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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021rotation-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitl14_reg_lc	.681
2	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.646
3	convnext_large_clip_laion2b_finelayers	.640
4	convnext_xxlarge_clip	.631
5	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.614
6	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.606
7	vit_huge_clip336_laion	.590
8	resnet-152_v2_pytorch	.589
9	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.581
10	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.571
11	dinov2_vitg14_reg_lc	.571
12	fixres_resnext101_32x48d_wsl	.568
13	dinov2_vitl14_lc	.567
14	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.565
15	resnet_152_v2	.561
16	dinov2_vitg14_lc	.560
17	vit_large_patch14_clip_336:laion2b_ft_in1k	.559
18	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.546
19	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.539
20	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.528
21	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.527
22	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.516
23	vit_large_clip336_openai	.511
24	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.506
25	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.500
26	effnetv2m_custom384	.489
27	vit_large_patch14_clip_224:openai_ft_in1k	.488
28	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.478
29	convnext_base:clip_laiona_augreg_ft_in1k_384	.476
30	dinov2_vitl14_lc_res336	.475
31	convnext_large_in22k_supervised	.473
32	convnext_large:fb_in22k_ft_in1k	.467
33	vit_large_patch14_clip_224:laion2b_ft_in1k	.457
34	convnext_base_fb_in22k_ft_in1k	.434
35	pnasnet_large_halfPrecision	.431
36	pnasnet_large	.431
37	vit_base_patch16_clip_224:openai_ft_in1k	.429
38	custom_model_cv_18_dagger_408	.425
39	convnext_xlarge:fb_in22k_ft_in1k	.417
40	resnet_101_v2	.416
41	resnet_50_v2	.413
42	resnext101_32x48d_wsl	.405
43	CLIP_resnet50	.404
44	CLIP_resnet50_float32	.404
45	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.404
46	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.400
47	eva02_large_in22k	.396
48	resnext101_32x16d_wsl	.391
49	resnext101_32x32d_wsl	.385
50	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.380
51	SWSL_resnet50	.370
52	SWSL_resnext101_32x8d	.368
53	CLIP-RN50	.367
54	pnasnet_large-tf	.357
55	effnetb1_272x240	.356
56	resnext101_32x8d_wsl	.351
57	nasnet_large	.344
58	cvt_cvt-13-384-in1k_4_LucyV4	.343
59	cvt_cvt-21-384-in1k_4_LucyV4	.338
60	convnext_tiny:in12k_ft_in1k	.334
61	nasnet_large-tf	.325
62	vision_transformer_vit_large_patch16_224	.308
63	antialias-resnet152	.282
64	inception_v3	.273
65	CLIP_ViT-B_32	.273
66	focalnet_tiny_lrf_in1k	.273
67	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.268
68	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.268
69	inception_v4	.266
70	inception_v3-tf	.264
71	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.261
72	resnet152_imagenet_full	.259
