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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	mehrer2020_alexnet_training_seed_01_fov4	.177
113	Res2Net50_26w_4s	.177
114	pnasnet_large_pytorch	.175
115	convnext_base_fb_in1k	.174
116	densenet-201	.172
117	densenet_201_pytorch	.172
118	resnet_50_v1_spiking	.172
119	efficientnet_b2_imagenet_full	.167
120	vgg_19	.166
121	efficientnet_b0	.165
122	densenet-121-keras	.164
123	convnext_tiny_sup	.161
124	convnext_base_fb_in1k_gram_aligned_dinov3	.161
125	ViT_L_32_imagenet1k	.161
126	seresnext50_32x4d	.161
127	grcnn	.161
128	resnet34_imagenet_full	.160
129	resnet50_ewconplus_wzc	.160
130	resnet-50_v2-tf	.156
131	densenet-121	.155
132	resnet50_st_wzc_2	.155
133	resnet50_tutorial	.154
134	resnet_50_v1	.154
135	resnet-50-pytorch	.154
136	resnet50-sup	.154
137	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.153
138	mobilenet_v2_1.4_224-tf	.153
139	resnet50_random_linf8_perturb	.152
140	ViT_B_32_imagenet1k	.152
141	AdvProp_efficientnet-b6	.150
142	resnet50-SIN_IN_IN	.150
143	resnet_SIN_IN_FT_IN	.150
144	BiT-S-R50x3	.149
145	inception_v2-tf	.149
146	resnet-101_v1-tf	.149
147	resnet50_byol	.144
148	efficientnet-b7	.143
149	nasnet_mobile	.143
150	mobilenet_v2_1_0_224	.140
151	AT_efficientnet-b2	.137
152	AdvProp_efficientnet-b2	.137
153	alexnet_fov4	.136
154	resnet50-vitoimagevidnet8	.135
155	cornet_s	.133
156	BiT-S-R152x2	.132
157	densenet-169-keras	.131
158	resnet50_simsiam_linhead	.131
159	voneresnet-50-non_stochastic	.130
160	BiT-S-R101x3	.130
161	mobilenet_v1_0.75_224	.130
162	mobilenet_v2_1.0_224-tf	.130
163	resnet18_imagenet_full	.130
164	efficientnet_b0_imagenet_full	.129
165	ijepa_vith14_linhead	.129
166	mobilenet_v2_1_3_224	.124
167	ReAlnet04	.124
168	AdvProp_efficientnet-b7	.123
169	inception_v1	.123
170	nasnet_mobile-tf	.121
171	ReAlnet03	.120
172	resnet50-SIN_IN	.119
173	resnet50_hvs_wzc	.118
174	resnet-50_v1-tf	.118
175	convnext_small_imagenet_100_seed-0	.117
176	ReAlnet10	.116
177	resnet_50_v1_spiking_l4a	.116
178	vgg_16	.116
179	AdvProp_efficientnet-b4	.115
180	AT_efficientnet-b4	.115
181	eBarlow_lmda_02_1000ep	.115
182	ReAlnet06	.115
183	ReAlnet01	.114
184	ReAlnet02	.114
185	ReAlnet09	.114
186	resnet-152_v1-tf	.114
187	densenet-169	.112
188	eicircuit_resnet18_bn_20260919	.111
189	resnet50_byol_linhead	.111
190	mobilenet_v2_1.3_224-tf	.109
191	resnet50_barlowtwins_linhead	.108
192	resnet50_moco_v2	.105
193	BiT-S-R152x4	.105
194	efficientnet_b1_imagenet_full	.101
195	AlexNet_SIN_fov4	.101
196	mobilenet_v1_1.0_192	.100
197	inception_v1-tf	.098
198	ReAlnet05	.098
199	resnet50_vicreg_linhead	.096
200	mobilenet_v2_1.0_160-tf	.096
201	vonegrcnn_47e	.096
202	ReAlnet07	.095
203	mobilenet_v2_1_0_192	.094
204	CORnet-S	.094
205	mobilenet_v1_1.0_224	.092
206	resnet50_simclr_linhead_01norm	.092
207	ReAlnet08	.092
208	mobilenet_v2_1_0_160	.091
209	mobilenet_v2_0_5_224	.091
210	resnet-34	.090
211	mobilenet_v2_0_75_192	.089
