Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021eidolonIII-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnext101_32x16d_wsl	.726
2	ViT_L_32_imagenet1k	.644
3	resnext101_32x48d_wsl	.641
4	SWSL_resnet50	.638
5	resnext101_32x32d_wsl	.629
6	vision_transformer_vit_large_patch16_224	.610
7	AdvProp_efficientnet-b4	.597
8	AT_efficientnet-b4	.597
9	convnext_base_fb_in22k_ft_in1k	.596
10	ViT_B_16_imagenet1k	.582
11	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.579
12	fixres_resnext101_32x48d_wsl	.578
13	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.574
14	eva02_large_in22k	.569
15	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.569
16	resnext101_32x8d_wsl	.567
17	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.564
18	cvt_cvt-13-224-in1k_4_LucyV4	.561
19	effnetv2m_custom384	.558
20	convnext_xlarge:fb_in22k_ft_in1k	.556
21	AdvProp_efficientnet-b6	.556
22	convnext_small_imagenet_full_seed-0	.554
23	SWSL_resnext101_32x8d	.551
24	focalnet_tiny_lrf_in1k	.550
25	resnet_101_v2	.548
26	convnext_small_imagenet_100_seed-0	.546
27	resnet_50_v2	.541
28	pnasnet_large-tf	.535
29	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.535
30	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.535
31	convnext_large_clip_laion2b_finelayers	.523
32	convnext_tiny_imagenet_full_seed-0	.521
33	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.518
34	resnet101	.517
35	convnext_base:clip_laiona_augreg_ft_in1k_384	.511
36	convnext_base_fb_in1k	.507
37	AdvProp_efficientnet-b7	.505
38	regnety_032	.505
39	convnext_large:fb_in22k_ft_in1k	.502
40	ViT_B_32_imagenet1k	.502
41	convnext_xxlarge_clip	.502
42	pnasnet_large_halfPrecision	.501
43	pnasnet_large	.501
44	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.500
45	effnetb1_272x240	.495
46	cvt_cvt-13-384-in1k_4_LucyV4	.494
47	nasnet_large	.490
48	resnet_152_v2	.489
49	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.489
50	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.484
51	convnext_large_in22k_supervised	.483
52	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.480
53	dinov2_vitl14_reg_lc	.479
54	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.477
55	dinov2_vitl14_lc	.477
56	resnet-152_v2_pytorch	.476
57	resnet152_imagenet_full	.474
58	efficientnet-b7	.473
59	vit_relpos_base_patch16_clsgap_224:sw_in1k	.473
60	antialias-resnet152	.470
61	inception_v4	.469
62	resnet50_st_wzc_seed3_2_323	.468
63	AT_efficientnet-b2	.468
64	AdvProp_efficientnet-b2	.468
65	convnext_tiny:in12k_ft_in1k	.468
66	resnet_101_v1	.465
67	vit_large_patch14_clip_224:laion2b_ft_in1k	.464
68	CLIP-RN50	.464
69	resnet-152_v2-tf	.459
70	resnet50_st_wzc_seed6_2_323	.453
71	convnext_large_imagenet_full_seed-0	.453
72	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.453
73	vit_large_patch14_clip_336:laion2b_ft_in1k	.451
74	inception_v4-tf	.445
75	efficientnet_b0	.444
76	nasnet_large-tf	.443
77	CLIP_ViT-B_32	.442
78	deit_base_imagenet_full_seed-0	.441
79	deit_large_imagenet_full_seed-0	.439
80	vit_large_patch14_clip_224:openai_ft_in1k	.438