73	convnext_femto_ols:d1_in1k	.255
74	resnet101	.255
75	resnet50-VITO-8deg-cc	.254
76	resnet101_imagenet_full	.250
77	vit_relpos_base_patch16_clsgap_224:sw_in1k	.249
78	resnet-152_v2-tf	.239
79	regnety_032	.238
80	convnext_large_imagenet_full_seed-0	.236
81	resnet50_st_wzc_seed6_2_323	.236
82	resnet_152_v1	.236
83	resnet50_st_wzc_seed3_2_323	.232
84	deit3_base_patch16_224_fb_in1k	.228
85	cv_18_dagger_408_pretrained	.226
86	xception-keras	.225
87	antialiased-rnext101_32x8d	.225
88	convnext_tiny_imagenet_full_seed-0	.224
89	resnet50_random_l2_perturb	.223
90	tv_efficientnet-b1	.221
91	cvt_cvt-13-224-in1k_4_LucyV4	.218
92	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.213
93	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.212
94	convnext_base_imagenet_full_seed-0	.206
95	resnet50	.206
96	inception_v4-tf	.204
97	resnet50_imagenet_full	.204
98	deit_base_imagenet_full_seed-0	.201
99	convnext_small_imagenet_full_seed-0	.197
100	deit_large_imagenet_full_seed-0	.196
101	resnet_101_v1	.195
102	antialiased-r50	.195
103	grcnn_109	.194
104	resnet50_ewconplus_wzc_seed5_2__323	.193
105	resnet50-moclr8deg	.190
106	deit_small_imagenet_full_seed-0	.190
107	resnet50_ewconplus_wzc_seed2_2__323	.183
108	ViT_B_16_imagenet1k	.182
109	cvt_cvt-21-224-in1k_4_LucyV4	.181
110	densenet-201-keras	.181
111	xception	.179
112	Res2Net50_26w_4s	.177
113	pnasnet_large_pytorch	.175
114	convnext_base_fb_in1k	.174
115	densenet-201	.172
116	densenet_201_pytorch	.172
117	resnet_50_v1_spiking	.172
118	efficientnet_b2_imagenet_full	.167
119	vgg_19	.166
120	efficientnet_b0	.165
121	densenet-121-keras	.164
122	convnext_tiny_sup	.161
123	convnext_base_fb_in1k_gram_aligned_dinov3	.161
124	ViT_L_32_imagenet1k	.161
125	seresnext50_32x4d	.161
126	grcnn	.161
127	resnet34_imagenet_full	.160
128	resnet50_ewconplus_wzc	.160
129	resnet-50_v2-tf	.156
130	densenet-121	.155
131	resnet50_st_wzc_2	.155
132	resnet50_tutorial	.154
133	resnet_50_v1	.154
134	resnet-50-pytorch	.154
135	resnet50-sup	.154
136	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.153
137	mobilenet_v2_1.4_224-tf	.153
138	resnet50_random_linf8_perturb	.152
139	ViT_B_32_imagenet1k	.152
140	AdvProp_efficientnet-b6	.150
141	resnet50-SIN_IN_IN	.150
142	resnet_SIN_IN_FT_IN	.150
143	BiT-S-R50x3	.149
144	inception_v2-tf	.149
145	resnet-101_v1-tf	.149
146	resnet50_byol	.144
147	efficientnet-b7	.143
148	nasnet_mobile	.143
149	mobilenet_v2_1_0_224	.140
150	AT_efficientnet-b2	.137
151	AdvProp_efficientnet-b2	.137
152	alexnet_fov4	.136
153	resnet50-vitoimagevidnet8	.135
154	cornet_s	.133
155	BiT-S-R152x2	.132
156	densenet-169-keras	.131
157	voneresnet-50-non_stochastic	.130
158	BiT-S-R101x3	.130
159	mobilenet_v1_0.75_224	.130
160	mobilenet_v2_1.0_224-tf	.130
161	resnet18_imagenet_full	.130
162	efficientnet_b0_imagenet_full	.129
163	mobilenet_v2_1_3_224	.124
164	ReAlnet04	.124
165	AdvProp_efficientnet-b7	.123
166	inception_v1	.123
167	nasnet_mobile-tf	.121
168	ReAlnet03	.120
169	resnet50-SIN_IN	.119
170	resnet50_hvs_wzc	.118
171	resnet-50_v1-tf	.118
172	convnext_small_imagenet_100_seed-0	.117
