-16-keras	.045
256	resnet50_imagenet_100_seed-0	.045
257	resnet50_FractalDB	.044
258	mobilenet_v1_0.75_192	.044
259	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.043
260	alexnet_linf_8_robust	.043
261	alexnet_random_linf8_perturb	.041
262	resnet-101_v1-tf	.041
263	alexnet_early_checkpoint	.040
264	vgg_16	.039
265	resnet-18	.039
266	alexnet	.038
267	alexnet_ks_torevert	.038
268	resnet-50-robust	.038
269	imagenet_l2_3_0	.038
270	resnet50_robust_l2_eps3	.038
271	resnet18_imagenet_full	.038
272	mobilenet_v2_0.75_160-tf	.038
273	efficientnet_b1_imagenet_full	.036
274	mobilenet_v2_0.75_128	.036
275	mobilenet_v2_1.0_128-tf	.036
276	texture_shape_resnet50_trained_on_SIN	.036
277	mobilenet_v1_1.0_160	.036
278	efficientnet_b0_imagenet_full	.035
279	shufflenet_v2_x1_0	.034
280	resnet_50_v1_spiking_l4a	.034
281	resnet50_robust_l2_eps1	.033
282	mobilenet_v1_0.25_224	.033
283	alexnet_reduced_aliasing_early_checkpoint	.031
284	squeezenet1_1	.031
285	mobilenet_v1_1.0_192	.030
286	mobilenet_v2_1.0_96	.028
287	alexnet_training_seed_09	.027
288	regnet_y_400mf	.027
289	resnet50_linf_8_robust	.026
290	alexnet_training_seed_03	.024
291	mobilenet_v2_0.5_96	.024
292	resnet50-SIN	.023
293	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.023
294	mobilenet_v2_1_0_128	.022
295	mobilenet_v1_1.0_224	.022
296	convnext_small_imagenet_10_seed-0	.022
297	resnet50-vicregl0p75	.022
298	resnet-50_untrained	.021
299	0.5x_resnet-18_LC_w_sh_1_iter	.021
300	mobilenet_v2_1.0_160-tf	.020
301	mobilenet_v1_0.75_224	.017
302	mobilenet_v1_1.0_128	.016
303	mobilenet_v2_0_75_224	.016
304	AlexNet_SIN_fov12	.014
305	mobilenet_v2_0.35_96	.013
306	AlexNet_SIN_fov16	.012
307	ReAlnet02	.011
308	cornet_s	.011
309	ReAlnet10	.011
310	mobilenet_v2_1.3_224-tf	.010
311	vonealexnet_gaussian_noise_std4_fixed	.010
312	resnet_50_v1_spiking_l3	.009
313	mobilenet_v2_1.4_224-tf	.008
314	barlow-twins-resnet50	.006
315	mobilenet_v2_0_5_192	.006
316	efficientnet_b2_imagenet_full	.006
317	CORnet-S	.005
318	mobilenet_v2_0_75_160	.005
319	alexnet_training_seed_06	.005
320	texture_shape_alexnet_trained_on_SIN	.005
321	artResNet18_1	.004
322	mobilenet_v2_1.0_192-tf	.004
323	resnet50-vicreg	.003
324	mobilenet_v2_0_75_192	.003
325	AlexNet_SIN	.002
326	mobilenet_v2_0_5_224	.001
327	resnet-50_v1-tf	.000
328	resnet-18-LC_w_sh_100_iter_conv_init_m
329	ViT-B/32
330	BiT-M-R50x3
331	BiT-M-R50x1
332	resnet-18-LC_w_sh_1_iter_conv_init_m
333	resnet-18-LC_w_sh_1_iter_m
334	BiT-M-R152x2
335	resnet-18-LC_w_sh_10_iter_m
336	ReAlnet09_ALL
337	resnet-18-LC_w_sh_100_iter_m
338	resnet-18-LC_w_sh_10_iter_conv_init_m
339	FrankRobWobv0
340	0.5x_resnet-18_LC
341	CORnetZ_CIFAR10
342	resnet18-local_aggregation
343	r3m_resnet18
344	CORnet-Z
345	resnet18-deepcluster
346	vggface
347	my-model
348	resnet18-instance_recognition
349	0.5x_resnet-18_LC_w_sh_10_iter
350	r3m_resnet50
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-colorization
363	resnet18-relative_position
364	resnet18-autoencoder
365	resnet18-simclr
366	ViT_L_32
367	ViT_B_32
368	resnet18-depth_prediction
369	ViT_B_16
370	r3m_resnet34_nocrop
371	resnet18-contrastive_predictive
372	resnet-18-LC_untrained
373	resnet-18_untrained
374	resnet-50x2_untrained
375	dcgan
376	unet_entire
377	v1-pyr-nodown
378	CORnetZ_CIFAR10_bs32_20_04
379	pixels
380	dorinet_cornet_z
381	omnivore_swinT
382	my-model
383	openclip
384	resnet50-cifar