81	antialiased-rnext101_32x8d	.437
82	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.433
83	resnet_152_v1	.433
84	cvt_cvt-21-384-in1k_4_LucyV4	.432
85	vit_base_patch16_clip_224:openai_ft_in1k	.432
86	seresnext50_32x4d	.431
87	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.429
88	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.427
89	convnext_femto_ols:d1_in1k	.424
90	BiT-S-R50x3	.423
91	resnet50_ewconplus_wzc_seed5_2__323	.420
92	convnext_base_imagenet_full_seed-0	.418
93	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.416
94	deit_small_imagenet_full_seed-0	.415
95	CLIP_resnet50	.415
96	CLIP_resnet50_float32	.415
97	dinov2_vitg14_lc	.415
98	xception	.412
99	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.412
100	cv_18_dagger_408_pretrained	.400
101	resnet50_ewconplus_wzc_seed6_2_323	.399
102	grcnn_109	.397
103	inception_v3-tf	.395
104	resnet34_imagenet_full	.393
105	vit_large_clip336_openai	.391
106	voneresnet-50-non_stochastic	.391
107	inception_v3	.388
108	Res2Net50_26w_4s	.383
109	grcnn	.380
110	tv_efficientnet-b1	.379
111	resnet101_imagenet_full	.377
112	densenet-121	.373
113	resnet50_ewconplus_wzc_seed2_2__323	.371
114	xception-keras	.369
115	resnet50_linf_4_robust	.368
116	cvt_cvt-21-224-in1k_4_LucyV4	.366
117	resnet-152_v1-tf	.364
118	resnet50_hvs_wzc	.363
119	resnet50_ewconplus_wzc	.363
120	densenet-201	.360
121	densenet_201_pytorch	.360
122	dinov2_vitl14_lc_res336	.359
123	densenet-121-keras	.357
124	resnet50-SIN_IN	.356
125	densenet-201-keras	.353
126	efficientnet_b2_imagenet_full	.353
127	vonegrcnn_52e_full	.352
128	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.350
129	resnet50	.346
130	resnet-50_v2-tf	.343
131	resnet50-moclr8deg	.340
132	vonegrcnn_62e_nobn	.334
133	pnasnet_large_pytorch	.333
134	dinov2_vitg14_reg_lc	.333
135	vonegrcnn_47e	.327
136	custom_model_cv_18_dagger_408	.324
137	blt_vs	.320
138	BiT-S-R152x2	.320
139	AdvProp_efficientnet-b8	.319
140	resnet50_random_linf8_perturb	.319
141	resnet50-VITO-8deg-cc	.319
142	resnet50_imagenet_full	.318
143	ReAlnet02	.317
144	resnet-50_v1-tf	.316
145	BiT-S-R101x3	.315
146	densenet-169	.314
147	resnet50-SIN_IN_IN	.313
148	resnet_SIN_IN_FT_IN	.313
149	nasnet_mobile	.312
150	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.309
151	vit_huge_clip336_laion	.307
152	resnet50_st_wzc_2	.305
153	vonegrcnn_62e_nobn	.304
154	vonegrcnn_52e_full	.302
155	inception_v2-tf	.302
156	mobilenet_v2_1-4_224_pytorch	.299
157	mobilenet_v2_1_4_224	.299
158	densenet-169-keras	.297
159	ReAlnet05	.297
160	alexnet_fov4	.296
161	texture_shape_resnet50_trained_on_SIN	.295
162	resnet_50_v1_spiking	.295
163	vonegrcnn_47e	.294
164	vgg_19	.294
165	resnet-101_v1-tf	.292
166	ReAlnet06	.292
167	resnet-50-pytorch	.291
168	resnet50-sup	.291
169	resnet50_tutorial	.291
170	resnet_50_v1	.291
171	antialiased-r50	.290
172	ReAlnet10	.290
173	BiT-S-R152x4	.287
174	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.286
175	resnet50_random_l2_perturb	.286
176	ReAlnet04	.285
177	voneresnet-50	.284
178	voneresnet-50-robust	.284
179	mobilenet_v2_1_0_160	.283
