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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021contrast-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnext101_32x16d_wsl	.771
2	effnetv2m_custom384	.731
3	CLIP_resnet50	.718
4	CLIP_resnet50_float32	.718
5	resnet-152_v2-tf	.709
6	CLIP_ViT-B_32	.708
7	SWSL_resnet50	.696
8	nasnet_large-tf	.688
9	resnet50_st_wzc_seed7_2_323	.676
10	ViT_B_16_imagenet1k	.658
11	resnet_50_v2	.647
12	ViT_L_32_imagenet1k	.635
13	effnetb1_272x240	.632
14	CLIP-RN50	.631
15	resnet50_st_wzc_noseed_2_323	.625
16	inception_v4	.623
17	resnext101_32x8d_wsl	.621
18	ViT_L_16_imagenet1k	.617
19	pnasnet_large-tf	.617
20	inception_v4-tf	.606
21	resnet50_ewconplus_wzc_seed5_2__323	.602
22	nasnet_large	.598
23	vision_transformer_vit_large_patch16_224	.590
24	resnet50_ewconplus_wzc_seed2_2__323	.584
25	resnext101_32x48d_wsl	.581
26	resnext101_32x32d_wsl	.577
27	xception-keras	.574
28	convnext_base_fb_in1k_gram_aligned_dinov3	.570
29	vit_large_patch14_clip_224:laion2b_ft_in1k	.568
30	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.565
31	resnet-50_v2-tf	.563
32	resnet_101_v2	.562
33	resnet50_ewconplus_wzc_2_323	.562
34	resnet50_ewconplus_noseed_2_323	.557
35	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.555
36	pnasnet_large_pytorch	.554
37	resnet50_ewconplus_wzc_seed3_2_323	.550
38	SWSL_resnext101_32x8d	.547
39	deit3_base_patch16_224_fb_in22k_ft_in1k	.546
40	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.544
41	pnasnet_large_halfPrecision	.544
42	pnasnet_large	.544
43	resnet50_st_wzc_seed5_2_323	.541
44	xception	.540
45	resnet50_st_wzc_seed3_2_323	.537
46	ViT_B_32_imagenet1k	.533
47	resnet50_st_wzc_2_323	.514
48	resnet50_ewconplus_wzc_seed6_2_323	.513
49	inception_v3-tf	.511
50	cvt_cvt-13-224-in1k_4_LucyV4	.507
51	focalnet_tiny_lrf_in1k	.506
52	convnext_base_fb_in1k	.506
53	convnext_femto_ols:d1_in1k	.503
54	convnext_tiny:in12k_ft_in1k	.503
55	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.499
56	resnet-152_v2_pytorch	.496
57	tv_efficientnet-b1	.492
58	resnet50_ewconplus_wzc	.490
59	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.481
60	convnext_tiny_sup	.478
61	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.476
62	cvt_cvt-21-224-in1k_4_LucyV4	.460
63	convnext_small_imagenet_100_seed-0	.456
64	convnext_small_imagenet_full_seed-0	.452
65	cvt_cvt-21-384-in1k_4_LucyV4	.445
66	convnext_tiny_imagenet_full_seed-0	.433
67	resnet50_st_wzc_2	.432
68	cvt_cvt-13-384-in1k_4_LucyV4	.431
69	resnet50-VITO-8deg-cc	.430
70	vit_relpos_base_patch16_clsgap_224:sw_in1k	.429
71	vit_base_patch16_clip_224:openai_ft_in1k	.418
72	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.416
73	vit_large_patch14_clip_336:laion2b_ft_in1k	.413
74	resnet50-moclr8deg	.403
75	resnet50_moco_v2	.400
76	resnet101	.399
77	BiT-S-R50x3	.397
78	convnext_base_fb_in22k_ft_in1k	.390
79	resnet_152_v2	.376
80	antialias-resnet152	.370
81	resnet50_byol	.367
82	inception_v3	.351
83	convnext_base:clip_laiona_augreg_ft_in1k_384	.349
84	antialiased-rnext101_32x8d	.347
85	convnext_base_imagenet_full_seed-0	.347
86	resnet50	.345
87	fixres_resnext101_32x48d_wsl	.344
88	resnet152_imagenet_full	.340
89	resnet50_imagenet_full	.335
90	cv_18_dagger_408_pretrained	.332
91	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.329
92	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.328
93	densenet-169-keras	.324
94	convnext_large_imagenet_full_seed-0	.322
95	densenet-121-keras	.317
96	deit_base_imagenet_full_seed-0	.309
97	antialiased-r50	.308
98	deit_small_imagenet_full_seed-0	.308
99	densenet-201-keras	.302
100	resnet_101_v1	.301
101	BiT-S-R152x4	.294
102	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.290
