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("Geirhos2021lowpass-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	.730
2	resnext101_32x32d_wsl	.695
3	convnext_xxlarge_clip	.695
4	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
5	convnext_large:fb_in22k_ft_in1k	.667
6	vit_large_patch14_clip_224:openai_ft_in1k	.663
7	deit3_base_patch16_224_fb_in22k_ft_in1k	.655
8	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.648
9	fixres_resnext101_32x48d_wsl	.630
10	resnet50-VITO-8deg-cc	.625
11	vit_large_patch14_clip_336:laion2b_ft_in1k	.623
12	SWSL_resnet50	.613
13	vit_large_patch14_clip_224:laion2b_ft_in1k	.603
14	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.602
15	deit3_base_patch16_224_fb_in1k	.601
16	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.600
17	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.589
18	vit_large_clip336_openai	.588
19	resnext101_32x48d_wsl	.579
20	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.578
21	convnext_large_in22k_supervised	.568
22	resnext101_32x8d_wsl	.563
23	convnext_base_fb_in22k_ft_in1k	.559
24	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.554
25	dinov2_vitg14_lc	.553
26	CLIP_resnet50	.544
27	CLIP_resnet50_float32	.544
28	deit_large_imagenet_full_seed-0	.543
29	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.537
30	resnext101_32x16d_wsl	.535
31	vit_base_patch16_clip_224:openai_ft_in1k	.535
32	convnext_large_clip_laion2b_finelayers	.530
33	convnext_xlarge:fb_in22k_ft_in1k	.527
34	effnetv2m_custom384	.527
35	dinov2_vitl14_lc	.520
36	convnext_base:clip_laiona_augreg_ft_in1k_384	.516
37	dinov2_vitl14_reg_lc	.505
38	eva02_large_in22k	.504
39	vision_transformer_vit_large_patch16_224	.499
40	resnet_152_v2	.498
41	effnetb1_272x240	.497
42	CLIP_ViT-B_32	.496
43	cvt_cvt-13-384-in1k_4_LucyV4	.492
44	vit_huge_clip336_laion	.483
45	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.478
46	convnext_large_imagenet_full_seed-0	.471
47	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.463
48	vit_relpos_base_patch16_clsgap_224:sw_in1k	.463
49	deit_small_imagenet_full_seed-0	.460
50	deit_base_imagenet_full_seed-0	.460
51	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.454
52	focalnet_tiny_lrf_in1k	.436
53	convnext_tiny:in12k_ft_in1k	.435
54	CLIP-RN50	.419
55	convnext_tiny_imagenet_full_seed-0	.419
56	resnet_50_v2	.415
57	pnasnet_large_halfPrecision	.410
58	pnasnet_large	.410
59	ViT_B_16_imagenet1k	.409
60	ViT_L_32_imagenet1k	.406
61	inception_v4	.400
62	resnet_101_v2	.397
63	nasnet_large	.396
64	cvt_cvt-21-384-in1k_4_LucyV4	.391
65	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.385
66	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.382
67	convnext_small_imagenet_full_seed-0	.379
68	convnext_femto_ols:d1_in1k	.379
69	resnet-152_v2_pytorch	.371
70	dinov2_vitl14_lc_res336	.370
71	cvt_cvt-21-224-in1k_4_LucyV4	.368
72	convnext_base_fb_in1k	.366
73	resnet50_st_wzc_seed6_2_323	.365
74	cvt_cvt-13-224-in1k_4_LucyV4	.361
75	dinov2_vitg14_reg_lc	.361
76	convnext_base_imagenet_full_seed-0	.354
