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("Geirhos2021eidolonII-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	.732
2	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.703
3	ViT_B_16_imagenet1k	.699
4	vision_transformer_vit_large_patch16_224	.696
5	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.692
6	vit_base_patch16_clip_224:openai_ft_in1k	.680
7	vit_relpos_base_patch16_clsgap_224:sw_in1k	.674
8	convnext_tiny_imagenet_full_seed-0	.665
9	resnext101_32x48d_wsl	.664
10	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.662
11	resnext101_32x16d_wsl	.662
12	deit3_base_patch16_224_fb_in1k	.661
13	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.659
14	AdvProp_efficientnet-b6	.656
15	resnext101_32x32d_wsl	.650
16	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.650
17	resnet_152_v2	.646
18	focalnet_tiny_lrf_in1k	.646
19	cvt_cvt-13-224-in1k_4_LucyV4	.643
20	pnasnet_large	.640
21	pnasnet_large_halfPrecision	.636
22	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.635
23	convnext_small_imagenet_100_seed-0	.632
24	resnet_50_v2	.630
25	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.626
26	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.625
27	resnext101_32x8d_wsl	.624
28	CLIP_ViT-B_32	.622
29	ViT_L_32_imagenet1k	.617
30	convnext_large:fb_in22k_ft_in1k	.613
31	vit_large_patch14_clip_224:laion2b_ft_in1k	.613
32	SWSL_resnet50	.613
33	resnet_101_v2	.610
34	convnext_base_fb_in22k_ft_in1k	.609
35	vit_large_patch14_clip_224:openai_ft_in1k	.603
36	resnet-152_v2-tf	.602
37	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.597
38	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.590
39	convnext_femto_ols:d1_in1k	.588
40	cvt_cvt-13-384-in1k_4_LucyV4	.582
41	AdvProp_efficientnet-b7	.578
42	pnasnet_large-tf	.577
43	resnet50_st_wzc_seed5_2_323	.571
44	convnext_large_imagenet_full_seed-0	.569
45	convnext_base_fb_in1k	.569
46	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.564
47	AdvProp_efficientnet-b4	.559
48	AT_efficientnet-b4	.559
49	resnet50_ewconplus_noseed_2_323	.559
50	CLIP_resnet50	.558
51	CLIP_resnet50_float32	.558
52	convnext_base:clip_laiona_augreg_ft_in1k_384	.555
53	fixres_resnext101_32x48d_wsl	.549
54	convnext_tiny:in12k_ft_in1k	.547
55	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.546
56	effnetv2m_custom384	.540
57	efficientnet_b0	.538
58	cvt_cvt-21-384-in1k_4_LucyV4	.535
59	efficientnet-b7	.534
60	nasnet_large	.534
61	resnet152_imagenet_full	.527
62	resnet_152_v1	.524
63	resnet50-VITO-8deg-cc	.522
64	deit3_base_patch16_224_fb_in22k_ft_in1k	.521
65	nasnet_large-tf	.520
66	cvt_cvt-21-224-in1k_4_LucyV4	.519
67	ViT_B_32_imagenet1k	.518
68	antialias-resnet152	.515
69	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.513
70	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.512
71	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.509
72	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.503
73	AT_efficientnet-b2	.501
74	AdvProp_efficientnet-b2	.501
75	resnet50_ewconplus_wzc_seed2_2__323	.500
