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	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.569
15	resnext101_32x8d_wsl	.567
16	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.564
17	cvt_cvt-13-224-in1k_4_LucyV4	.561
18	effnetv2m_custom384	.558
19	convnext_xlarge:fb_in22k_ft_in1k	.556
20	AdvProp_efficientnet-b6	.556
21	convnext_small_imagenet_full_seed-0	.554
22	SWSL_resnext101_32x8d	.551
23	focalnet_tiny_lrf_in1k	.550
24	resnet_101_v2	.548
25	convnext_small_imagenet_100_seed-0	.546
26	resnet_50_v2	.541
27	pnasnet_large-tf	.535
28	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.535
29	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.535
30	convnext_tiny_imagenet_full_seed-0	.521
31	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.518
32	resnet101	.517
33	convnext_base:clip_laiona_augreg_ft_in1k_384	.511
34	convnext_base_fb_in1k	.507
35	AdvProp_efficientnet-b7	.505
36	convnext_large:fb_in22k_ft_in1k	.502
37	ViT_B_32_imagenet1k	.502
38	pnasnet_large_halfPrecision	.501
39	pnasnet_large	.501
40	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.500
41	effnetb1_272x240	.495
42	cvt_cvt-13-384-in1k_4_LucyV4	.494
43	resnet50_st_wzc_noseed_2_323	.493
44	nasnet_large	.490
45	resnet_152_v2	.489
46	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.489
47	resnet50_ewconplus_noseed_2_323	.488
48	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.484
49	resnet50_st_wzc_seed4_2_323	.481
50	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.480
51	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.477
52	resnet-152_v2_pytorch	.476
53	resnet152_imagenet_full	.474
54	efficientnet-b7	.473
55	vit_relpos_base_patch16_clsgap_224:sw_in1k	.473
56	antialias-resnet152	.470
57	inception_v4	.469
58	resnet50_st_wzc_seed3_2_323	.468
59	AT_efficientnet-b2	.468
60	AdvProp_efficientnet-b2	.468
61	convnext_tiny:in12k_ft_in1k	.468
62	resnet_101_v1	.465
63	vit_large_patch14_clip_224:laion2b_ft_in1k	.464
64	CLIP-RN50	.464
65	resnet50_ewconplus_wzc_2_323	.463
66	resnet-152_v2-tf	.459
67	resnet50_st_wzc_seed6_2_323	.453
68	convnext_large_imagenet_full_seed-0	.453
69	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.453
70	vit_large_patch14_clip_336:laion2b_ft_in1k	.451
71	resnet50_st_wzc_seed5_2_323	.447
72	inception_v4-tf	.445
73	efficientnet_b0	.444
74	nasnet_large-tf	.443
75	CLIP_ViT-B_32	.442
76	deit_base_imagenet_full_seed-0	.441
77	deit_large_imagenet_full_seed-0	.439
78	vit_large_patch14_clip_224:openai_ft_in1k	.438
79	antialiased-rnext101_32x8d	.437
80	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.433
81	resnet_152_v1	.433
82	cvt_cvt-21-384-in1k_4_LucyV4	.432
83	vit_base_patch16_clip_224:openai_ft_in1k	.432
84	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.429
85	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.427
86	convnext_femto_ols:d1_in1k	.424
87	BiT-S-R50x3	.423
88	resnet50_ewconplus_wzc_seed5_2__323	.420
89	resnet50_ewconplus_wzc_seed3_2_323	.418
90	convnext_base_imagenet_full_seed-0	.418
91	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.416
92	deit_small_imagenet_full_seed-0	.415
93	CLIP_resnet50	.415
94	CLIP_resnet50_float32	.415
95	xception	.412
96	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.412
97	cv_18_dagger_408_pretrained	.400
98	resnet50_ewconplus_wzc_seed6_2_323	.399
99	grcnn_109	.397
100	inception_v3-tf	.395
101	resnet34_imagenet_full	.393
102	voneresnet-50-non_stochastic	.391
103	inception_v3	.388
104	Res2Net50_26w_4s	.383
105	grcnn	.380
106	tv_efficientnet-b1	.379
107	resnet101_imagenet_full	.377