103	blt_vs	.283
104	resnet34_imagenet_full	.276
105	resnet50_random_l2_perturb	.274
106	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.271
107	AlexNet_SIN_fov4	.270
108	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.269
109	inception_v2-tf	.265
110	BiT-S-R101x3	.261
111	resnet50_simclr	.260
112	densenet-169	.254
113	densenet-201	.253
114	densenet_201_pytorch	.253
115	densenet-121	.250
116	resnet_152_v1	.246
117	inception_v1-tf	.242
118	vit_large_patch14_clip_224:openai_ft_in1k	.241
119	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.240
120	nasnet_mobile	.237
121	resnet50-SIN_IN_IN	.229
122	resnet_SIN_IN_FT_IN	.229
123	Res2Net50_26w_4s	.228
124	resnet-50-pytorch	.221
125	resnet50-sup	.221
126	resnet50_tutorial	.221
127	resnet_50_v1	.221
128	grcnn_109	.220
129	efficientnet_b0	.219
130	resnet-101_v1-tf	.216
131	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.215
132	deit_large_imagenet_full_seed-0	.206
133	convnext_large:fb_in22k_ft_in1k	.204
134	alexnet_fov4	.204
135	AT_efficientnet-b2	.200
136	AdvProp_efficientnet-b2	.200
137	resnet50-SIN_IN	.193
138	BiT-S-R152x2	.191
139	resnet_50_v1_spiking	.190
140	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.186
141	grcnn	.184
142	resnet-50_v1-tf	.182
143	resnet-152_v1-tf	.182
144	BiT-S-R101x1	.181
145	AdvProp_efficientnet-b6	.179
146	vgg_19	.178
147	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.176
148	mobilenet_v2_0_5_224	.176
149	resnet101_imagenet_full	.171
150	vonegrcnn_52e_full	.171
151	efficientnet-b7	.166
152	efficientnet_b2_imagenet_full	.166
153	mobilenet_v2_1-4_224_pytorch	.166
154	mobilenet_v2_1_4_224	.166
155	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.163
156	BiT-S-R50x1	.158
157	nasnet_mobile-tf	.158
158	alexnet_training_seed_02	.156
159	alexnet_training_seed_04	.156
160	alexnet_training_seed_10	.156
161	vgg-16-keras	.155
162	alexnet_random_linf8_perturb	.155
163	AdvProp_efficientnet-b4	.155
164	AT_efficientnet-b4	.155
165	ReAlnet05	.154
166	mobilenet_v2_0.5_224-tf	.152
167	mobilenet_v1_0.25_128	.152
168	vonegrcnn_47e	.151
169	alexnet_random_l2_3_perturb	.148
170	ReAlnet02	.147
171	resnet50-vitoimagevidnet8	.147
172	resnet-18	.147
173	convnext_xlarge:fb_in22k_ft_in1k	.145
174	ReAlnet04	.144
175	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.143
176	mobilenet_v2_1_0_224	.140
177	voneresnet-50-non_stochastic	.140
178	AdvProp_efficientnet-b7	.139
179	cornet_s	.139
180	ReAlnet08	.135
181	ReAlnet03	.133
182	alexnet_reduced_aliasing_early_checkpoint	.131
183	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.131
184	vonegrcnn_52e_full	.125
185	alexnet_ks_torevert	.123
186	alexnet	.123
187	texture_shape_resnet50_trained_on_SIN	.122
188	resnet50_l2_3_robust	.121
189	vgg_16	.121
190	resnet50-meshes-lt-100-original-scratch	.120
191	mobilenet_v1_0.25_192	.120
192	vonegrcnn_62e_nobn	.120
193	mobilenet_v2_0.5_128	.119
194	voneresnet-50-robust	.119
195	resnet50_linf_4_robust	.119
196	mobilevit_small	.118
197	alexnet_fov16	.118
198	alexnet_robust_correct	.117
199	resnet50_linf_8_robust	.116
200	alexnet_l2_3_robust	.115
201	vgg-19-keras	.114
202	vonegrcnn_62e_nobn	.113
203	resnet-50-robust	.113
204	imagenet_l2_3_0	.113
205	resnet50_robust_l2_eps3	.113
206	resnet50_robust_l2_eps1	.113
207	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.110
208	alexnet_linf_8_robust	.109
209	imagenet_l2_10_0	.108
210	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.108
211	ReAlnet09	.107
212	mobilenet_v2_1_0_128	.107
213	ReAlnet07	.107
214	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.106
215	resnet50_imagenet_10_seed-0	.106
216	deit_small_imagenet_10_seed-0	.106
217	deit_small_imagenet_1_seed-0	.106
218	mobilenet_v2_0_5_192	.105
