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("Geirhos2021powerequalisation-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	fixres_resnext101_32x48d_wsl	.755
2	vit_large_patch14_clip_224:laion2b_ft_in1k	.718
3	cvt_cvt-13-384-in1k_4_LucyV4	.713
4	vit_large_patch14_clip_224:openai_ft_in1k	.709
5	cvt_cvt-21-384-in1k_4_LucyV4	.707
6	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.707
7	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.705
8	convnext_xlarge:fb_in22k_ft_in1k	.680
9	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.672
10	convnext_large:fb_in22k_ft_in1k	.670
11	SWSL_resnext101_32x8d	.668
12	vit_large_patch14_clip_336:laion2b_ft_in1k	.651
13	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.650
14	vit_base_patch16_clip_224:openai_ft_in1k	.647
15	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.638
16	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.633
17	resnet_152_v2	.599
18	resnext101_32x16d_wsl	.592
19	convnext_base:clip_laiona_augreg_ft_in1k_384	.586
20	resnext101_32x32d_wsl	.579
21	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.564
22	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.560
23	resnext101_32x48d_wsl	.548
24	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.540
25	effnetv2m_custom384	.501
26	resnet-152_v2_pytorch	.494
27	SWSL_resnet50	.489
28	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.486
29	convnext_base_imagenet_full_seed-0	.482
30	vision_transformer_vit_large_patch16_224	.472
31	convnext_tiny:in12k_ft_in1k	.468
32	convnext_large_imagenet_full_seed-0	.467
33	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.462
34	resnet_50_v2	.455
35	resnext101_32x8d_wsl	.453
36	resnet_101_v2	.451
37	convnext_small_imagenet_full_seed-0	.450
38	convnext_tiny_imagenet_full_seed-0	.427
39	CLIP_resnet50	.427
40	CLIP_resnet50_float32	.427
41	cvt_cvt-13-224-in1k_4_LucyV4	.397
42	cv_18_dagger_408_pretrained	.388
43	vit_relpos_base_patch16_clsgap_224:sw_in1k	.382
44	pnasnet_large	.380
45	convnext_femto_ols:d1_in1k	.378
46	nasnet_large	.363
47	ViT_B_16_imagenet1k	.339
48	resnet-152_v2-tf	.335
49	inception_v4	.323
50	focalnet_tiny_lrf_in1k	.317
51	resnet152_imagenet_full	.317
52	CLIP-RN50	.315
53	ViT_L_32_imagenet1k	.307
54	pnasnet_large-tf	.295
55	resnet50-VITO-8deg-cc	.292
56	antialias-resnet152	.289
57	effnetb1_272x240	.289
58	resnet101	.287
59	CLIP_ViT-B_32	.287
60	inception_v3	.280
61	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.278
62	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.269
63	deit_large_imagenet_full_seed-0	.269
64	resnet50_random_linf8_perturb	.260
65	resnet_152_v1	.260
66	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.257
67	nasnet_large-tf	.248
68	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.246
69	xception-keras	.245
70	inception_v3-tf	.237
71	resnet_101_v1	.234
72	cvt_cvt-21-224-in1k_4_LucyV4	.228
73	resnet50_random_l2_perturb	.227
74	inception_v3_pytorch	.222
75	resnet101_imagenet_full	.221
76	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.217
77	ViT_B_32_imagenet1k	.217
78	resnet50_imagenet_full	.216
79	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.214
80	inception_v4-tf	.209
81	grcnn_109	.201
82	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.197
83	vgg_19	.195
84	Res2Net50_26w_4s	.193
85	AdvProp_efficientnet-b7	.190
86	AdvProp_efficientnet-b4	.189
87	AT_efficientnet-b4	.189