180	resnet50_moco_v2	.282
181	ReAlnet07	.281
182	inception_v1	.278
183	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.277
184	CORnet-S	.276
185	ReAlnet08	.274
186	ReAlnet01	.273
187	resnet50_l2_3_robust	.273
188	mobilenet_v2_1.4_224-tf	.272
189	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
190	ReAlnet03	.267
191	cornet_s	.263
192	mobilenet_v2_1_3_224	.262
193	convnext_base_fb_in1k_gram_aligned_dinov3	.261
194	mobilenet_v2_1_0_224	.258
195	eicircuit_resnet18_bn_20260919	.258
196	resnet50_linf_8_robust	.257
197	resnet50-SIN	.256
198	resnet50_byol	.255
199	AlexNet_SIN_fov4	.252
200	mobilenet_v2_1.0_192-tf	.252
201	mobilenet_v2_1.0_224-tf	.251
202	inception_v1-tf	.250
203	resnet18_imagenet_full	.247
204	mobilenet_v2_1_0_192	.245
205	resnet-34	.245
206	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.244
207	vgg_16	.242
208	BiT-S-R50x1	.241
209	mobilenet_v2_1.3_224-tf	.240
210	efficientnet_b1_imagenet_full	.238
211	resnet50_robust_l2_eps1	.233
212	mobilenet_v2_1.0_160-tf	.231
213	eBarlow_lmda_02_1000ep	.230
214	alexnet_random_linf8_perturb	.228
215	ReAlnet09	.226
216	efficientnet_b0_imagenet_full	.221
217	mobilenet_v1_0.75_224	.220
218	resnet-50-robust	.219
219	imagenet_l2_3_0	.219
220	resnet50_robust_l2_eps3	.219
221	resnet-18	.215
222	mobilenet_v1_1.0_224	.214
223	mobilenet_v2_0_5_224	.213
224	resnet50-vitoimagevidnet8	.212
225	regnet_y_400mf	.203
226	vonealexnet_gaussian_noise_std4_fixed	.200
227	mobilenet_v2_0.75_128	.196
228	alexnet_random_l2_3_perturb	.190
229	mobilenet_v2_0_75_160	.189
230	alexnet_reduced_aliasing_early_checkpoint	.174
231	mobilenet_v2_0.5_192-tf	.173
232	mobilenet_v2_0.75_160-tf	.171
233	shufflenet_v2_x1_0	.168
234	nasnet_mobile-tf	.168
235	alexnet_ks_torevert	.167
236	alexnet	.167
237	resnet50_simclr	.162
238	mobilenet_v1_0.75_192	.161
239	mobilenet_v2_1_0_128	.157
240	deit_small_imagenet_100_seed-0	.154
241	BiT-S-R101x1	.154
242	vgg-19-keras	.151
243	AdvProp_efficientnet-b0	.151
244	alexnet_robust_correct	.146
245	mobilenet_v1_1.0_192	.145
246	mobilenet_v1_0.75_160	.142
247	convnext_tiny_sup	.138
248	mobilenet_v2_0_5_192	.137
249	mobilenet_v2_0.35_192	.136
250	alexnet_fov16	.135
251	alexnet_l2_3_robust	.132
252	vgg-16-keras	.130
253	resnet50-barlow	.129
254	alexnet_training_seed_05	.129
255	alexnet_training_seed_01	.129
256	alexnet_training_seed_01_fov4	.129
257	alexnet_training_seed_01_fov12	.129
258	alexnet_training_seed_01_fov16	.129
259	alexnet_linf_8_robust	.127
260	mobilenet_v2_0_75_192	.125
261	alexnet_early_checkpoint	.124
262	mobilenet_v2_0.35_96	.124
263	mobilenet_v1_1.0_128	.124
264	mobilenet_v1_1.0_160	.123
265	resnet50_eMMCR_Vanilla	.123
266	0.5x_resnet-18_LC_w_sh_1_iter	.121
267	resnet50-simclr-vissl	.121
268	mobilenet_v1_0.5_224	.117
269	mobilenet_v2_0_75_224	.113
270	resnet50_imagenet_10_seed-0	.112
271	deit_small_imagenet_10_seed-0	.112
272	deit_small_imagenet_1_seed-0	.112
273	alexnet_fov12	.112
274	mobilenet_v1_0.5_128	.112
275	mobilenet_v1_0.5_192	.108
276	squeezenet1_1	.105
277	konkle_alexnetgn_ipcl_ref01_primary_model	.105