76	deit_large_imagenet_full_seed-0	.496
77	effnetb1_272x240	.495
78	convnext_xlarge:fb_in22k_ft_in1k	.491
79	inception_v4	.482
80	vit_large_patch14_clip_336:laion2b_ft_in1k	.481
81	resnet50_ewconplus_wzc_seed5_2__323	.479
82	CLIP-RN50	.477
83	convnext_base_imagenet_full_seed-0	.475
84	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.473
85	resnet50_ewconplus_wzc_seed7_2_323	.471
86	resnet_101_v1	.470
87	antialiased-rnext101_32x8d	.469
88	convnext_small_imagenet_full_seed-0	.465
89	deit_base_imagenet_full_seed-0	.465
90	inception_v3_pytorch	.463
91	resnet50_st_wzc_seed6_2_323	.459
92	inception_v3	.458
93	resnet-152_v1-tf	.455
94	grcnn_109	.454
95	tv_efficientnet-b1	.454
96	resnet50-moclr8deg	.453
97	resnet-152_v2_pytorch	.453
98	resnet101	.451
99	resnet50_imagenet_full	.448
100	resnet50_ewconplus_wzc_2_323	.448
101	pnasnet_large_pytorch	.445
102	cv_18_dagger_408_pretrained	.443
103	resnet101_imagenet_full	.433
104	densenet-201-keras	.423
105	inception_v4-tf	.423
106	densenet-201	.421
107	densenet_201_pytorch	.421
108	resnet50_st_wzc_noseed_2_323	.417
109	resnet50_st_wzc_seed3_2_323	.417
110	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.416
111	resnet-50_v2-tf	.416
112	grcnn	.414
113	alexnet_fov4	.411
114	deit_small_imagenet_full_seed-0	.410
115	resnet50_random_linf8_perturb	.405
116	custom_model_cv_18_dagger_408	.401
117	xception-keras	.399
118	BiT-S-R50x3	.399
119	Res2Net50_26w_4s	.394
120	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.379
121	resnet34_imagenet_full	.379
122	inception_v3-tf	.375
123	BiT-S-R152x2	.371
124	resnet50_random_l2_perturb	.371
125	resnet50_ewconplus_wzc_seed6_2_323	.368
126	ReAlnet03	.366
127	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.365
128	resnet50_moco_v2	.364
129	resnet50_st_wzc_2	.363
130	resnet50	.363
131	cornet_s	.361
132	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.361
133	resnet50_ewconplus_wzc_seed4_2_323	.360
134	vonegrcnn_62e_nobn	.359
135	efficientnet_b2_imagenet_full	.359
136	resnet50_linf_4_robust	.358
137	vonegrcnn_47e	.354
138	vonegrcnn_52e_full	.351
139	AdvProp_efficientnet-b8	.350
140	ReAlnet01	.345
141	ReAlnet04	.342
142	resnet50_byol	.337
143	BiT-S-R101x3	.331
144	vonegrcnn_47e	.330
145	resnet50_tutorial	.329
146	resnet_50_v1	.329
147	resnet-50-pytorch	.329
148	resnet50-sup	.329
149	resnet18_imagenet_full	.329
150	resnet50_ewconplus_wzc	.327
151	vonegrcnn_52e_full	.325
152	densenet-121-keras	.320
153	resnet-50_v1-tf	.317
154	vgg_19	.317
155	antialiased-r50	.315
156	alexnet_random_linf8_perturb	.314
157	resnet50-SIN_IN_IN	.313
158	resnet_SIN_IN_FT_IN	.313
159	ReAlnet06	.313
160	densenet-169-keras	.311
161	vonegrcnn_62e_nobn	.311
162	alexnet_reduced_aliasing_early_checkpoint	.308
163	CORnet-S	.304
164	densenet-121	.302
165	convnext_base_fb_in1k_gram_aligned_dinov3	.300
166	ReAlnet05	.299
167	ReAlnet07	.298
168	xception	.298
169	resnet_50_v1_spiking	.297
170	voneresnet-50-robust	.296
171	mobilenet_v2_1.4_224-tf	.296
172	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.294
173	inception_v2-tf	.294