173	ReAlnet10	.116
174	resnet_50_v1_spiking_l4a	.116
175	vgg_16	.116
176	AdvProp_efficientnet-b4	.115
177	AT_efficientnet-b4	.115
178	eBarlow_lmda_02_1000ep	.115
179	ReAlnet06	.115
180	ReAlnet01	.114
181	ReAlnet02	.114
182	ReAlnet09	.114
183	resnet-152_v1-tf	.114
184	densenet-169	.112
185	eicircuit_resnet18_bn_20260919	.111
186	mobilenet_v2_1.3_224-tf	.109
187	resnet50_moco_v2	.105
188	BiT-S-R152x4	.105
189	efficientnet_b1_imagenet_full	.101
190	AlexNet_SIN_fov4	.101
191	mobilenet_v1_1.0_192	.100
192	inception_v1-tf	.098
193	ReAlnet05	.098
194	mobilenet_v2_1.0_160-tf	.096
195	vonegrcnn_47e	.096
196	ReAlnet07	.095
197	mobilenet_v2_1_0_192	.094
198	CORnet-S	.094
199	mobilenet_v1_1.0_224	.092
200	ReAlnet08	.092
201	mobilenet_v2_1_0_160	.091
202	mobilenet_v2_0_5_224	.091
203	resnet-34	.090
204	mobilenet_v2_0_75_192	.089
205	BiT-S-R50x1	.089
206	mobilenet_v2_0_75_160	.088
207	mobilenet_v2_1-4_224_pytorch	.087
208	mobilenet_v2_1_4_224	.087
209	resnet50_linf_4_robust	.085
210	squeezenet1_1	.085
211	BiT-S-R101x1	.085
212	vonegrcnn_62e_nobn	.085
213	regnet_y_400mf	.085
214	vgg-16-keras	.084
215	vonegrcnn_47e	.081
216	resnet50_simclr	.081
217	mobilenet_v2_0_75_224	.080
218	vonegrcnn_52e_full	.080
219	resnet-18	.079
220	vonegrcnn_52e_full	.079
221	mobilenet_v2_0_5_192	.079
222	AdvProp_efficientnet-b0	.078
223	vonegrcnn_62e_nobn	.075
224	shufflenet_v2_x1_0	.074
225	resnet50_l2_3_robust	.073
226	mobilenet_v1_0.5_192	.073
227	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.073
228	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.071
229	0.5x_resnet-18_LC_w_sh_1_iter	.070
230	mobilenet_v2_0.75_160-tf	.070
231	mobilenet_v2_1.0_192-tf	.069
232	texture_shape_alexnet_trained_on_SIN	.068
233	mobilenet_v2_0.75_224-tf	.067
234	mobilenet_v2_0.75_192-tf	.064
235	texture_shape_resnet50_trained_on_SIN	.064
236	mobilenet_v2_0.35_192	.064
237	mobilenet_v2_1_0_128	.063
238	mobilenet_v2_0.75_96	.063
239	resnet50_eMMCR_Vanilla	.063
240	mobilenet_v1_0.25_224	.062
241	squeezenet1_0	.062
242	resnet50_robust_l2_eps1	.062
243	resnet50_linf_8_robust	.061
244	mobilenet_v2_0.5_192-tf	.061
245	mobilenet_v1_1.0_128	.061
246	AdvProp_efficientnet-b8	.061
247	mobilenet_v1_0.25_192	.060
248	mobilenet_v1_0.75_160	.060
249	mobilenet_v2_0.35_224	.059
250	blt_vs	.059
251	konkle_alexnetgn_ipcl_ref01_primary_model	.059
252	mobilenet_v1_0.5_224	.058
253	resnet50_imagenet_100_seed-0	.058
254	alexnet_random_linf8_perturb	.058
255	resnet-50-robust	.058
256	imagenet_l2_3_0	.058
257	resnet50_robust_l2_eps3	.058
258	voneresnet-50	.057
259	vgg-19-keras	.057
260	alexnet_reduced_aliasing_early_checkpoint	.056
261	mobilenet_v2_0.5_224-tf	.055
262	mobilenet_v2_0.75_128	.055
263	mobilenet_v2_0.35_96	.055
264	resnet50-SIN	.055
265	convnext_small_imagenet_1_seed-0	.054
266	mobilenet_v2_1.0_128-tf	.054
267	mobilenet_v1_0.75_128	.053
268	AlexNet_SIN	.052
269	mobilenet_v2_0.35_160	.052
270	mobilenet_v1_0.75_192	.052
271	voneresnet-50-robust	.052
272	mobilenet_v1_1.0_160	.050
273	alexnet_random_l2_3_perturb	.050