212	BiT-S-R50x1	.089
213	mobilenet_v2_0_75_160	.088
214	mobilenet_v2_1-4_224_pytorch	.087
215	mobilenet_v2_1_4_224	.087
216	resnet50_linf_4_robust	.085
217	squeezenet1_1	.085
218	BiT-S-R101x1	.085
219	vonegrcnn_62e_nobn	.085
220	regnet_y_400mf	.085
221	vgg-16-keras	.084
222	vonegrcnn_47e	.081
223	resnet50_simclr	.081
224	mobilenet_v2_0_75_224	.080
225	vonegrcnn_52e_full	.080
226	resnet-18	.079
227	vonegrcnn_52e_full	.079
228	mobilenet_v2_0_5_192	.079
229	AdvProp_efficientnet-b0	.078
230	vonegrcnn_62e_nobn	.075
231	shufflenet_v2_x1_0	.074
232	resnet50_l2_3_robust	.073
233	mobilenet_v1_0.5_192	.073
234	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.073
235	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.071
236	0.5x_resnet-18_LC_w_sh_1_iter	.070
237	mobilenet_v2_0.75_160-tf	.070
238	mobilenet_v2_1.0_192-tf	.069
239	texture_shape_alexnet_trained_on_SIN	.068
240	mobilenet_v2_0.75_224-tf	.067
241	mehrer2020_alexnet_training_seed_01	.066
242	mobilenet_v2_0.75_192-tf	.064
243	texture_shape_resnet50_trained_on_SIN	.064
244	mobilenet_v2_0.35_192	.064
245	mobilenet_v2_1_0_128	.063
246	mobilenet_v2_0.75_96	.063
247	resnet50_eMMCR_Vanilla	.063
248	mehrer2020_alexnet_training_seed_02	.063
249	mobilenet_v1_0.25_224	.062
250	squeezenet1_0	.062
251	resnet50_robust_l2_eps1	.062
252	resnet50_linf_8_robust	.061
253	mobilenet_v2_0.5_192-tf	.061
254	mobilenet_v1_1.0_128	.061
255	AdvProp_efficientnet-b8	.061
256	mobilenet_v1_0.25_192	.060
257	mobilenet_v1_0.75_160	.060
258	mobilenet_v2_0.35_224	.059
259	blt_vs	.059
260	konkle_alexnetgn_ipcl_ref01_primary_model	.059
261	mobilenet_v1_0.5_224	.058
262	resnet50_imagenet_100_seed-0	.058
263	alexnet_random_linf8_perturb	.058
264	resnet-50-robust	.058
265	imagenet_l2_3_0	.058
266	resnet50_robust_l2_eps3	.058
267	voneresnet-50	.057
268	vgg-19-keras	.057
269	alexnet_reduced_aliasing_early_checkpoint	.056
270	mobilenet_v2_0.5_224-tf	.055
271	mobilenet_v2_0.75_128	.055
272	mobilenet_v2_0.35_96	.055
273	resnet50-SIN	.055
274	convnext_small_imagenet_1_seed-0	.054
275	mobilenet_v2_1.0_128-tf	.054
276	mobilenet_v1_0.75_128	.053
277	mehrer2020_alexnet_training_seed_04	.053
278	AlexNet_SIN	.052
279	mobilenet_v2_0.35_160	.052
280	mobilenet_v1_0.75_192	.052
281	voneresnet-50-robust	.052
282	mobilenet_v1_1.0_160	.050
283	alexnet_random_l2_3_perturb	.050
284	mobilenet_v2_0.5_96	.050
285	mobilenet_v2_0.5_160	.049
286	alexnet_ks_torevert	.049
287	alexnet	.049
288	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.049
289	mobilenet_v2_0.35_128	.048
290	mehrer2020_alexnet_training_seed_05	.048
291	mobilenet_v1_0.5_128	.046
292	mehrer2020_alexnet_training_seed_03	.045
293	mehrer2020_alexnet_training_seed_01_fov12	.045
294	alexnet_fov12	.045
295	vonealexnet_gaussian_noise_std4_fixed	.045
296	alexnet_early_checkpoint	.044
297	alexnet_l2_3_robust	.044
298	resnet_50_v1_spiking_l4	.042
299	AlexNet_SIN_fov12	.042
300	mobilenet_v2_1.0_96	.042
