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-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitg14_reg_lc	.995
2	dinov2_vitl14_reg_lc	.993
3	eva02_large_in22k	.991
4	dinov2_vitg14_lc	.989
5	dinov2_vitl14_lc_res336	.989
6	dinov2_vitl14_lc	.986
7	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.979
8	convnext_xxlarge_clip	.975
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.970
10	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.968
11	convnext_large_in22k_supervised	.966
12	vit_large_patch14_clip_224:openai_ft_in1k	.964
13	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.964
14	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.963
15	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.963
16	vit_huge_clip336_laion	.961
17	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.959
18	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.959
19	vit_large_clip336_openai	.959
20	convnext_large_clip_laion2b_finelayers	.952
21	convnext_large:fb_in22k_ft_in1k	.948
22	vit_large_patch14_clip_336:laion2b_ft_in1k	.945
23	convnext_base_fb_in1k	.945
24	convnext_xlarge:fb_in22k_ft_in1k	.943
25	deit_large_imagenet_full_seed-0	.943
26	vit_large_patch14_clip_224:laion2b_ft_in1k	.939
27	convnext_large_imagenet_full_seed-0	.938
28	convnext_base_fb_in22k_ft_in1k	.938
29	convnext_base:clip_laiona_augreg_ft_in1k_384	.936
30	convnext_small_imagenet_full_seed-0	.934
31	convnext_base_imagenet_full_seed-0	.934
32	deit3_base_patch16_224_fb_in22k_ft_in1k	.932
33	deit_base_imagenet_full_seed-0	.929
34	convnext_tiny:in12k_ft_in1k	.927
35	effnetv2m_custom384	.923
36	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.914
37	resnext101_32x32d_wsl	.911
38	vit_relpos_base_patch16_clsgap_224:sw_in1k	.911
39	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.909
40	fixres_resnext101_32x48d_wsl	.907
41	cv_18_dagger_408_pretrained	.905
42	focalnet_tiny_lrf_in1k	.905
43	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.902
44	resnext101_32x16d_wsl	.902
45	resnext101_32x48d_wsl	.900
46	vit_base_patch16_clip_224:openai_ft_in1k	.896
47	resnext101_32x8d_wsl	.896
48	convnext_tiny_imagenet_full_seed-0	.893
49	AdvProp_efficientnet-b7	.891
50	seresnext50_32x4d	.889
51	regnety_032	.882
52	AdvProp_efficientnet-b6	.875
53	convnext_tiny_sup	.875
54	cvt_cvt-13-224-in1k_4_LucyV4	.871
55	deit_small_imagenet_full_seed-0	.868
56	nasnet_large-tf	.864
57	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.863
58	resnet_101_v2	.854
59	resnet-152_v2_pytorch	.850
60	cvt_cvt-21-384-in1k_4_LucyV4	.850
61	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.845
62	cvt_cvt-21-224-in1k_4_LucyV4	.841
63	nasnet_large	.841
64	convnext_femto_ols:d1_in1k	.836
65	AdvProp_efficientnet-b4	.834
66	AT_efficientnet-b4	.834
67	densenet-201	.832
68	densenet_201_pytorch	.832
69	densenet-201-keras	.832
70	inception_v4-tf	.830
71	densenet-169	.825
72	densenet-169-keras	.823
73	cvt_cvt-13-384-in1k_4_LucyV4	.823
74	resnet_50_v2	.823
75	convnext_base_fb_in1k_gram_aligned_dinov3	.823