88	AdvProp_efficientnet-b6	.187
89	AT_efficientnet-b2	.186
90	AdvProp_efficientnet-b2	.186
91	resnet50	.185
92	xception	.184
93	resnet50_linf_4_robust	.182
94	efficientnet_b0	.181
95	resnet_50_v1_spiking	.181
96	resnet50_ewconplus_wzc	.174
97	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.173
98	deit_base_imagenet_full_seed-0	.169
99	convnext_small_imagenet_100_seed-0	.167
100	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.164
101	resnet50-moclr8deg	.159
102	resnet-50_v2-tf	.155
103	antialiased-rnext101_32x8d	.149
104	densenet-121-keras	.147
105	custom_model_cv_18_dagger_408	.145
106	inception_v2-tf	.145
107	alexnet_random_linf8_perturb	.140
108	resnet50_byol	.134
109	pnasnet_large_pytorch	.133
110	resnet50-SIN_IN_IN	.132
111	resnet_SIN_IN_FT_IN	.132
112	BiT-S-R50x3	.128
113	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.127
114	antialiased-r50	.127
115	resnet34_imagenet_full	.126
116	grcnn	.125
117	densenet-201	.125
118	densenet_201_pytorch	.125
119	voneresnet-50-robust	.122
120	ReAlnet03	.121
121	densenet-121	.119
122	resnet50_linf_8_robust	.119
123	ReAlnet04	.118
124	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.116
125	ReAlnet08	.115
126	efficientnet-b7	.114
127	vgg_16	.113
128	densenet-201-keras	.112
129	voneresnet-50-non_stochastic	.108
130	resnet-50_v1-tf	.107
131	vonealexnet_gaussian_noise_std4_fixed	.105
132	ReAlnet01	.105
133	inception_v1	.100
134	alexnet_l2_3_robust	.098
135	alexnet_random_l2_3_perturb	.098
136	resnet50_tutorial	.098
137	resnet_50_v1	.098
138	resnet-50-pytorch	.098
139	resnet50-sup	.098
140	alexnet_ks_torevert	.097
141	alexnet-baseline	.097
142	alexnet	.097
143	alexnet	.097
144	alexnet	.097
145	alexnet	.097
146	alexnet	.097
147	alexnet	.097
148	alexnet	.097
149	alexnet	.097
150	alexnet	.097
151	ReAlnet05	.096
152	densenet-169	.096
153	resnet50_l2_3_robust	.095
154	resnet-152_v1-tf	.094
155	resnet50_moco_v2	.094
156	densenet-169-keras	.094
157	ReAlnet02	.093
158	ReAlnet07	.091
159	tv_efficientnet-b1	.090
160	cornet_s	.089
161	convnext_tiny_sup	.089
162	ReAlnet06	.089
163	vonegrcnn_62e_nobn	.088
164	vonegrcnn_62e_nobn	.088
165	alexnet_reduced_aliasing_early_checkpoint	.088
166	nasnet_mobile-tf	.086
167	alexnet_early_checkpoint	.085
168	deit_small_imagenet_full_seed-0	.084
169	BiT-S-R152x2	.083
170	ReAlnet10	.083
171	vonegrcnn_52e_full	.083
172	alexnet_training_seed_05	.083
173	alexnet_training_seed_01	.083
174	resnet50-vitoimagevidnet8	.082
175	alexnet	.082
176	inception_v1-tf	.078
177	barlow-twins-resnet50	.078
178	ReAlnet09	.078
179	resnet-101_v1-tf	.076
180	resnet50_robust_l2_eps1	.075
181	vonegrcnn_47e	.075
182	AdvProp_efficientnet-b8	.073
183	resnet-34	.070
184	vonegrcnn_52e_full	.070
185	squeezenet1_1	.068
186	resnet18_imagenet_full	.065
187	vonegrcnn_47e	.065
188	mobilenet_v2_1.0_160-tf	.065
189	alexnet_robust_correct	.064
190	artResNet18_1	.064
191	resnet50-SIN_IN	.063
192	resnet-50-robust	.062
193	imagenet_l2_3_0	.062
194	resnet50_robust_l2_eps3	.062
195	konkle_alexnetgn_ipcl_ref01_primary_model	.062
196	mobilenet_v2_1_0_192	.060
197	resnet50_simclr	.059
198	mobilenet_v2_1_0_160	.059
199	BiT-S-R152x4	.057
200	alexnet_training_seed_02	.053
201	alexnet_training_seed_04	.053
202	alexnet_training_seed_08	.053
203	alexnet_training_seed_10	.053
204	resnet50-meshes-lt-100-original-scratch	.053
205	vgg-19-keras	.053
206	CORnet-S	.052
207	efficientnet_b2_imagenet_full	.050
208	mobilenet_v1_0.25_128	.048
