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