76	efficientnet-b7	.820
77	pnasnet_large-tf	.814
78	resnet-101_v2-tf	.812
79	pnasnet_large_halfPrecision	.812
80	pnasnet_large	.812
81	inception_v4	.807
82	inception_v3-tf	.807
83	resnet50-SIN	.807
84	inception_v2-tf	.804
85	inception_v3_pytorch	.804
86	tv_efficientnet-b1	.804
87	resnet_152_v2	.804
88	AdvProp_efficientnet-b0	.802
89	xception-keras	.800
90	resnet50-SIN_IN	.798
91	antialiased-rnext101_32x8d	.798
92	ViT_L_32_imagenet1k	.796
93	AT_efficientnet-b2	.796
94	AdvProp_efficientnet-b2	.796
95	effnetb1_272x240	.793
96	antialias-resnet152	.793
97	resnet_152_v1	.793
98	ijepa_vith14_linhead	.793
99	inception_v3	.791
100	BiT-S-R152x2	.787
101	BiT-S-R50x3	.786
102	resnet-152_v2-tf	.786
103	grcnn_109	.786
104	BiT-S-R152x4	.780
105	resnet-50_v2-tf	.780
106	Res2Net50_26w_4s	.780
107	resnet50_st_wzc_2	.777
108	BiT-S-R101x1	.777
109	densenet-121-keras	.775
110	BiT-S-R101x3	.775
111	BiT-S-R50x1	.773
112	densenet-121	.773
113	resnet50_hvs_wzc	.773
114	resnet50-vitoimagevidnet8	.770
115	inception_v1-tf	.766
116	ViT_B_32_imagenet1k	.766
117	resnet50_ewconplus_wzc	.766
118	resnet_101_v1	.766
119	resnet50_st_wzc_seed6_2_323	.762
120	resnet101_imagenet_full	.757
121	resnet_SIN_IN_FT_IN	.755
122	resnet50-SIN_IN_IN	.755
123	resnet50-VITO-8deg-cc	.754
124	grcnn	.752
125	efficientnet_b0	.743
126	resnet-152_v1-tf	.738
127	vonegrcnn_47e	.736
128	resnet50_ewconplus_wzc_seed2_2__323	.734
129	resnet50_ewconplus_wzc_seed5_2__323	.734
130	resnet50_tutorial	.732
131	resnet_50_v1	.732
132	resnet-50-pytorch	.732
133	resnet50-sup	.732
134	vonegrcnn_47e	.730
135	resnet50-moclr8deg	.730
136	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.730
137	antialiased-r50	.729
138	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.727
139	AdvProp_efficientnet-b8	.725
140	resnet50_st_wzc_seed7_2_323	.723
141	efficientnet_b2_imagenet_full	.720
142	vonegrcnn_62e_nobn	.720
143	resnet-50_v1-tf	.720
144	resnet50_imagenet_full	.718
145	resnet152_imagenet_full	.716
146	resnet50	.711
147	vonegrcnn_52e_full	.709
148	resnet-101_v1-tf	.709
149	resnet50_vicreg_linhead	.707
150	vonegrcnn_62e_nobn	.707
151	CORnet-S	.707
152	xception	.704
153	resnet-34	.698
154	resnet_50_v1_spiking	.698
155	CLIP-RN50	.696
156	resnet50_moco_v2	.696
157	resnet50_robust_l2_eps1	.696
158	voneresnet-50-non_stochastic	.695
159	vgg-19-keras	.691
160	resnet34_imagenet_full	.691
161	efficientnet_b1_imagenet_full	.691
162	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.689
163	resnet50_byol_linhead	.688
164	vonegrcnn_52e_full	.686
165	inception_v1	.684
166	mobilenet_v2_1.4_224-tf	.682
167	mobilenet_v2_1.3_224-tf	.679
168	voneresnet-50-robust	.679
169	mobilenet_v2_1_3_224	.679
170	resnet50_simclr_linhead_01norm	.677
171	ReAlnet06	.673
172	AlexNet_SIN	.671
173	AlexNet_SIN_fov4	.671
174	AlexNet_SIN_fov12	.671
175	AlexNet_SIN_fov16	.671
176	resnet50_simsiam_linhead	.671
177	nasnet_mobile	.670
178	eBarlow_lmda_02_1000ep	.664
179	mobilenet_v2_1.0_224-tf	.664
180	vgg-16-keras	.661
181	efficientnet_b0_imagenet_full	.657