77	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.352
78	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.338
79	pnasnet_large-tf	.338
80	antialias-resnet152	.326
81	xception-keras	.317
82	cv_18_dagger_408_pretrained	.314
83	resnet101	.313
84	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.311
85	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.306
86	nasnet_large-tf	.305
87	inception_v3-tf	.299
88	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.297
89	inception_v4-tf	.295
90	resnet152_imagenet_full	.290
91	resnet-152_v2-tf	.285
92	resnet50_byol	.274
93	resnet_152_v1	.270
94	resnet_101_v1	.268
95	antialiased-rnext101_32x8d	.268
96	inception_v3	.260
97	convnext_tiny_sup	.260
98	resnet50_ewconplus_wzc_seed5_2__323	.259
99	AdvProp_efficientnet-b4	.258
100	AT_efficientnet-b4	.258
101	grcnn_109	.252
102	inception_v3_pytorch	.252
103	resnet50	.251
104	resnet50_st_wzc_seed3_2_323	.247
105	ViT_B_32_imagenet1k	.244
106	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.243
107	resnet50_ewconplus_wzc_seed2_2__323	.238
108	resnet50_moco_v2	.232
109	convnext_base_fb_in1k_gram_aligned_dinov3	.230
110	resnet50_ewconplus_wzc	.230
111	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.225
112	AdvProp_efficientnet-b6	.221
113	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.218
114	tv_efficientnet-b1	.215
115	densenet-121-keras	.214
116	antialiased-r50	.214
117	resnet50_imagenet_full	.213
118	voneresnet-50-non_stochastic	.209
119	convnext_small_imagenet_100_seed-0	.207
120	densenet-169-keras	.203
121	AdvProp_efficientnet-b7	.203
122	resnet34_imagenet_full	.203
123	resnet-50_v2-tf	.202
124	densenet-121	.201
125	resnet50_st_wzc_2	.197
126	densenet-201-keras	.197
127	grcnn	.194
128	resnet_50_v1_spiking	.190
129	resnet50-moclr8deg	.187
130	densenet-169	.186
131	mobilenet_v2_1_0_224	.186
132	resnet50_tutorial	.185
133	resnet_50_v1	.185
134	resnet-50-pytorch	.185
135	resnet50-sup	.185
136	efficientnet-b7	.185
137	vgg_19	.184
138	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.180
139	resnet50_hvs_wzc	.179
140	BiT-S-R152x4	.175
141	pnasnet_large_pytorch	.175
142	Res2Net50_26w_4s	.174
143	resnet50_ewconplus_wzc_seed6_2_323	.169
144	xception	.168
145	resnet-50_v1-tf	.167
146	resnet101_imagenet_full	.165
147	AT_efficientnet-b2	.165
148	AdvProp_efficientnet-b2	.165
149	resnet18_imagenet_full	.163
150	densenet-201	.161
151	densenet_201_pytorch	.161
152	ReAlnet04	.156
153	custom_model_cv_18_dagger_408	.156
154	resnet-101_v1-tf	.155
155	vonegrcnn_62e_nobn	.153
156	efficientnet_b1_imagenet_full	.153
157	efficientnet_b0	.152
158	eBarlow_lmda_02_1000ep	.147
159	inception_v1-tf	.144
160	deit_small_imagenet_100_seed-0	.143
161	vonegrcnn_47e	.141
162	efficientnet_b2_imagenet_full	.140
163	resnet50_random_linf8_perturb	.140
164	vonegrcnn_52e_full	.139
165	resnet-152_v1-tf	.138
166	mobilenet_v2_1.0_224-tf	.135
167	ReAlnet03	.135
168	nasnet_mobile	.133
169	mobilenet_v2_1.4_224-tf	.133
170	voneresnet-50	.132
171	ReAlnet09	.132
172	vonegrcnn_62e_nobn	.130
173	resnet50-SIN_IN	.129