278	mobilenet_v1_0.75_128	.104
279	resnet50-vicreg	.103
280	mobilenet_v2_1.0_128-tf	.101
281	resnet50_imagenet_100_seed-0	.099
282	mobilenet_v2_0.5_96	.097
283	mobilenet_v2_0.5_160	.096
284	mobilenet_v2_0.35_224	.095
285	mobilenet_v2_1.0_96	.094
286	AlexNet_SIN	.093
287	mobilenet_v1_0.25_224	.093
288	mobilenet_v2_0.75_96	.093
289	mobilenet_v1_0.5_160	.091
290	convnext_small_imagenet_10_seed-0	.091
291	mobilenet_v2_0.75_192-tf	.090
292	mobilenet_v2_0.75_224-tf	.090
293	imagenet_l2_10_0	.089
294	resnet_50_v1_spiking_l4a	.089
295	mobilenet_v2_0.35_128	.085
296	mobilenet_v1_0.25_160	.081
297	mobilenet_v2_0.5_224-tf	.080
298	mobilenet_v2_0.35_160	.079
299	texture_shape_alexnet_trained_on_SIN	.078
300	alexnet_training_seed_06	.076
301	squeezenet1_0	.071
302	mobilenet_v1_0.25_192	.069
303	resnet50-vicregl0p75	.063
304	resnet_50_v1_spiking_l4	.062
305	resnet_50_v1_spiking_l3	.057
306	mobilenet_v2_0.5_128	.056
307	AlexNet_SIN_fov12	.042
308	my-model	.040
309	alexnet_training_seed_02	.037
310	alexnet_training_seed_04	.037
311	alexnet_training_seed_08	.037
312	alexnet_training_seed_10	.037
313	artResNet18_1	.037
314	resnet50-vicregl0p9	.036
315	alexnet_training_seed_09	.034
316	mobilenet_v1_0.25_128	.033
317	alexnet_training_seed_07	.033
318	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.028
319	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.026
320	resnet50_FractalDB	.023
321	resnet-50_untrained	.018
322	AlexNet_SIN_fov16	.010
323	resnet50_imagenet_1_seed-0	.010
324	convnext_small_imagenet_1_seed-0	.007
325	barlow-twins-resnet50	.003
326	alexnet_training_seed_03	.001
327	mobilevit_small	.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	BiT-M-R152x2
333	resnet-18-LC_w_sh_1_iter_conv_init_m
334	resnet-18-LC_w_sh_10_iter_m
335	resnet-18_test_m
336	resnet-18-LC_w_sh_100_iter_m
337	resnet-18-LC_w_sh_1_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	resnet18-deepcluster
344	r3m_resnet18
345	CORnet-Z
346	resnet18-instance_recognition
347	my-model
348	vggface
349	0.5x_resnet-18_LC_w_sh_10_iter
350	resnet18-colorization
351	r3m_resnet50
352	r3m_resnet34
353	resnet-18-LC_m
354	r3m_resnet50_nocrop
355	resnet18-supervised
356	resnet-18-LC_1st_conv_m
357	resnet-18-LC_conv_init_m
358	resnet18-contrastive_multiview
359	0.5x_resnet-18
360	RN50
361	0.5x_resnet-18_LC_w_sh_100_iter
362	RN50
363	resnet18-relative_position
364	resnet18-autoencoder
365	resnet18-simclr
366	ViT_L_32
367	ViT_B_32
368	yudixie_resnet50_random_0_240908
369	resnet18-depth_prediction
370	ViT_B_16
371	r3m_resnet34_nocrop
372	resnet18-contrastive_predictive
373	omnivore_swinT
374	resnet-18-LC_untrained
375	resnet-18_untrained
376	resnet-50x2_untrained
377	dcgan
378	v1-pyr-nodown
379	unet_entire
380	CORnetZ_CIFAR10_bs32_20_04
381	pixels
382	dorinet_cornet_z
383	openclip
384	resnet50-cifar
385	resnet50_pretrained_with_retinal_waves
386	resnet50_ImageNet
387	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
388	yudixie_resnet50_imagenet1kpret_0_240908
389	yudixie_resnet50_imagenet1kpret_0_240312
390	yudixie_resnet50_object_class_0_240908