209	mobilenet_v2_1.0_224-tf	.047
210	vgg-16-keras	.047
211	mobilenet_v2_0_5_192	.046
212	voneresnet-50	.045
213	texture_shape_resnet50_trained_on_SIN	.044
214	mobilenet_v2_0.5_96	.043
215	mobilenet_v1_0.5_160	.041
216	convnext_small_imagenet_1_seed-0	.041
217	deit_small_imagenet_100_seed-0	.040
218	mobilenet_v2_1_0_224	.040
219	resnet50_imagenet_100_seed-0	.040
220	resnet50-SIN	.040
221	mobilenet_v1_0.5_128	.039
222	BiT-S-R101x3	.039
223	resnet50-barlow	.038
224	alexnet_training_seed_07	.038
225	alexnet_training_seed_09	.038
226	AdvProp_efficientnet-b0	.038
227	0.5x_resnet-18_LC_w_sh_1_iter	.038
228	BiT-S-R50x1	.037
229	mobilenet_v2_0.35_192	.037
230	texture_shape_alexnet_trained_on_SIN	.037
231	alexnet_linf_8_robust	.037
232	mobilenet_v2_1-4_224_pytorch	.036
233	mobilenet_v2_1_4_224	.036
234	resnet50_FractalDB	.036
235	BiT-S-R101x1	.035
236	mobilenet_v1_0.75_192	.035
237	mobilenet_v1_0.5_224	.034
238	mobilenet_v2_0.5_128	.034
239	mobilenet_v2_0_75_224	.034
240	mobilenet_v1_0.25_192	.033
241	mobilenet_v2_0.35_224	.033
242	resnet50-meshes-lt-100-original-pretrained	.033
243	resnet50_imagenet_10_seed-0	.033
244	AlexNet_SIN	.032
245	nasnet_mobile	.032
246	efficientnet_b0_imagenet_full	.031
247	mobilenet_v2_1.0_96	.031
248	deit_small_imagenet_10_seed-0	.031
249	deit_small_imagenet_1_seed-0	.031
250	convnext_small_imagenet_10_seed-0	.031
251	resnet50-vicregl0p9	.030
252	resnet50-vicregl0p75	.029
253	mobilenet_v2_0.5_192-tf	.028
254	resnet50-vicreg	.027
255	mobilenet_v2_0.75_96	.027
256	mobilenet_v2_1_3_224	.027
257	mobilenet_v2_1.0_128-tf	.026
258	resnet-50_untrained	.024
259	mobilenet_v1_0.25_224	.024
260	mobilenet_v2_0.75_224-tf	.023
261	blt_vs	.023
262	mobilenet_v2_0.35_128	.023
263	mobilenet_v1_0.5_192	.021
264	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.021
265	mobilenet_v2_1.4_224-tf	.020
266	mobilenet_v2_0.35_160	.020
267	mobilenet_v2_0_75_160	.019
268	mobilenet_v2_0.75_128	.019
269	mobilenet_v2_0_75_192	.019
270	mobilenet_v2_0.5_160	.018
271	imagenet_l2_10_0	.018
272	mobilenet_v2_1.0_192-tf	.017
273	mobilenet_v1_0.75_160	.016
274	squeezenet1_0	.015
275	shufflenet_v2_x1_0	.015
276	mobilenet_v2_0.35_96	.014
277	alexnet_training_seed_06	.014
278	mobilenet_v2_0.5_224-tf	.014
279	mobilenet_v1_0.75_128	.014
280	resnet50_eMMCR_Vanilla	.013
281	resnet_50_v1_spiking_l4a	.012
282	resnet50_imagenet_1_seed-0	.012
283	mobilenet_v2_0.75_160-tf	.011
284	resnet_50_v1_spiking_l4	.011
285	resnet_50_v1_spiking_l3	.011
286	alexnet_training_seed_03	.010
287	mobilenet_v2_0_5_224	.010
288	mobilevit_small	.010
289	mobilenet_v1_1.0_192	.009
290	resnet50-simclr-vissl	.008
291	mobilenet_v1_0.25_160	.007
292	mobilenet_v1_1.0_128	.006
293	mobilenet_v1_1.0_160	.006
294	mobilenet_v1_1.0_224	.005
295	resnet-18	.004
296	mobilenet_v2_1_0_128	.003
297	mobilenet_v2_1.3_224-tf	.003
298	efficientnet_b1_imagenet_full	.003
299	regnet_y_400mf	.002
300	mobilenet_v2_0.75_192-tf	.002
301	mobilenet_v1_0.75_224	.001
302	my-model	.000
303	resnet-18-LC_w_sh_100_iter_conv_init_m
304	ViT-B/32
305	BiT-M-R50x3
306	BiT-M-R50x1
307	BiT-M-R152x2
308	resnet-18-LC_w_sh_1_iter_conv_init_m
309	resnet-18-LC_w_sh_10_iter_m
310	resnet-18-LC_w_sh_100_iter_m
311	resnet-18-LC_w_sh_10_iter_conv_init_m
312	resnet-18-LC_w_sh_1_iter_m
313	FrankRobWobv0
314	0.5x_resnet-18_LC
315	CORnetZ_CIFAR10
316	resnet18-local_aggregation
317	resnet18-deepcluster
318	r3m_resnet18
319	CORnet-Z
320	resnet18-instance_recognition