174	BiT-S-R50x3	.129
175	blt_vs	.129
176	mobilenet_v2_1_0_192	.127
177	BiT-S-R101x3	.127
178	ReAlnet07	.127
179	vonegrcnn_52e_full	.126
180	vonegrcnn_47e	.126
181	ReAlnet08	.126
182	resnet50_random_l2_perturb	.126
183	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.125
184	inception_v2-tf	.124
185	cornet_s	.124
186	AdvProp_efficientnet-b8	.123
187	mobilenet_v2_1-4_224_pytorch	.122
188	mobilenet_v2_1_4_224	.122
189	ReAlnet02	.121
190	voneresnet-50-robust	.119
191	mobilenet_v2_0_5_192	.116
192	ReAlnet06	.115
193	nasnet_mobile-tf	.113
194	resnet50-vitoimagevidnet8	.113
195	mobilenet_v1_0.75_224	.112
196	ReAlnet10	.112
197	mobilenet_v2_0_5_224	.111
198	vgg-19-keras	.111
199	resnet50_l2_3_robust	.110
200	resnet50_linf_4_robust	.110
201	inception_v1	.109
202	resnet50-SIN_IN_IN	.109
203	resnet_SIN_IN_FT_IN	.109
204	mobilenet_v2_1.0_160-tf	.109
205	resnet_50_v1_spiking_l4a	.108
206	mobilenet_v2_1_0_160	.108
207	resnet50_linf_8_robust	.107
208	resnet-50-robust	.103
209	imagenet_l2_3_0	.103
210	resnet50_robust_l2_eps3	.103
211	vgg_16	.100
212	ReAlnet01	.100
213	BiT-S-R50x1	.100
214	CORnet-S	.097
215	vgg-16-keras	.097
216	efficientnet_b0_imagenet_full	.096
217	mobilenet_v2_1_3_224	.096
218	mobilenet_v2_0.5_192-tf	.096
219	mobilenet_v2_0.75_192-tf	.095
220	mobilenet_v1_1.0_160	.095
221	ReAlnet05	.094
222	alexnet_fov4	.092
223	mobilenet_v2_1.3_224-tf	.091
224	resnet50_eMMCR_Vanilla	.090
225	regnet_y_400mf	.087
226	imagenet_l2_10_0	.086
227	mobilenet_v2_1.0_192-tf	.085
228	resnet50_imagenet_10_seed-0	.085
229	deit_small_imagenet_10_seed-0	.085
230	deit_small_imagenet_1_seed-0	.085
231	mobilenet_v2_0.75_160-tf	.085
232	mobilenet_v2_0.5_224-tf	.084
233	mobilenet_v2_0_75_160	.084
234	resnet50_robust_l2_eps1	.082
235	mobilenet_v1_0.75_192	.081
236	alexnet_linf_8_robust	.081
237	resnet-18	.081
238	mobilenet_v2_0.75_96	.081
239	resnet-34	.080
240	alexnet_fov16	.080
241	convnext_small_imagenet_10_seed-0	.078
242	mobilenet_v2_1.0_96	.078
243	mobilenet_v2_0_75_192	.077
244	mobilenet_v2_0.35_224	.077
245	mobilenet_v2_0.5_96	.077
246	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
247	alexnet_training_seed_05	.074
248	alexnet_training_seed_01	.074
249	alexnet_training_seed_01_fov4	.074
250	alexnet_training_seed_01_fov12	.074
251	alexnet_training_seed_01_fov16	.074
252	mobilenet_v2_0.75_128	.072
253	texture_shape_resnet50_trained_on_SIN	.071
254	alexnet_random_l2_3_perturb	.070
255	alexnet_l2_3_robust	.070
256	mobilenet_v2_0.75_224-tf	.069
257	resnet-50_untrained	.067
258	vonealexnet_gaussian_noise_std4_fixed	.066
259	mobilenet_v2_1_0_128	.065
260	resnet50-SIN	.064
261	alexnet_reduced_aliasing_early_checkpoint	.063
262	mobilenet_v2_0.35_96	.061
263	mobilenet_v2_0_75_224	.061
264	mobilenet_v2_0.35_192	.061
265	alexnet_robust_correct	.060
266	shufflenet_v2_x1_0	.060
267	BiT-S-R152x2	.059
268	texture_shape_alexnet_trained_on_SIN	.059
269	alexnet_training_seed_03	.058
270	alexnet_training_seed_09	.057
271	squeezenet1_1	.057
272	mobilenet_v1_0.75_128	.056
273	alexnet_ks_torevert	.056