174	voneresnet-50	.289
175	inception_v1-tf	.289
176	mobilenet_v2_1-4_224_pytorch	.287
177	mobilenet_v2_1_4_224	.287
178	voneresnet-50-non_stochastic	.286
179	resnet-101_v1-tf	.285
180	ReAlnet10	.279
181	ReAlnet08	.278
182	ReAlnet02	.274
183	densenet-169	.270
184	vgg_16	.270
185	mobilenet_v2_1_0_224	.267
186	resnet50_l2_3_robust	.266
187	mobilenet_v2_1_0_160	.266
188	ReAlnet09	.265
189	mobilenet_v2_1_3_224	.260
190	resnet50-SIN_IN	.258
191	BiT-S-R152x4	.257
192	BiT-S-R50x1	.256
193	alexnet_l2_3_robust	.255
194	resnet50-vitoimagevidnet8	.254
195	alexnet	.252
196	alexnet_ks_torevert	.252
197	nasnet_mobile	.250
198	blt_vs	.247
199	alexnet_linf_8_robust	.246
200	alexnet_robust_correct	.236
201	vonealexnet_gaussian_noise_std4_fixed	.235
202	inception_v1	.235
203	alexnet_fov12	.232
204	mobilenet_v2_0_5_224	.226
205	resnet-50-robust	.226
206	imagenet_l2_3_0	.226
207	resnet50_robust_l2_eps3	.226
208	mobilenet_v2_1.0_160-tf	.225
209	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.225
210	deit_small_imagenet_100_seed-0	.224
211	efficientnet_b0_imagenet_full	.224
212	konkle_alexnetgn_ipcl_ref01_primary_model	.223
213	convnext_tiny_sup	.223
214	resnet-18	.216
215	resnet-34	.216
216	alexnet_random_l2_3_perturb	.215
217	resnet50_robust_l2_eps1	.206
218	mobilenet_v2_1_0_192	.206
219	vgg-16-keras	.204
220	mobilenet_v2_1.3_224-tf	.198
221	mobilenet_v1_1.0_224	.196
222	resnet50_linf_8_robust	.195
223	BiT-S-R101x1	.191
224	regnet_y_400mf	.190
225	efficientnet_b1_imagenet_full	.189
226	mobilenet_v2_1.0_192-tf	.189
227	resnet50_imagenet_10_seed-0	.182
228	deit_small_imagenet_10_seed-0	.182
229	mobilenet_v1_0.75_224	.180
230	mobilenet_v2_1.0_224-tf	.180
231	resnet50-barlow	.179
232	resnet50-vicreg	.178
233	texture_shape_resnet50_trained_on_SIN	.178
234	deit_small_imagenet_1_seed-0	.174
235	alexnet_fov16	.174
236	resnet50_eMMCR_Vanilla	.173
237	nasnet_mobile-tf	.169
238	mobilenet_v2_0_5_192	.166
239	convnext_small_imagenet_10_seed-0	.161
240	mobilenet_v2_0.5_192-tf	.161
241	resnet50_simclr	.158
242	shufflenet_v2_x1_0	.158
243	mobilenet_v2_0_75_160	.155
244	mobilenet_v1_1.0_192	.154
245	alexnet_early_checkpoint	.151
246	imagenet_l2_10_0	.149
247	mobilenet_v1_0.75_128	.145
248	mobilenet_v2_0.5_224-tf	.143
249	alexnet_training_seed_05	.143
250	alexnet_training_seed_01	.143
251	alexnet_training_seed_01_fov4	.143
252	alexnet_training_seed_01_fov16	.143
253	alexnet_training_seed_01_fov12	.143
254	0.5x_resnet-18_LC_w_sh_1_iter	.142
255	mobilenet_v2_0.35_160	.137
256	vgg-19-keras	.136
257	resnet50-SIN	.134
258	mobilenet_v2_0.5_96	.133
259	AlexNet_SIN_fov4	.130
260	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.128
261	texture_shape_alexnet_trained_on_SIN	.124
262	mobilenet_v2_0.75_192-tf	.124
263	AdvProp_efficientnet-b0	.118
264	resnet50_imagenet_100_seed-0	.118
265	mobilenet_v1_0.75_192	.116
266	AlexNet_SIN	.115
267	mobilenet_v2_0.75_224-tf	.114
268	mobilenet_v2_0.5_160	.114
269	mobilenet_v1_0.25_160	.112
270	mobilenet_v2_0_75_192	.110
271	mobilenet_v2_0.35_128	.109
272	mobilenet_v2_0_75_224	.107