301	alexnet_fov16	.041
302	mehrer2020_alexnet_training_seed_01_fov16	.040
303	mobilenet_v2_0.5_128	.038
304	alexnet_training_seed_05	.037
305	alexnet_training_seed_01	.037
306	alexnet_training_seed_01_fov4	.037
307	alexnet_training_seed_01_fov12	.037
308	alexnet_training_seed_01_fov16	.037
309	mobilenet_v1_0.25_160	.035
310	imagenet_l2_10_0	.035
311	mobilenet_v1_0.5_160	.033
312	resnet50-vicregl0p75	.032
313	AlexNet_SIN_fov16	.031
314	alexnet_linf_8_robust	.029
315	alexnet_robust_correct	.023
316	resnet-50_untrained	.021
317	alexnet_training_seed_06	.018
318	deit_small_imagenet_100_seed-0	.018
319	alexnet_training_seed_03	.016
320	resnet50-vicreg	.015
321	resnet50_FractalDB	.012
322	artResNet18_1	.011
323	alexnet_training_seed_07	.011
324	resnet50-vicregl0p9	.009
325	alexnet_training_seed_02	.009
326	alexnet_training_seed_04	.009
327	alexnet_training_seed_08	.009
328	alexnet_training_seed_10	.009
329	mobilenet_v1_0.25_128	.008
330	deit_small_imagenet_10_seed-0	.008
331	deit_small_imagenet_1_seed-0	.008
332	convnext_small_imagenet_10_seed-0	.007
333	resnet50_imagenet_10_seed-0	.007
334	mobilevit_small	.007
335	resnet50_imagenet_1_seed-0	.006
336	resnet50-barlow	.004
337	resnet50-simclr-vissl	.003
338	barlow-twins-resnet50	.002
339	resnet_50_v1_spiking_l3	.001
340	alexnet_training_seed_09	.001
341	resnet-18-LC_w_sh_100_iter_conv_init_m
342	ViT-B/32
343	BiT-M-R50x3
344	BiT-M-R50x1
345	BiT-M-R152x2
346	resnet-18-LC_w_sh_1_iter_conv_init_m
347	resnet-18-LC_w_sh_10_iter_m
348	resnet-18-LC_w_sh_100_iter_m
349	resnet-18-LC_w_sh_10_iter_conv_init_m
350	FrankRobWobv0
351	resnet-18-LC_w_sh_1_iter_m
352	0.5x_resnet-18_LC
353	CORnetZ_CIFAR10
354	resnet18-local_aggregation
355	resnet18-deepcluster
356	r3m_resnet18
357	CORnet-Z
358	vggface
359	my-model
360	resnet18-instance_recognition
361	0.5x_resnet-18_LC_w_sh_10_iter
362	r3m_resnet50
363	r3m_resnet34
364	resnet-18-LC_m
365	r3m_resnet50_nocrop
366	resnet18-supervised
367	resnet-18-LC_1st_conv_m
368	resnet-18-LC_conv_init_m
369	resnet18-contrastive_multiview
370	0.5x_resnet-18
371	resnet18-colorization
372	RN50
373	0.5x_resnet-18_LC_w_sh_100_iter
374	RN50
375	resnet18-relative_position
376	resnet18-autoencoder
377	resnet18-simclr
378	ViT_L_32
379	ViT_B_32
380	resnet18-depth_prediction
381	ViT_B_16
382	r3m_resnet34_nocrop
383	resnet18-contrastive_predictive
384	resnet-18-LC_untrained
385	resnet-18_untrained
386	resnet-50x2_untrained
387	dcgan
388	unet_entire
389	v1-pyr-nodown
390	CORnetZ_CIFAR10_bs32_20_04
391	omnivore_swinT
392	pixels
393	dorinet_cornet_z
394	my-model
395	openclip
396	resnet50-cifar
397	resnet50_pretrained_with_retinal_waves
398	resnet50_ImageNet
399	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
400	ReAlnet07_ALL
401	yudixie_resnet50_imagenet1kpret_0_240312
402	yudixie_resnet50_imagenet1kpret_0_240908
403	yudixie_resnet50_random_0_240908
404	yudixie_resnet50_cat_obj_class_all_latents_0_240908