274	alexnet	.056
275	AdvProp_efficientnet-b0	.055
276	mobilenet_v1_0.5_224	.055
277	resnet50-simclr-vissl	.054
278	AlexNet_SIN	.054
279	barlow-twins-resnet50	.052
280	alexnet_random_linf8_perturb	.049
281	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.049
282	resnet50_simclr	.047
283	mobilenet_v1_1.0_224	.045
284	mobilenet_v1_1.0_192	.045
285	mobilenet_v2_0.35_128	.044
286	BiT-S-R101x1	.044
287	alexnet_early_checkpoint	.043
288	AlexNet_SIN_fov4	.040
289	resnet50-vicreg	.038
290	resnet50-vicregl0p9	.038
291	mobilenet_v2_1.0_128-tf	.037
292	alexnet_fov12	.034
293	artResNet18_1	.032
294	resnet_50_v1_spiking_l4	.032
295	alexnet_training_seed_02	.031
296	alexnet_training_seed_08	.031
297	alexnet_training_seed_04	.031
298	alexnet_training_seed_10	.031
299	mobilenet_v2_0.5_160	.030
300	AlexNet_SIN_fov16	.029
301	mobilenet_v2_0.35_160	.029
302	0.5x_resnet-18_LC_w_sh_1_iter	.028
303	mobilenet_v1_0.25_160	.026
304	resnet50_FractalDB	.026
305	resnet50_imagenet_1_seed-0	.025
306	resnet_50_v1_spiking_l3	.024
307	alexnet_training_seed_06	.024
308	mobilenet_v1_0.25_224	.022
309	mobilenet_v2_0.5_128	.020
310	mobilenet_v1_0.25_192	.019
311	mobilenet_v1_0.25_128	.017
312	mobilenet_v1_1.0_128	.016
313	squeezenet1_0	.014
314	mobilenet_v1_0.5_192	.013
315	alexnet_training_seed_07	.013
316	mobilevit_small	.013
317	mobilenet_v1_0.75_160	.013
318	konkle_alexnetgn_ipcl_ref01_primary_model	.013
319	resnet50_imagenet_100_seed-0	.007
320	mobilenet_v1_0.5_160	.006
321	resnet50-barlow	.006
322	convnext_small_imagenet_1_seed-0	.005
323	AlexNet_SIN_fov12	.004
324	mobilenet_v1_0.5_128	.003
325	resnet50-vicregl0p75	.003
326	resnet-18-LC_w_sh_100_iter_conv_init_m
327	ViT-B/32
328	BiT-M-R50x3
329	BiT-M-R50x1
330	BiT-M-R152x2
331	resnet-18-LC_w_sh_1_iter_conv_init_m
332	resnet-18-LC_w_sh_10_iter_m
333	resnet-18-LC_w_sh_100_iter_m
334	resnet-18-LC_w_sh_10_iter_conv_init_m
335	resnet-18-LC_w_sh_1_iter_m
336	FrankRobWobv0
337	0.5x_resnet-18_LC
338	CORnetZ_CIFAR10
339	resnet18-local_aggregation
340	resnet18-deepcluster
341	r3m_resnet18
342	CORnet-Z
343	resnet18-instance_recognition
344	vggface
345	my-model
346	0.5x_resnet-18_LC_w_sh_10_iter
347	r3m_resnet50
348	resnet18-colorization
349	r3m_resnet34
350	resnet-18-LC_m
351	r3m_resnet50_nocrop
352	resnet18-supervised
353	resnet-18-LC_1st_conv_m
354	resnet-18-LC_conv_init_m
355	resnet18-contrastive_multiview
356	0.5x_resnet-18
357	RN50
358	0.5x_resnet-18_LC_w_sh_100_iter
359	RN50
360	resnet18-relative_position
361	resnet18-autoencoder
362	resnet18-simclr
363	ViT_L_32
364	ViT_B_32
365	resnet18-depth_prediction
366	ViT_B_16
367	r3m_resnet34_nocrop
368	resnet18-contrastive_predictive
369	omnivore_swinT
370	resnet-18-LC_untrained
371	resnet-18_untrained
372	resnet-50x2_untrained
373	dcgan
374	unet_entire
375	v1-pyr-nodown
376	CORnetZ_CIFAR10_bs32_20_04
377	pixels
378	dorinet_cornet_z
379	my-model
380	openclip
381	resnet50-cifar
382	resnet50_pretrained_with_retinal_waves
383	resnet50_ImageNet
384	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
385	yudixie_resnet50_random_0_240908