273	mobilenet_v2_0.75_128	.105
274	mobilenet_v2_1_0_128	.105
275	mobilenet_v2_0.35_96	.104
276	mobilenet_v1_0.75_160	.100
277	alexnet_training_seed_06	.098
278	mobilenet_v1_1.0_160	.098
279	mobilenet_v1_0.5_192	.096
280	mobilenet_v2_1.0_96	.089
281	mobilenet_v2_1.0_128-tf	.088
282	mobilenet_v2_0.75_160-tf	.086
283	mobilenet_v1_0.5_224	.086
284	mobilenet_v1_0.25_192	.086
285	mobilenet_v2_0.35_192	.078
286	squeezenet1_1	.075
287	mobilenet_v1_1.0_128	.071
288	my-model	.065
289	mobilenet_v2_0.75_96	.065
290	resnet_50_v1_spiking_l4a	.061
291	mobilenet_v2_0.35_224	.061
292	squeezenet1_0	.058
293	resnet50-simclr-vissl	.058
294	resnet50-vicregl0p9	.057
295	AlexNet_SIN_fov12	.053
296	mobilevit_small	.052
297	alexnet_training_seed_02	.049
298	alexnet_training_seed_04	.049
299	alexnet_training_seed_08	.049
300	alexnet_training_seed_10	.049
301	resnet50-vicregl0p75	.048
302	mobilenet_v1_0.25_128	.046
303	resnet50-meshes-lt-100-original-scratch	.043
304	mobilenet_v2_0.5_128	.042
305	resnet-50_untrained	.041
306	mobilenet_v1_0.5_160	.040
307	mobilenet_v1_0.25_224	.039
308	convnext_small_imagenet_1_seed-0	.032
309	alexnet_training_seed_03	.030
310	resnet50-meshes-lt-100-original-pretrained	.030
311	resnet_50_v1_spiking_l3	.026
312	resnet50_FractalDB	.024
313	alexnet_training_seed_07	.024
314	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.024
315	resnet_50_v1_spiking_l4	.020
316	alexnet_training_seed_09	.013
317	resnet50_imagenet_1_seed-0	.010
318	mobilenet_v1_0.5_128	.007
319	artResNet18_1	.006
320	AlexNet_SIN_fov16	.003
321	barlow-twins-resnet50	.002
322	resnet-18-LC_w_sh_100_iter_conv_init_m
323	ViT-B/32
324	BiT-M-R50x3
325	BiT-M-R50x1
326	BiT-M-R152x2
327	resnet-18-LC_w_sh_1_iter_conv_init_m
328	resnet-18-LC_w_sh_10_iter_m
329	resnet-18-LC_w_sh_100_iter_m
330	resnet-18-LC_w_sh_1_iter_m
331	resnet-18-LC_w_sh_10_iter_conv_init_m
332	FrankRobWobv0
333	resnet18-local_aggregation
334	0.5x_resnet-18_LC
335	CORnetZ_CIFAR10
336	resnet18-deepcluster
337	r3m_resnet18
338	CORnet-Z
339	resnet18-instance_recognition
340	my-model
341	vggface
342	0.5x_resnet-18_LC_w_sh_10_iter
343	resnet18-colorization
344	r3m_resnet50
345	r3m_resnet34
346	resnet-18-LC_m
347	r3m_resnet50_nocrop
348	resnet18-supervised
349	resnet-18-LC_1st_conv_m
350	resnet-18-LC_conv_init_m
351	resnet18-contrastive_multiview
352	0.5x_resnet-18
353	RN50
354	0.5x_resnet-18_LC_w_sh_100_iter
355	RN50
356	resnet18-relative_position
357	resnet18-autoencoder
358	resnet18-simclr
359	ViT_L_32
360	ViT_B_32
361	resnet18-depth_prediction
362	ViT_B_16
363	r3m_resnet34_nocrop
364	resnet18-contrastive_predictive
365	omnivore_swinT
366	resnet-18-LC_untrained
367	resnet-18_untrained
368	resnet-50x2_untrained
369	dcgan
370	v1-pyr-nodown
371	unet_entire
372	yudixie_resnet50_imagenet1kpret_0_240908
373	CORnetZ_CIFAR10_bs32_20_04
374	pixels
375	dorinet_cornet_z
376	resnet50
377	openclip
378	resnet50-cifar
379	resnet50_pretrained_with_retinal_waves
380	resnet50_ImageNet
381	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