108	densenet-121	.373
109	resnet50_ewconplus_wzc_seed2_2__323	.371
110	xception-keras	.369
111	resnet50_linf_4_robust	.368
112	cvt_cvt-21-224-in1k_4_LucyV4	.366
113	resnet-152_v1-tf	.364
114	resnet50_ewconplus_wzc	.363
115	densenet-201	.360
116	densenet_201_pytorch	.360
117	resnet50_ewconplus_wzc_seed4_2_323	.358
118	densenet-121-keras	.357
119	resnet50-SIN_IN	.356
120	densenet-201-keras	.353
121	efficientnet_b2_imagenet_full	.353
122	vonegrcnn_52e_full	.352
123	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.350
124	resnet50	.346
125	resnet-50_v2-tf	.343
126	resnet50-moclr8deg	.340
127	vonegrcnn_62e_nobn	.334
128	pnasnet_large_pytorch	.333
129	vonegrcnn_47e	.327
130	custom_model_cv_18_dagger_408	.324
131	blt_vs	.320
132	BiT-S-R152x2	.320
133	AdvProp_efficientnet-b8	.319
134	resnet50_random_linf8_perturb	.319
135	resnet50-VITO-8deg-cc	.319
136	resnet50_imagenet_full	.318
137	ReAlnet02	.317
138	resnet-50_v1-tf	.316
139	BiT-S-R101x3	.315
140	densenet-169	.314
141	resnet50-SIN_IN_IN	.313
142	resnet_SIN_IN_FT_IN	.313
143	nasnet_mobile	.312
144	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.309
145	resnet50_st_wzc_2	.305
146	vonegrcnn_62e_nobn	.304
147	vonegrcnn_52e_full	.302
148	inception_v2-tf	.302
149	mobilenet_v2_1-4_224_pytorch	.299
150	mobilenet_v2_1_4_224	.299
151	densenet-169-keras	.297
152	ReAlnet05	.297
153	alexnet_fov4	.296
154	texture_shape_resnet50_trained_on_SIN	.295
155	resnet_50_v1_spiking	.295
156	vonegrcnn_47e	.294
157	vgg_19	.294
158	resnet-101_v1-tf	.292
159	ReAlnet06	.292
160	resnet-50-pytorch	.291
161	resnet50-sup	.291
162	resnet50_tutorial	.291
163	resnet_50_v1	.291
164	antialiased-r50	.290
165	ReAlnet10	.290
166	BiT-S-R152x4	.287
167	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.286
168	resnet50_random_l2_perturb	.286
169	ReAlnet04	.285
170	voneresnet-50	.284
171	voneresnet-50-robust	.284
172	mobilenet_v2_1_0_160	.283
173	resnet50_moco_v2	.282
174	ReAlnet07	.281
175	inception_v1	.278
176	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.277
177	CORnet-S	.276
178	ReAlnet08	.274
179	ReAlnet01	.273
180	resnet50_l2_3_robust	.273
181	mobilenet_v2_1.4_224-tf	.272
182	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
183	ReAlnet03	.267
184	cornet_s	.263
185	mobilenet_v2_1_3_224	.262
186	convnext_base_fb_in1k_gram_aligned_dinov3	.261
187	mobilenet_v2_1_0_224	.258
188	resnet50_linf_8_robust	.257
189	resnet50-SIN	.256
190	resnet50_byol	.255
191	AlexNet_SIN_fov4	.252
192	mobilenet_v2_1.0_192-tf	.252
193	mobilenet_v2_1.0_224-tf	.251
194	inception_v1-tf	.250
195	resnet18_imagenet_full	.247
196	mobilenet_v2_1_0_192	.245
197	resnet-34	.245
198	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.244
199	vgg_16	.242
200	BiT-S-R50x1	.241
201	mobilenet_v2_1.3_224-tf	.240
202	efficientnet_b1_imagenet_full	.238
203	resnet50_robust_l2_eps1	.233
204	mobilenet_v2_1.0_160-tf	.231
205	eBarlow_lmda_02_1000ep	.230
206	alexnet_random_linf8_perturb	.228
207	ReAlnet09	.226
208	efficientnet_b0_imagenet_full	.221
209	mobilenet_v1_0.75_224	.220
210	resnet-50-robust	.219
211	imagenet_l2_3_0	.219
212	resnet50_robust_l2_eps3	.219
213	resnet-18	.215
214	mobilenet_v1_1.0_224	.214
215	mobilenet_v2_0_5_224	.213
216	resnet50-vitoimagevidnet8	.212
217	regnet_y_400mf	.203
218	vonealexnet_gaussian_noise_std4_fixed	.200
219	mobilenet_v2_0.75_128	.196
220	alexnet_random_l2_3_perturb	.190
221	mobilenet_v2_0_75_160	.189
222	alexnet_reduced_aliasing_early_checkpoint	.174
223	mobilenet_v2_0.5_192-tf	.173
224	mobilenet_v2_0.75_160-tf	.171
225	shufflenet_v2_x1_0	.168