386	yudixie_resnet50_imagenet1kpret_0_240908
387	yudixie_resnet50_cat_obj_class_all_latents_0_240908
388	yudixie_resnet50_imagenet1kpret_0_240312
389	yudixie_resnet50_category_class_0_240908
390	resnet18_imagenet21kP
391	yudixie_resnet50_distance_reg_0_240908
392	ConvLSTM
393	PredRNN
394	SimVP
395	TAU
396	MIM
397	hmax
398	ReAlnet01_cornet
399	yolos_tiny
400	resnet152_ecoset_full
401	compact_resnet50_V4
402	yudixie_resnet18_translation_reg_0_240719
403	yudixie_resnet18_distance_reg_0_240719
404	ReAlnet03_cornet
405	yudixie_resnet18_rotation_reg_0_240719
406	ReAlnet02_cornet
407	yudixie_resnet18_imagenet1kpret_0_240719
408	vit_base_patch16_dinov3-lvd1689m
409	resnet34_ecoset_full
410	compact_resnet50_IT
411	resnet50_ecoset_full
412	vit_base_patch14_dinov2-lvd142m
413	vit_base_patch14_reg4_dinov2-lvd142m
414	resnet101_ecoset_full
415	compact_resnet50_robust_V4
416	ReAlnet01_cornet_fov4
417	yudixie_resnet50_distance_translation_0_240908
418	ReAlnet01_cornet_fov12
419	omnivore_swinB
420	yudixie_resnet18_distance_rotation_0_240719
421	yudixie_resnet50_distance_rotation_0_240908
422	yudixie_resnet18_category_class_0_240719
423	yudixie_resnet18_random_0_240719
424	ReAlnet05_cornet
425	yudixie_resnet18_cat_obj_class_all_latents_0_240719
426	yudixie_resnet50_rotation_reg_0_240908
427	resnet-18_test_m
428	compact_vgg19_V4
429	yudixie_resnet18_distance_translation_rotation_0_240719
430	yudixie_resnet18_object_class_0_240719
431	SeLaVi-AVE
432	r3d_18
433	ReAlnet06_cornet
434	yudixie_resnet50_translation_reg_0_240908
435	yudixie_resnet50_translation_rotation_0_240908
436	ReAlnet01_ALL
437	mc3_18
438	ReAlnet07_cornet
439	s3d
440	mvit_v1_b
441	ReAlnet08_cornet
442	ReAlnet01_cornet_fov16
443	ReAlnet02_ALL
444	ReAlnet03_ALL
445	VOneCORnet-S
446	compact_cornets_V4
447	ReAlnet04_ALL
448	ReAlnet09_cornet
449	SeLaVi-Kinetics400
450	compact_cornets_IT
451	SeLaVi-VGG-Sound
452	ReAlnet05_ALL
453	SeLaVi-Kinetics-Sound
454	compact_vgg19_IT
455	omnivore_swinS
456	mvit_v2_s
457	compact_resnet50_robust_IT
458	ReAlnet06_ALL
459	r2plus1d_18
460	ReAlnet10_cornet
461	ReAlnet07_ALL
462	resnet18_ecoset_full
463	yudixie_resnet50_distance_translation_rotation_0_240908
464	ReAlnet08_ALL
465	yudixie_resnet18_translation_rotation_0_240719
466	yudixie_resnet18_distance_translation_0_240719
467	resnet50_primary_visual_cortex
468	ReAlnet04_cornet
469	ReAlnet09_ALL
470	yudixie_resnet50_object_class_0_240908
471	briaai_rmbg_1_4
472	ReAlnet10_ALL
473	resnet18_fair
474	predictive_coding_pc
475	yudixie_wbh_object_class_scaling_0415_run_0
476	yudixie_wbh_object_class_scaling_0415_run_3
477	yudixie_wbh_object_class_scaling_0415_imagenet
478	yudixie_wbh_object_class_scaling_0415_run_2
479	yudixie_wbh_object_class_scaling_0415_run_1
480	deepeisnn_ei_cifar10_vgg19
481	deepeisnn_ei_cifar10_resnet18
482	deepeisnn_ei_imagenet_resnet18
483	dinov2_vitl14_reg_lc_featread

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

0.47.

Note that scores are relative to this ceiling.

Data: Geirhos2021lowpass

Metric: error_consistency