274	mobilenet_v2_0.5_96	.050
275	mobilenet_v2_0.5_160	.049
276	alexnet_ks_torevert	.049
277	alexnet	.049
278	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.049
279	mobilenet_v2_0.35_128	.048
280	mobilenet_v1_0.5_128	.046
281	alexnet_fov12	.045
282	vonealexnet_gaussian_noise_std4_fixed	.045
283	alexnet_early_checkpoint	.044
284	alexnet_l2_3_robust	.044
285	resnet_50_v1_spiking_l4	.042
286	AlexNet_SIN_fov12	.042
287	mobilenet_v2_1.0_96	.042
288	alexnet_fov16	.041
289	mobilenet_v2_0.5_128	.038
290	alexnet_training_seed_05	.037
291	alexnet_training_seed_01	.037
292	alexnet_training_seed_01_fov4	.037
293	alexnet_training_seed_01_fov12	.037
294	alexnet_training_seed_01_fov16	.037
295	mobilenet_v1_0.25_160	.035
296	imagenet_l2_10_0	.035
297	mobilenet_v1_0.5_160	.033
298	resnet50-vicregl0p75	.032
299	AlexNet_SIN_fov16	.031
300	alexnet_linf_8_robust	.029
301	alexnet_robust_correct	.023
302	resnet-50_untrained	.021
303	alexnet_training_seed_06	.018
304	deit_small_imagenet_100_seed-0	.018
305	alexnet_training_seed_03	.016
306	resnet50-vicreg	.015
307	resnet50_FractalDB	.012
308	artResNet18_1	.011
309	alexnet_training_seed_07	.011
310	resnet50-vicregl0p9	.009
311	alexnet_training_seed_02	.009
312	alexnet_training_seed_04	.009
313	alexnet_training_seed_08	.009
314	alexnet_training_seed_10	.009
315	mobilenet_v1_0.25_128	.008
316	deit_small_imagenet_10_seed-0	.008
317	deit_small_imagenet_1_seed-0	.008
318	convnext_small_imagenet_10_seed-0	.007
319	resnet50_imagenet_10_seed-0	.007
320	mobilevit_small	.007
321	resnet50_imagenet_1_seed-0	.006
322	resnet50-barlow	.004
323	resnet50-simclr-vissl	.003
324	barlow-twins-resnet50	.002
325	resnet_50_v1_spiking_l3	.001
326	alexnet_training_seed_09	.001
327	resnet-18-LC_w_sh_100_iter_conv_init_m
328	ViT-B/32
329	BiT-M-R50x3
330	BiT-M-R50x1
331	BiT-M-R152x2
332	resnet-18-LC_w_sh_1_iter_conv_init_m
333	resnet-18-LC_w_sh_10_iter_m
334	resnet-18-LC_w_sh_100_iter_m
335	resnet-18-LC_w_sh_10_iter_conv_init_m
336	FrankRobWobv0
337	resnet-18-LC_w_sh_1_iter_m
338	0.5x_resnet-18_LC
339	CORnetZ_CIFAR10
340	resnet18-local_aggregation
341	resnet18-deepcluster
342	r3m_resnet18
343	CORnet-Z
344	vggface
345	my-model
346	resnet18-instance_recognition
347	0.5x_resnet-18_LC_w_sh_10_iter
348	r3m_resnet50
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	resnet18-colorization
358	RN50
359	0.5x_resnet-18_LC_w_sh_100_iter
360	RN50
361	resnet18-relative_position
362	resnet18-autoencoder
363	resnet18-simclr
364	ViT_L_32
365	ViT_B_32
366	resnet18-depth_prediction
367	ViT_B_16
368	r3m_resnet34_nocrop
369	resnet18-contrastive_predictive
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	omnivore_swinT
378	pixels
379	dorinet_cornet_z
380	my-model
381	openclip
382	resnet50-cifar
383	resnet50_pretrained_with_retinal_waves
384	resnet50_ImageNet
385	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
386	ReAlnet07_ALL
387	yudixie_resnet50_imagenet1kpret_0_240312
388	yudixie_resnet50_imagenet1kpret_0_240908
389	yudixie_resnet50_random_0_240908
390	yudixie_resnet50_cat_obj_class_all_latents_0_240908