182	pnasnet_large_pytorch	.657
183	eicircuit_resnet18_bn_20260919	.657
184	resnet50_barlowtwins_linhead	.657
185	voneresnet-50	.652
186	vgg_16	.652
187	vgg_19	.648
188	ReAlnet04	.648
189	ReAlnet01	.645
190	mobilenet_v2_0.75_192-tf	.641
191	mobilenet_v2_1_0_224	.639
192	mobilenet_v2_1.0_192-tf	.637
193	mobilenet_v1_1.0_192	.637
194	regnet_y_400mf	.637
195	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.636
196	resnet18_imagenet_full	.632
197	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.632
198	resnet-18	.630
199	mobilenet_v2_1_0_192	.630
200	ReAlnet09	.627
201	mobilenet_v2_0.75_224-tf	.627
202	mobilenet_v2_0_75_192	.625
203	blt_vs	.625
204	ReAlnet03	.625
205	custom_model_cv_18_dagger_408	.623
206	ReAlnet08	.621
207	ReAlnet05	.621
208	mobilenet_v2_1.0_160-tf	.620
209	mobilenet_v1_1.0_224	.616
210	ReAlnet07	.613
211	ReAlnet10	.611
212	ReAlnet02	.609
213	nasnet_mobile-tf	.609
214	resnet-50-robust	.609
215	imagenet_l2_3_0	.609
216	resnet50_robust_l2_eps3	.609
217	mobilenet_v2_0_75_224	.605
218	mobilenet_v2_1_0_160	.604
219	shufflenet_v2_x1_0	.598
220	resnet50_eMMCR_Vanilla	.598
221	mobilenet_v2_1-4_224_pytorch	.596
222	mobilenet_v2_1_4_224	.596
223	mobilenet_v1_0.75_224	.596
224	mehrer2020_alexnet_training_seed_02	.589
225	mobilenet_v2_1.0_128-tf	.586
226	mehrer2020_alexnet_training_seed_01	.584
227	mehrer2020_alexnet_training_seed_01_fov12	.584
228	mehrer2020_alexnet_training_seed_01_fov4	.584
229	mehrer2020_alexnet_training_seed_01_fov16	.584
230	mobilenet_v1_1.0_160	.571
231	mobilenet_v2_1_0_128	.570
232	resnet50_l2_3_robust	.570
233	mehrer2020_alexnet_training_seed_04	.564
234	mobilenet_v2_0_5_224	.559
235	mehrer2020_alexnet_training_seed_05	.557
236	resnet_50_v1_spiking_l4a	.554
237	convnext_small_imagenet_100_seed-0	.554
238	mobilenet_v2_0_75_160	.552
239	mehrer2020_alexnet_training_seed_03	.550
240	mobilenet_v2_0.5_224-tf	.548
241	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.541
242	mobilenet_v1_0.75_192	.539
243	mobilenet_v1_0.75_160	.539
244	mobilenet_v1_1.0_128	.537
245	mobilenet_v2_0.75_160-tf	.537
246	resnet50_linf_8_robust	.536
247	mobilenet_v2_0_5_192	.532
248	mobilenet_v2_0.75_128	.532
249	alexnet_random_linf8_perturb	.532
250	mobilenet_v1_0.5_224	.530
251	mobilenet_v2_0.5_160	.523
252	mobilenet_v2_0.5_192-tf	.521
253	alexnet	.505
254	alexnet_ks_torevert	.505
255	alexnet_fov4	.505
256	alexnet_fov12	.505
257	alexnet_fov16	.505
258	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.504
259	squeezenet1_1	.498
260	mobilenet_v1_0.5_160	.498
261	alexnet_early_checkpoint	.498
262	mobilenet_v2_0.35_192	.496
263	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.495
264	mobilenet_v1_0.5_192	.495
265	mobilenet_v2_1.0_96	.491
266	mobilenet_v1_0.75_128	.484
267	mobilenet_v2_0.5_128	.482
268	mobilenet_v2_0.35_224	.461
269	squeezenet1_0	.457
270	mobilenet_v1_0.5_128	.457
271	mobilenet_v2_0.35_160	.454
272	mobilenet_v2_0.75_96	.445
273	imagenet_l2_10_0	.425
274	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.412
275	0.5x_resnet-18_LC_w_sh_1_iter	.409