226	nasnet_mobile-tf	.168
227	alexnet_ks_torevert	.167
228	alexnet	.167
229	resnet50_simclr	.162
230	mobilenet_v1_0.75_192	.161
231	mobilenet_v2_1_0_128	.157
232	deit_small_imagenet_100_seed-0	.154
233	BiT-S-R101x1	.154
234	vgg-19-keras	.151
235	AdvProp_efficientnet-b0	.151
236	alexnet_robust_correct	.146
237	mobilenet_v1_1.0_192	.145
238	mobilenet_v1_0.75_160	.142
239	convnext_tiny_sup	.138
240	mobilenet_v2_0_5_192	.137
241	mobilenet_v2_0.35_192	.136
242	alexnet_fov16	.135
243	alexnet_l2_3_robust	.132
244	vgg-16-keras	.130
245	resnet50-barlow	.129
246	alexnet_training_seed_05	.129
247	alexnet_training_seed_01	.129
248	alexnet_training_seed_01_fov4	.129
249	alexnet_training_seed_01_fov12	.129
250	alexnet_training_seed_01_fov16	.129
251	alexnet_linf_8_robust	.127
252	resnet50-meshes-lt-100-original-scratch	.126
253	mobilenet_v2_0_75_192	.125
254	alexnet_early_checkpoint	.124
255	mobilenet_v2_0.35_96	.124
256	mobilenet_v1_1.0_128	.124
257	mobilenet_v1_1.0_160	.123
258	resnet50_eMMCR_Vanilla	.123
259	0.5x_resnet-18_LC_w_sh_1_iter	.121
260	resnet50-simclr-vissl	.121
261	mobilenet_v1_0.5_224	.117
262	mobilenet_v2_0_75_224	.113
263	resnet50_imagenet_10_seed-0	.112
264	deit_small_imagenet_10_seed-0	.112
265	deit_small_imagenet_1_seed-0	.112
266	alexnet_fov12	.112
267	mobilenet_v1_0.5_128	.112
268	mobilenet_v1_0.5_192	.108
269	squeezenet1_1	.105
270	konkle_alexnetgn_ipcl_ref01_primary_model	.105
271	mobilenet_v1_0.75_128	.104
272	resnet50-vicreg	.103
273	mobilenet_v2_1.0_128-tf	.101
274	resnet50_imagenet_100_seed-0	.099
275	mobilenet_v2_0.5_96	.097
276	mobilenet_v2_0.5_160	.096
277	mobilenet_v2_0.35_224	.095
278	mobilenet_v2_1.0_96	.094
279	AlexNet_SIN	.093
280	mobilenet_v1_0.25_224	.093
281	mobilenet_v2_0.75_96	.093
282	mobilenet_v1_0.5_160	.091
283	convnext_small_imagenet_10_seed-0	.091
284	mobilenet_v2_0.75_192-tf	.090
285	mobilenet_v2_0.75_224-tf	.090
286	imagenet_l2_10_0	.089
287	resnet_50_v1_spiking_l4a	.089
288	mobilenet_v2_0.35_128	.085
289	mobilenet_v1_0.25_160	.081
290	mobilenet_v2_0.5_224-tf	.080
291	mobilenet_v2_0.35_160	.079
292	texture_shape_alexnet_trained_on_SIN	.078
293	alexnet_training_seed_06	.076
294	squeezenet1_0	.071
295	mobilenet_v1_0.25_192	.069
296	resnet50-vicregl0p75	.063
297	resnet_50_v1_spiking_l4	.062
298	resnet_50_v1_spiking_l3	.057
299	mobilenet_v2_0.5_128	.056
300	AlexNet_SIN_fov12	.042
301	my-model	.040
302	resnet50-meshes-lt-100-original-pretrained	.039
303	alexnet_training_seed_02	.037
304	alexnet_training_seed_04	.037
305	alexnet_training_seed_08	.037
306	alexnet_training_seed_10	.037
307	artResNet18_1	.037
308	resnet50-vicregl0p9	.036
309	alexnet_training_seed_09	.034
310	mobilenet_v1_0.25_128	.033
311	alexnet_training_seed_07	.033
312	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.028
313	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.026
314	resnet50_FractalDB	.023
315	resnet-50_untrained	.018
316	AlexNet_SIN_fov16	.010
317	resnet50_imagenet_1_seed-0	.010
318	convnext_small_imagenet_1_seed-0	.007
319	barlow-twins-resnet50	.003
320	alexnet_training_seed_03	.001
321	mobilevit_small	.000
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_test_m
330	resnet-18-LC_w_sh_100_iter_m
331	resnet-18-LC_w_sh_1_iter_m
332	resnet-18-LC_w_sh_10_iter_conv_init_m
333	FrankRobWobv0
334	0.5x_resnet-18_LC
335	CORnetZ_CIFAR10
336	resnet18-local_aggregation
337	resnet18-deepcluster
338	r3m_resnet18
339	CORnet-Z
340	resnet18-instance_recognition
341	my-model
342	vggface
343	0.5x_resnet-18_LC_w_sh_10_iter
344	resnet18-colorization
345	r3m_resnet50