391	yudixie_resnet50_category_class_0_240908
392	resnet18_imagenet21kP
393	ConvLSTM
394	PredRNN
395	yudixie_resnet50_distance_reg_0_240908
396	SimVP
397	TAU
398	MIM
399	hmax
400	inception_v3_pytorch
401	yolos_tiny
402	ReAlnet01_cornet
403	yudixie_resnet18_translation_reg_0_240719
404	yudixie_resnet18_distance_reg_0_240719
405	compact_resnet50_V4
406	yudixie_resnet18_rotation_reg_0_240719
407	briaai_rmbg_1_4
408	vit_base_patch14_dinov2-lvd142m
409	ReAlnet03_cornet
410	vit_base_patch16_dinov3-lvd1689m
411	resnet18_ecoset_full
412	ReAlnet01_cornet_fov4
413	resnet34_ecoset_full
414	compact_resnet50_IT
415	resnet50_ecoset_full
416	compact_resnet50_robust_V4
417	resnet101_ecoset_full
418	yudixie_resnet50_distance_translation_0_240908
419	yudixie_resnet50_rotation_reg_0_240908
420	resnet152_ecoset_full
421	ReAlnet01_cornet_fov12
422	yudixie_resnet18_distance_translation_0_240719
423	yudixie_resnet18_translation_rotation_0_240719
424	yudixie_resnet18_distance_rotation_0_240719
425	yudixie_resnet18_category_class_0_240719
426	ReAlnet05_cornet
427	compact_vgg19_V4
428	yudixie_resnet18_cat_obj_class_all_latents_0_240719
429	resnet-18_test_m
430	yudixie_resnet18_distance_translation_rotation_0_240719
431	yudixie_resnet18_object_class_0_240719
432	yudixie_resnet18_imagenet1kpret_0_240719
433	SeLaVi-AVE
434	ReAlnet06_cornet
435	r3d_18
436	ReAlnet01_cornet_fov16
437	compact_vgg19_IT
438	yudixie_resnet50_translation_reg_0_240908
439	yudixie_resnet50_translation_rotation_0_240908
440	ReAlnet01_ALL
441	mc3_18
442	ReAlnet07_cornet
443	s3d
444	mvit_v1_b
445	ReAlnet08_cornet
446	ReAlnet03_ALL
447	VOneCORnet-S
448	compact_cornets_V4
449	omnivore_swinB
450	ReAlnet04_ALL
451	SeLaVi-Kinetics400
452	ReAlnet09_cornet
453	SeLaVi-VGG-Sound
454	compact_cornets_IT
455	ReAlnet05_ALL
456	omnivore_swinS
457	ReAlnet06_ALL
458	mvit_v2_s
459	SeLaVi-Kinetics-Sound
460	compact_resnet50_robust_IT
461	ReAlnet10_cornet
462	r2plus1d_18
463	ReAlnet08_ALL
464	yudixie_resnet18_random_0_240719
465	yudixie_resnet50_distance_rotation_0_240908
466	ReAlnet02_cornet
467	yudixie_resnet50_distance_translation_rotation_0_240908
468	ReAlnet09_ALL
469	ReAlnet04_cornet
470	resnet50_primary_visual_cortex
471	yudixie_resnet50_object_class_0_240908
472	ReAlnet10_ALL
473	ReAlnet02_ALL
474	vit_base_patch14_reg4_dinov2-lvd142m
475	resnet18_fair
476	pr1_stl10_disentangled_alpha04
477	predictive_coding_pc
478	yudixie_wbh_object_class_scaling_0415_run_0
479	yudixie_wbh_object_class_scaling_0415_run_3
480	yudixie_wbh_object_class_scaling_0415_imagenet
481	yudixie_wbh_object_class_scaling_0415_run_2
482	yudixie_wbh_object_class_scaling_0415_run_1
483	deepeisnn_ei_cifar10_vgg19
484	deepeisnn_ei_cifar10_resnet18
485	deepeisnn_ei_imagenet_resnet18
486	dinov2_vitl14_reg_lc_featread
487	gabor_filter_entropy_4x4
488	gabor_filter_mean_abs_4x4_v2
489	gabor_filter_entropy_4x4_v2
490	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

0.44.

Note that scores are relative to this ceiling.

Data: Geirhos2021rotation

Metric: error_consistency