276	mobilenet_v2_0.35_128	.396
277	mobilenet_v2_0.5_96	.366
278	mobilenet_v1_0.25_224	.366
279	alexnet_robust_correct	.362
280	mobilenet_v2_0.35_96	.354
281	mobilenet_v1_0.25_160	.339
282	alexnet_l2_3_robust	.327
283	mobilenet_v1_0.25_192	.316
284	alexnet_linf_8_robust	.296
285	mobilenet_v1_0.25_128	.284
286	deit_small_imagenet_100_seed-0	.282
287	resnet_50_v1_spiking_l4	.279
288	resnet50_imagenet_100_seed-0	.266
289	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.084
290	resnet50-vicregl0p9	.077
291	convnext_small_imagenet_10_seed-0	.075
292	resnet50_imagenet_10_seed-0	.073
293	resnet_50_v1_spiking_l3	.073
294	deit_small_imagenet_10_seed-0	.066
295	resnet50_imagenet_1_seed-0	.066
296	alexnet_training_seed_09	.064
297	convnext_small_imagenet_1_seed-0	.064
298	resnet50-vicregl0p75	.064
299	resnet-50_untrained	.062
300	alexnet_training_seed_05	.062
301	mobilevit_small	.062
302	alexnet_training_seed_02	.062
303	alexnet_training_seed_04	.062
304	alexnet_training_seed_08	.062
305	alexnet_training_seed_10	.062
306	alexnet_training_seed_01	.062
307	deit_small_imagenet_1_seed-0	.062
308	alexnet_training_seed_01_fov4	.062
309	alexnet_training_seed_01_fov12	.062
310	alexnet_training_seed_01_fov16	.062
311	alexnet_training_seed_03	.062
312	alexnet_training_seed_06	.059
313	alexnet_training_seed_07	.057
314	resnet50-barlow	.052
315	artResNet18_1	.048
316	barlow-twins-resnet50	.048
317	resnet50-simclr-vissl	.039
318	ViT-B/32
319	resnet-18-LC_w_sh_100_iter_conv_init_m
320	BiT-M-R50x1
321	resnet-18-LC_w_sh_1_iter_conv_init_m
322	BiT-M-R152x2
323	resnet-18-LC_w_sh_1_iter_m
324	BiT-M-R50x3
325	resnet-18-LC_w_sh_10_iter_m
326	resnet-18-LC_w_sh_100_iter_m
327	resnet-18-LC_w_sh_10_iter_conv_init_m
328	FrankRobWobv0
329	0.5x_resnet-18_LC
330	CORnetZ_CIFAR10
331	resnet18-local_aggregation
332	r3m_resnet18
333	resnet18-deepcluster
334	CORnet-Z
335	vggface
336	resnet18-instance_recognition
337	my-model
338	0.5x_resnet-18_LC_w_sh_10_iter
339	r3m_resnet50
340	r3m_resnet34
341	resnet-18-LC_m
342	resnet18-supervised
343	r3m_resnet50_nocrop
344	resnet-18-LC_1st_conv_m
345	resnet-18-LC_conv_init_m
346	resnet18-contrastive_multiview
347	0.5x_resnet-18
348	0.5x_resnet-18_LC_w_sh_100_iter
349	RN50
350	RN50
351	resnet18-colorization
352	resnet18-relative_position
353	resnet18-autoencoder
354	resnet18-simclr
355	ViT_L_32
356	ViT_B_32
357	resnet18-depth_prediction
358	ViT_B_16
359	r3m_resnet34_nocrop
360	resnet18-contrastive_predictive
361	resnet-18-LC_untrained
362	resnet-18_untrained
363	resnet-50x2_untrained
364	dcgan
365	unet_entire
366	CORnetZ_CIFAR10_bs32_20_04
367	v1-pyr-nodown
368	pixels
369	dorinet_cornet_z
370	omnivore_swinT
371	openclip
372	vonealexnet_gaussian_noise_std4_fixed
373	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
374	ReAlnet08_ALL
375	yudixie_resnet50_imagenet1kpret_0_240312
376	yudixie_resnet50_category_class_0_240908
377	yudixie_resnet50_distance_reg_0_240908
378	resnet18_imagenet21kP
379	ConvLSTM
380	PredRNN
381	SimVP
382	TAU
383	yolos_tiny