385	resnet50_pretrained_with_retinal_waves
386	resnet50_ImageNet
387	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
388	ReAlnet08_ALL
389	yudixie_resnet50_random_0_240908
390	yudixie_resnet50_imagenet1kpret_0_240908
391	yudixie_resnet50_imagenet1kpret_0_240312
392	yudixie_resnet50_cat_obj_class_all_latents_0_240908
393	yudixie_resnet50_object_class_0_240908
394	yudixie_resnet50_category_class_0_240908
395	resnet18_imagenet21kP
396	yudixie_resnet50_distance_reg_0_240908
397	ConvLSTM
398	PredRNN
399	SimVP
400	TAU
401	vit_base_patch16_dinov3-lvd1689m
402	MIM
403	hmax
404	briaai_rmbg_1_4
405	pnasnet_large_pytorch
406	inception_v3_pytorch
407	vit_base_patch14_reg4_dinov2-lvd142m
408	ReAlnet01_cornet
409	yolos_tiny
410	yudixie_resnet18_translation_reg_0_240719
411	ReAlnet02_cornet
412	yudixie_resnet18_distance_reg_0_240719
413	yudixie_resnet18_rotation_reg_0_240719
414	yudixie_resnet18_imagenet1kpret_0_240719
415	compact_resnet50_V4
416	vit_base_patch14_dinov2-lvd142m
417	compact_resnet50_IT
418	resnet18_ecoset_full
419	ReAlnet03_cornet
420	ReAlnet01_cornet_fov4
421	resnet34_ecoset_full
422	VOneCORnet-S
423	resnet50_ecoset_full
424	resnet101_ecoset_full
425	yudixie_resnet50_distance_translation_0_240908
426	compact_vgg19_V4
427	yudixie_resnet18_distance_translation_0_240719
428	ReAlnet01_cornet_fov12
429	yudixie_resnet18_translation_rotation_0_240719
430	ReAlnet04_cornet
431	omnivore_swinB
432	yudixie_resnet18_distance_rotation_0_240719
433	yudixie_resnet18_category_class_0_240719
434	yudixie_resnet50_rotation_reg_0_240908
435	ReAlnet05_cornet
436	yudixie_resnet18_random_0_240719
437	resnet-18_test_m
438	yudixie_resnet50_distance_rotation_0_240908
439	yudixie_resnet18_cat_obj_class_all_latents_0_240719
440	SeLaVi-AVE
441	yudixie_resnet18_distance_translation_rotation_0_240719
442	yudixie_resnet18_object_class_0_240719
443	compact_resnet50_robust_V4
444	compact_vgg19_IT
445	ReAlnet06_cornet
446	yudixie_resnet50_translation_reg_0_240908
447	r3d_18
448	ReAlnet07_cornet
449	mc3_18
450	ReAlnet02_ALL
451	s3d
452	ReAlnet08_cornet
453	mvit_v1_b
454	ReAlnet04_ALL
455	compact_cornets_V4
456	ReAlnet01_cornet_fov16
457	ReAlnet03_ALL
458	compact_cornets_IT
459	ReAlnet09_cornet
460	SeLaVi-Kinetics400
461	ReAlnet05_ALL
462	SeLaVi-VGG-Sound
463	ReAlnet06_ALL
464	omnivore_swinS
465	r2plus1d_18
466	compact_resnet50_robust_IT
467	ReAlnet07_ALL
468	mvit_v2_s
469	ReAlnet10_cornet
470	SeLaVi-Kinetics-Sound
471	resnet152_ecoset_full
472	yudixie_resnet50_distance_translation_rotation_0_240908
473	yudixie_resnet50_translation_rotation_0_240908
474	resnet50_primary_visual_cortex
475	ReAlnet10_ALL
476	ReAlnet01_ALL
477	resnet18_fair
478	pr1_stl10_disentangled_alpha04
479	predictive_coding_pc
480	yudixie_wbh_object_class_scaling_0415_run_0
481	yudixie_wbh_object_class_scaling_0415_imagenet
482	yudixie_wbh_object_class_scaling_0415_run_3
483	yudixie_wbh_object_class_scaling_0415_run_2
484	yudixie_wbh_object_class_scaling_0415_run_1
485	deepeisnn_ei_cifar10_vgg19
486	deepeisnn_ei_cifar10_resnet18
487	deepeisnn_ei_imagenet_resnet18
488	dinov2_vitl14_reg_lc_featread
489	gabor_filter_entropy_4x4
490	gabor_filter_mean_abs_4x4_v2
491	gabor_filter_entropy_4x4_v2
492	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

0.43.

Note that scores are relative to this ceiling.

Data: Geirhos2021uniformnoise

Metric: error_consistency