391	yudixie_resnet50_cat_obj_class_all_latents_0_240908
392	yudixie_resnet50_category_class_0_240908
393	inception_v3_pytorch
394	resnet18_imagenet21kP
395	yudixie_resnet50_distance_reg_0_240908
396	ConvLSTM
397	PredRNN
398	TAU
399	MIM
400	hmax
401	briaai_rmbg_1_4
402	ReAlnet01_cornet
403	vit_base_patch16_dinov3-lvd1689m
404	ReAlnet02_cornet
405	yudixie_resnet18_distance_reg_0_240719
406	compact_resnet50_V4
407	yudixie_resnet18_rotation_reg_0_240719
408	ReAlnet03_cornet
409	vit_base_patch14_dinov2-lvd142m
410	resnet34_ecoset_full
411	VOneCORnet-S
412	resnet50_ecoset_full
413	ReAlnet01_cornet_fov4
414	vit_base_patch14_reg4_dinov2-lvd142m
415	yudixie_resnet50_distance_translation_0_240908
416	compact_resnet50_robust_V4
417	yudixie_resnet18_distance_translation_0_240719
418	yudixie_resnet18_translation_rotation_0_240719
419	compact_resnet50_IT
420	yudixie_resnet18_cat_obj_class_all_latents_0_240719
421	ReAlnet05_cornet
422	yudixie_resnet18_translation_reg_0_240719
423	ReAlnet01_cornet_fov12
424	yudixie_resnet50_rotation_reg_0_240908
425	yudixie_resnet18_distance_translation_rotation_0_240719
426	yudixie_resnet18_object_class_0_240719
427	SeLaVi-AVE
428	yudixie_resnet18_imagenet1kpret_0_240719
429	r3d_18
430	compact_vgg19_V4
431	yudixie_resnet50_translation_reg_0_240908
432	ReAlnet06_cornet
433	ReAlnet01_cornet_fov16
434	compact_vgg19_IT
435	yudixie_resnet50_translation_rotation_0_240908
436	mc3_18
437	ReAlnet01_ALL
438	ReAlnet07_cornet
439	s3d
440	mvit_v1_b
441	ReAlnet08_cornet
442	ReAlnet02_ALL
443	compact_cornets_V4
444	omnivore_swinB
445	ReAlnet04_ALL
446	SeLaVi-Kinetics400
447	ReAlnet09_cornet
448	SeLaVi-VGG-Sound
449	compact_cornets_IT
450	ReAlnet05_ALL
451	SeLaVi-Kinetics-Sound
452	omnivore_swinS
453	resnet152_ecoset_full
454	ReAlnet06_ALL
455	r2plus1d_18
456	mvit_v2_s
457	compact_resnet50_robust_IT
458	ReAlnet10_cornet
459	ReAlnet07_ALL
460	resnet18_ecoset_full
461	resnet101_ecoset_full
462	yudixie_resnet18_category_class_0_240719
463	yudixie_resnet50_distance_translation_rotation_0_240908
464	ReAlnet08_ALL
465	yudixie_resnet18_random_0_240719
466	yudixie_resnet18_distance_rotation_0_240719
467	yudixie_resnet50_distance_rotation_0_240908
468	ReAlnet04_cornet
469	ReAlnet09_ALL
470	resnet50_primary_visual_cortex
471	yolos_tiny
472	ReAlnet10_ALL
473	ReAlnet03_ALL
474	resnet18_fair
475	pr1_stl10_disentangled_alpha04
476	predictive_coding_pc
477	yudixie_wbh_object_class_scaling_0415_run_0
478	yudixie_wbh_object_class_scaling_0415_run_3
479	yudixie_wbh_object_class_scaling_0415_imagenet
480	yudixie_wbh_object_class_scaling_0415_run_2
481	yudixie_wbh_object_class_scaling_0415_run_1
482	deepeisnn_ei_cifar10_vgg19
483	deepeisnn_ei_cifar10_resnet18
484	deepeisnn_ei_imagenet_resnet18
485	dinov2_vitl14_reg_lc_featread
486	gabor_filter_entropy_4x4
487	gabor_filter_entropy_4x4_v2
488	gabor_filter_entropy_4x4_v2_forcedCosine
489	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

0.46.

Note that scores are relative to this ceiling.

Data: Geirhos2021eidolonIII

Metric: error_consistency