384	MIM
385	hmax
386	yudixie_resnet18_distance_translation_0_240719
387	briaai_rmbg_1_4
388	vit_base_patch16_dinov3-lvd1689m
389	ReAlnet03_cornet
390	yudixie_resnet18_distance_reg_0_240719
391	yudixie_resnet18_rotation_reg_0_240719
392	yudixie_resnet18_imagenet1kpret_0_240719
393	compact_resnet50_V4
394	ReAlnet02_cornet
395	yudixie_resnet50_rotation_reg_0_240908
396	yudixie_resnet50_distance_rotation_0_240908
397	yudixie_resnet50_distance_translation_0_240908
398	compact_resnet50_IT
399	resnet18_ecoset_full
400	vit_base_patch14_dinov2-lvd142m
401	VOneCORnet-S
402	ReAlnet01_cornet_fov4
403	ReAlnet04_cornet
404	resnet50_ecoset_full
405	resnet101_ecoset_full
406	ReAlnet01_cornet_fov12
407	vit_base_patch14_reg4_dinov2-lvd142m
408	resnet152_ecoset_full
409	compact_vgg19_V4
410	yudixie_resnet18_translation_rotation_0_240719
411	yudixie_resnet18_distance_rotation_0_240719
412	resnet-18_test_m
413	yudixie_resnet50_translation_reg_0_240908
414	yudixie_resnet18_category_class_0_240719
415	ReAlnet05_cornet
416	yudixie_resnet18_random_0_240719
417	yudixie_resnet18_cat_obj_class_all_latents_0_240719
418	yudixie_resnet18_translation_reg_0_240719
419	compact_vgg19_IT
420	yudixie_resnet18_distance_translation_rotation_0_240719
421	yudixie_resnet18_object_class_0_240719
422	SeLaVi-AVE
423	compact_resnet50_robust_V4
424	r3d_18
425	yudixie_resnet50_translation_rotation_0_240908
426	ReAlnet01_ALL
427	ReAlnet07_cornet
428	mc3_18
429	ReAlnet02_ALL
430	s3d
431	omnivore_swinB
432	ReAlnet08_cornet
433	resnet50-vicreg
434	mvit_v1_b
435	ReAlnet04_ALL
436	compact_cornets_V4
437	ReAlnet03_ALL
438	compact_cornets_IT
439	ReAlnet09_cornet
440	omnivore_swinS
441	ReAlnet05_ALL
442	SeLaVi-Kinetics400
443	SeLaVi-VGG-Sound
444	ReAlnet06_ALL
445	SeLaVi-Kinetics-Sound
446	compact_resnet50_robust_IT
447	yudixie_resnet50_distance_translation_rotation_0_240908
448	yudixie_resnet50_random_0_240908
449	r2plus1d_18
450	mvit_v2_s
451	yudixie_resnet50_imagenet1kpret_0_240908
452	ReAlnet07_ALL
453	resnet34_ecoset_full
454	yudixie_resnet50_cat_obj_class_all_latents_0_240908
455	ReAlnet09_ALL
456	yudixie_resnet50_object_class_0_240908
457	ReAlnet10_cornet
458	resnet50_primary_visual_cortex
459	ReAlnet10_ALL
460	ReAlnet01_cornet
461	ReAlnet01_cornet_fov16
462	ReAlnet06_cornet
463	resnet18_fair
464	pr1_stl10_disentangled_alpha04
465	predictive_coding_pc
466	yudixie_wbh_object_class_scaling_0415_run_0
467	yudixie_wbh_object_class_scaling_0415_run_3
468	yudixie_wbh_object_class_scaling_0415_imagenet
469	yudixie_wbh_object_class_scaling_0415_run_2
470	yudixie_wbh_object_class_scaling_0415_run_1
471	deepeisnn_ei_cifar10_vgg19
472	deepeisnn_ei_cifar10_resnet18
473	deepeisnn_ei_imagenet_resnet18
474	dinov2_vitl14_reg_lc_featread
475	gabor_filter_entropy_4x4
476	gabor_filter_mean_abs_4x4_v2
477	gabor_filter_entropy_4x4_v2
478	gabor_filter_entropy_4x4_v2_forcedCosine

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

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021powerequalisation

Metric: top1