382	yudixie_resnet50_random_0_240908
383	yudixie_resnet50_cat_obj_class_all_latents_0_240908
384	yudixie_resnet50_imagenet1kpret_0_240312
385	yudixie_resnet50_object_class_0_240908
386	yudixie_resnet50_category_class_0_240908
387	resnet18_imagenet21kP
388	yudixie_resnet50_distance_reg_0_240908
389	ConvLSTM
390	PredRNN
391	SimVP
392	TAU
393	MIM
394	hmax
395	ReAlnet01_cornet
396	briaai_rmbg_1_4
397	vit_base_patch16_dinov3-lvd1689m
398	yolos_tiny
399	yudixie_resnet18_translation_reg_0_240719
400	compact_resnet50_V4
401	yudixie_resnet18_distance_reg_0_240719
402	ReAlnet03_cornet
403	yudixie_resnet18_rotation_reg_0_240719
404	yudixie_resnet18_imagenet1kpret_0_240719
405	ReAlnet02_cornet
406	eBarlow_lmda_02_1000ep
407	resnet18_ecoset_full
408	vit_base_patch14_dinov2-lvd142m
409	compact_resnet50_IT
410	VOneCORnet-S
411	resnet50_ecoset_full
412	ReAlnet01_cornet_fov4
413	vit_base_patch14_reg4_dinov2-lvd142m
414	yudixie_resnet50_distance_rotation_0_240908
415	compact_resnet50_robust_V4
416	aughost_fair_resnet18
417	yudixie_resnet50_rotation_reg_0_240908
418	resnet152_ecoset_full
419	yudixie_resnet50_distance_translation_0_240908
420	yudixie_resnet18_distance_translation_0_240719
421	ReAlnet01_cornet_fov12
422	yudixie_resnet18_translation_rotation_0_240719
423	yudixie_resnet18_distance_rotation_0_240719
424	compact_vgg19_V4
425	yudixie_resnet18_category_class_0_240719
426	ReAlnet05_cornet
427	resnet-18_test_m
428	yudixie_resnet18_cat_obj_class_all_latents_0_240719
429	yudixie_resnet18_distance_translation_rotation_0_240719
430	yudixie_resnet18_object_class_0_240719
431	SeLaVi-AVE
432	ReAlnet06_cornet
433	compact_vgg19_IT
434	r3d_18
435	ReAlnet01_cornet_fov16
436	yudixie_resnet50_translation_reg_0_240908
437	yudixie_resnet50_translation_rotation_0_240908
438	ReAlnet01_ALL
439	ReAlnet07_cornet
440	mc3_18
441	s3d
442	mvit_v1_b
443	ReAlnet08_cornet
444	ReAlnet02_ALL
445	ReAlnet03_ALL
446	compact_cornets_V4
447	ReAlnet04_ALL
448	omnivore_swinB
449	SeLaVi-Kinetics400
450	SeLaVi-VGG-Sound
451	compact_cornets_IT
452	ReAlnet05_ALL
453	SeLaVi-Kinetics-Sound
454	ReAlnet06_ALL
455	omnivore_swinS
456	r2plus1d_18
457	ReAlnet10_cornet
458	mvit_v2_s
459	ReAlnet07_ALL
460	compact_resnet50_robust_IT
461	resnet101_ecoset_full
462	resnet34_ecoset_full
463	yudixie_resnet50_distance_translation_rotation_0_240908
464	ReAlnet08_ALL
465	yudixie_resnet18_random_0_240719
466	ReAlnet04_cornet
467	ReAlnet09_ALL
468	ReAlnet09_cornet
469	resnet50_primary_visual_cortex
470	ReAlnet10_ALL
471	resnet18_fair
472	predictive_coding_pc
473	yudixie_wbh_object_class_scaling_0415_run_0
474	yudixie_wbh_object_class_scaling_0415_run_3
475	yudixie_wbh_object_class_scaling_0415_imagenet
476	yudixie_wbh_object_class_scaling_0415_run_2
477	yudixie_wbh_object_class_scaling_0415_run_1
478	deepeisnn_ei_cifar10_vgg19
479	deepeisnn_ei_cifar10_resnet18
480	deepeisnn_ei_imagenet_resnet18

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

0.45.

Note that scores are relative to this ceiling.

Data: Geirhos2021eidolonII

Metric: error_consistency