405	yudixie_resnet50_category_class_0_240908
406	resnet18_imagenet21kP
407	ConvLSTM
408	PredRNN
409	yudixie_resnet50_distance_reg_0_240908
410	SimVP
411	TAU
412	MIM
413	hmax
414	inception_v3_pytorch
415	yolos_tiny
416	yudixie_resnet18_translation_reg_0_240719
417	yudixie_resnet18_distance_reg_0_240719
418	compact_resnet50_V4
419	yudixie_resnet18_rotation_reg_0_240719
420	briaai_rmbg_1_4
421	vit_base_patch14_dinov2-lvd142m
422	vit_base_patch16_dinov3-lvd1689m
423	ReAlnet01_cornet_fov4
424	compact_resnet50_IT
425	resnet50_ecoset_full
426	compact_resnet50_robust_V4
427	resnet101_ecoset_full
428	yudixie_resnet50_distance_translation_0_240908
429	yudixie_resnet50_rotation_reg_0_240908
430	resnet152_ecoset_full
431	yudixie_resnet18_distance_translation_0_240719
432	yudixie_resnet18_translation_rotation_0_240719
433	yudixie_resnet18_distance_rotation_0_240719
434	yudixie_resnet18_category_class_0_240719
435	ReAlnet05_cornet
436	compact_vgg19_V4
437	yudixie_resnet18_cat_obj_class_all_latents_0_240719
438	resnet-18_test_m
439	yudixie_resnet18_distance_translation_rotation_0_240719
440	yudixie_resnet18_object_class_0_240719
441	yudixie_resnet18_imagenet1kpret_0_240719
442	SeLaVi-AVE
443	r3d_18
444	ReAlnet01_cornet_fov16
445	compact_vgg19_IT
446	yudixie_resnet50_translation_reg_0_240908
447	yudixie_resnet50_translation_rotation_0_240908
448	ReAlnet01_ALL
449	mc3_18
450	ReAlnet07_cornet
451	s3d
452	mvit_v1_b
453	ReAlnet03_ALL
454	VOneCORnet-S
455	compact_cornets_V4
456	omnivore_swinB
457	ReAlnet04_ALL
458	SeLaVi-Kinetics400
459	ReAlnet09_cornet
460	SeLaVi-VGG-Sound
461	compact_cornets_IT
462	ReAlnet05_ALL
463	omnivore_swinS
464	ReAlnet06_ALL
465	mvit_v2_s
466	SeLaVi-Kinetics-Sound
467	compact_resnet50_robust_IT
468	ReAlnet10_cornet
469	r2plus1d_18
470	ReAlnet08_ALL
471	yudixie_resnet18_random_0_240719
472	yudixie_resnet50_distance_rotation_0_240908
473	ReAlnet02_cornet
474	yudixie_resnet50_distance_translation_rotation_0_240908
475	ReAlnet09_ALL
476	ReAlnet04_cornet
477	resnet50_primary_visual_cortex
478	yudixie_resnet50_object_class_0_240908
479	ReAlnet10_ALL
480	ReAlnet02_ALL
481	vit_base_patch14_reg4_dinov2-lvd142m
482	ReAlnet01_cornet
483	ReAlnet01_cornet_fov12
484	ReAlnet03_cornet
485	ReAlnet06_cornet
486	ReAlnet08_cornet
487	resnet18_ecoset_full
488	resnet34_ecoset_full
489	resnet18_fair
490	pr1_stl10_disentangled_alpha04
491	predictive_coding_pc
492	yudixie_wbh_object_class_scaling_0415_run_0
493	yudixie_wbh_object_class_scaling_0415_run_3
494	yudixie_wbh_object_class_scaling_0415_imagenet
495	yudixie_wbh_object_class_scaling_0415_run_2
496	yudixie_wbh_object_class_scaling_0415_run_1
497	deepeisnn_ei_cifar10_vgg19
498	deepeisnn_ei_cifar10_resnet18
499	deepeisnn_ei_imagenet_resnet18
500	dinov2_vitl14_reg_lc_featread
501	gabor_filter_entropy_4x4
502	gabor_filter_mean_abs_4x4_v2
503	gabor_filter_entropy_4x4_v2
504	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