346	r3m_resnet34
347	resnet-18-LC_m
348	r3m_resnet50_nocrop
349	resnet18-supervised
350	resnet-18-LC_1st_conv_m
351	resnet-18-LC_conv_init_m
352	resnet18-contrastive_multiview
353	0.5x_resnet-18
354	RN50
355	0.5x_resnet-18_LC_w_sh_100_iter
356	RN50
357	resnet18-relative_position
358	resnet18-autoencoder
359	resnet18-simclr
360	ViT_L_32
361	ViT_B_32
362	yudixie_resnet50_random_0_240908
363	resnet18-depth_prediction
364	ViT_B_16
365	r3m_resnet34_nocrop
366	resnet18-contrastive_predictive
367	omnivore_swinT
368	resnet-18-LC_untrained
369	resnet-18_untrained
370	resnet-50x2_untrained
371	dcgan
372	v1-pyr-nodown
373	unet_entire
374	CORnetZ_CIFAR10_bs32_20_04
375	pixels
376	dorinet_cornet_z
377	resnet50
378	openclip
379	resnet50-cifar
380	resnet50_pretrained_with_retinal_waves
381	resnet50_ImageNet
382	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
383	yudixie_resnet50_imagenet1kpret_0_240908
384	yudixie_resnet50_imagenet1kpret_0_240312
385	yudixie_resnet50_object_class_0_240908
386	yudixie_resnet50_cat_obj_class_all_latents_0_240908
387	yudixie_resnet50_category_class_0_240908
388	inception_v3_pytorch
389	resnet18_imagenet21kP
390	yudixie_resnet50_distance_reg_0_240908
391	ConvLSTM
392	PredRNN
393	TAU
394	MIM
395	hmax
396	briaai_rmbg_1_4
397	ReAlnet01_cornet
398	vit_base_patch16_dinov3-lvd1689m
399	ReAlnet02_cornet
400	yudixie_resnet18_distance_reg_0_240719
401	compact_resnet50_V4
402	yudixie_resnet18_rotation_reg_0_240719
403	ReAlnet03_cornet
404	vit_base_patch14_dinov2-lvd142m
405	resnet34_ecoset_full
406	VOneCORnet-S
407	resnet50_ecoset_full
408	ReAlnet01_cornet_fov4
409	vit_base_patch14_reg4_dinov2-lvd142m
410	yudixie_resnet50_distance_translation_0_240908
411	compact_resnet50_robust_V4
412	yudixie_resnet18_distance_translation_0_240719
413	aughost_fair_resnet18
414	yudixie_resnet18_translation_rotation_0_240719
415	compact_resnet50_IT
416	yudixie_resnet18_cat_obj_class_all_latents_0_240719
417	ReAlnet05_cornet
418	yudixie_resnet18_translation_reg_0_240719
419	ReAlnet01_cornet_fov12
420	yudixie_resnet50_rotation_reg_0_240908
421	yudixie_resnet18_distance_translation_rotation_0_240719
422	yudixie_resnet18_object_class_0_240719
423	SeLaVi-AVE
424	yudixie_resnet18_imagenet1kpret_0_240719
425	r3d_18
426	compact_vgg19_V4
427	yudixie_resnet50_translation_reg_0_240908
428	ReAlnet06_cornet
429	ReAlnet01_cornet_fov16
430	compact_vgg19_IT
431	yudixie_resnet50_translation_rotation_0_240908
432	mc3_18
433	ReAlnet01_ALL
434	ReAlnet07_cornet
435	s3d
436	mvit_v1_b
437	ReAlnet08_cornet
438	ReAlnet02_ALL
439	compact_cornets_V4
440	omnivore_swinB
441	ReAlnet04_ALL
442	SeLaVi-Kinetics400
443	ReAlnet09_cornet
444	SeLaVi-VGG-Sound
445	compact_cornets_IT
446	ReAlnet05_ALL
447	SeLaVi-Kinetics-Sound
448	omnivore_swinS
449	resnet152_ecoset_full
450	ReAlnet06_ALL
451	r2plus1d_18
452	mvit_v2_s
453	compact_resnet50_robust_IT
454	ReAlnet10_cornet
455	ReAlnet07_ALL
456	resnet18_ecoset_full
457	resnet101_ecoset_full
458	yudixie_resnet18_category_class_0_240719
459	yudixie_resnet50_distance_translation_rotation_0_240908
460	ReAlnet08_ALL
461	yudixie_resnet18_random_0_240719
462	yudixie_resnet18_distance_rotation_0_240719
463	yudixie_resnet50_distance_rotation_0_240908
464	ReAlnet04_cornet
465	ReAlnet09_ALL
466	resnet50_primary_visual_cortex
467	yolos_tiny
468	ReAlnet10_ALL
469	ReAlnet03_ALL
470	resnet18_fair
471	pr1_stl10_disentangled_alpha04
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

0.46.

Note that scores are relative to this ceiling.

Data: Geirhos2021eidolonIII

Metric: error_consistency