321	vggface
322	my-model
323	0.5x_resnet-18_LC_w_sh_10_iter
324	r3m_resnet50
325	r3m_resnet34
326	resnet18-colorization
327	resnet-18-LC_m
328	r3m_resnet50_nocrop
329	resnet18-supervised
330	resnet-18-LC_1st_conv_m
331	resnet-18-LC_conv_init_m
332	resnet18-contrastive_multiview
333	0.5x_resnet-18
334	RN50
335	0.5x_resnet-18_LC_w_sh_100_iter
336	RN50
337	resnet18-relative_position
338	resnet18-autoencoder
339	resnet18-simclr
340	ViT_L_32
341	ViT_B_32
342	resnet18-depth_prediction
343	ViT_B_16
344	r3m_resnet34_nocrop
345	resnet18-contrastive_predictive
346	omnivore_swinT
347	resnet-18-LC_untrained
348	resnet-18_untrained
349	resnet-50x2_untrained
350	dcgan
351	unet_entire
352	v1-pyr-nodown
353	CORnetZ_CIFAR10_bs32_20_04
354	pixels
355	dorinet_cornet_z
356	resnet50
357	openclip
358	resnet50-cifar
359	resnet50_pretrained_with_retinal_waves
360	resnet50_ImageNet
361	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
362	yudixie_resnet50_random_0_240908
363	yudixie_resnet50_cat_obj_class_all_latents_0_240908
364	yudixie_resnet50_imagenet1kpret_0_240908
365	yudixie_resnet50_imagenet1kpret_0_240312
366	yudixie_resnet50_object_class_0_240908
367	yudixie_resnet50_category_class_0_240908
368	resnet18_imagenet21kP
369	yudixie_resnet50_distance_reg_0_240908
370	ConvLSTM
371	PredRNN
372	SimVP
373	TAU
374	MIM
375	hmax
376	briaai_rmbg_1_4
377	ReAlnet01_cornet
378	compact_resnet50_V4
379	yudixie_resnet18_translation_reg_0_240719
380	yolos_tiny
381	ReAlnet03_cornet
382	yudixie_resnet18_rotation_reg_0_240719
383	yudixie_resnet18_imagenet1kpret_0_240719
384	ReAlnet02_cornet
385	resnet18_ecoset_full
386	compact_resnet50_IT
387	resnet50_ecoset_full
388	VOneCORnet-S
389	resnet101_ecoset_full
390	yudixie_resnet50_distance_translation_0_240908
391	resnet152_ecoset_full
392	yudixie_resnet18_distance_translation_0_240719
393	yudixie_resnet18_translation_rotation_0_240719
394	compact_vgg19_V4
395	yudixie_resnet18_distance_rotation_0_240719
396	yudixie_resnet18_category_class_0_240719
397	resnet-18_test_m
398	yudixie_resnet18_cat_obj_class_all_latents_0_240719
399	yudixie_resnet50_rotation_reg_0_240908
400	yudixie_resnet50_distance_rotation_0_240908
401	yudixie_resnet18_object_class_0_240719
402	SeLaVi-AVE
403	ReAlnet05_cornet
404	ReAlnet06_cornet
405	compact_resnet50_robust_V4
406	compact_vgg19_IT
407	yudixie_resnet50_translation_reg_0_240908
408	r3d_18
409	ReAlnet01_ALL
410	yudixie_resnet18_distance_reg_0_240719
411	yudixie_resnet50_translation_rotation_0_240908
412	omnivore_swinB
413	mc3_18
414	ReAlnet07_cornet
415	s3d
416	ReAlnet02_ALL
417	mvit_v1_b
418	ReAlnet08_cornet
419	ReAlnet04_ALL
420	compact_cornets_V4
421	ReAlnet03_ALL
422	ReAlnet09_cornet
423	SeLaVi-Kinetics400
424	ReAlnet05_ALL
425	compact_cornets_IT
426	SeLaVi-VGG-Sound
427	ReAlnet06_ALL
428	SeLaVi-Kinetics-Sound
429	mvit_v2_s
430	omnivore_swinS
431	r2plus1d_18
432	compact_resnet50_robust_IT
433	yudixie_resnet50_distance_translation_rotation_0_240908
434	ReAlnet10_cornet
435	ReAlnet07_ALL
436	resnet34_ecoset_full
437	ReAlnet08_ALL
438	yudixie_resnet18_random_0_240719
439	yudixie_resnet18_distance_translation_rotation_0_240719
440	ReAlnet09_ALL
441	ReAlnet04_cornet
442	resnet50_primary_visual_cortex
443	ReAlnet10_ALL

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

0.51.

Note that scores are relative to this ceiling.

Data: Geirhos2021powerequalisation

Metric: error_consistency