219	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.103
220	ReAlnet06	.102
221	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.102
222	vonealexnet_gaussian_noise_std4_fixed	.101
223	alexnet_training_seed_05	.101
224	alexnet_training_seed_01	.101
225	alexnet_training_seed_01_fov4	.101
226	alexnet_training_seed_01_fov12	.101
227	alexnet_training_seed_01_fov16	.101
228	barlow-twins-resnet50	.099
229	ReAlnet10	.097
230	alexnet_fov12	.097
231	vonegrcnn_47e	.096
232	konkle_alexnetgn_ipcl_ref01_primary_model	.094
233	resnet50-vicreg	.094
234	mobilenet_v1_0.5_192	.094
235	mobilenet_v2_1.0_96	.093
236	mobilenet_v2_0.35_128	.091
237	mobilenet_v2_1_0_160	.088
238	mobilenet_v2_0.35_192	.088
239	resnet18_imagenet_full	.087
240	resnet50-SIN	.085
241	mobilenet_v1_0.5_128	.083
242	mobilenet_v1_1.0_224	.081
243	mobilenet_v2_0.35_160	.081
244	squeezenet1_0	.081
245	mobilenet_v2_1.0_128-tf	.080
246	AdvProp_efficientnet-b8	.079
247	resnet50_eMMCR_Vanilla	.079
248	alexnet_early_checkpoint	.075
249	inception_v1	.074
250	resnet50-vicregl0p9	.072
251	mobilenet_v1_0.5_160	.072
252	mobilenet_v2_1_0_192	.071
253	mobilenet_v2_1.0_160-tf	.070
254	resnet50_FractalDB	.070
255	ReAlnet01	.070
256	mobilenet_v2_1.0_224-tf	.070
257	efficientnet_b0_imagenet_full	.069
258	voneresnet-50	.069
259	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.064
260	alexnet_training_seed_09	.058
261	mobilenet_v2_1.0_192-tf	.056
262	alexnet_training_seed_07	.054
263	CORnet-S	.052
264	mobilenet_v2_0.5_192-tf	.052
265	mobilenet_v2_1.4_224-tf	.050
266	mobilenet_v1_0.75_160	.050
267	resnet_50_v1_spiking_l4	.049
268	mobilenet_v2_0.5_160	.049
269	resnet50_imagenet_1_seed-0	.048
270	resnet-34	.047
271	mobilenet_v1_1.0_160	.046
272	mobilenet_v1_1.0_192	.045
273	resnet50-vicregl0p75	.044
274	efficientnet_b1_imagenet_full	.044
275	AdvProp_efficientnet-b0	.044
276	mobilenet_v2_0_75_192	.044
277	custom_model_cv_18_dagger_408	.044
278	mobilenet_v2_0.35_224	.043
279	mobilenet_v1_0.5_224	.043
280	resnet_50_v1_spiking_l3	.038
281	resnet50-barlow	.037
282	resnet50_imagenet_100_seed-0	.035
283	resnet_50_v1_spiking_l4a	.033
284	mobilenet_v2_0_75_160	.033
285	mobilenet_v1_0.75_128	.033
286	mobilenet_v2_0.75_128	.032
287	my-model	.030
288	AlexNet_SIN_fov12	.027
289	mobilenet_v2_1_3_224	.025
290	convnext_small_imagenet_10_seed-0	.025
291	mobilenet_v1_0.75_192	.024
292	mobilenet_v2_0_75_224	.024
293	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.024
294	AlexNet_SIN_fov16	.023
295	AlexNet_SIN	.022
296	alexnet_training_seed_03	.022
297	mobilenet_v1_0.25_224	.022
298	deit_small_imagenet_100_seed-0	.021
299	mobilenet_v2_0.75_96	.020
300	squeezenet1_1	.020
301	convnext_small_imagenet_1_seed-0	.020
302	alexnet_training_seed_08	.020
303	mobilenet_v2_1.3_224-tf	.019
304	mobilenet_v2_0.75_160-tf	.018
305	artResNet18_1	.018
306	resnet50_random_linf8_perturb	.017
307	mobilenet_v2_0.5_96	.017
308	mobilenet_v1_1.0_128	.016
309	mobilenet_v1_0.25_160	.016
310	alexnet_training_seed_06	.016
311	texture_shape_alexnet_trained_on_SIN	.015
312	mobilenet_v2_0.35_96	.015
313	mobilenet_v2_0.75_224-tf	.014
314	mobilenet_v2_0.75_192-tf	.013
315	regnet_y_400mf	.013
316	resnet-50_untrained	.012
317	resnet50-meshes-lt-100-original-pretrained	.012
318	mobilenet_v1_0.75_224	.011
319	resnet50-simclr-vissl	.008
320	shufflenet_v2_x1_0	.006
321	0.5x_resnet-18_LC_w_sh_1_iter	.006
322	resnet-18-LC_w_sh_100_iter_conv_init_m
323	ViT-B/32
324	BiT-M-R50x3
325	BiT-M-R50x1
326	BiT-M-R152x2
327	resnet-18-LC_w_sh_1_iter_conv_init_m
328	resnet-18-LC_w_sh_1_iter_m
329	resnet-18-LC_w_sh_10_iter_m
330	resnet-18-LC_w_sh_100_iter_m
331	resnet-18-LC_w_sh_10_iter_conv_init_m
332	FrankRobWobv0
333	resnet18-local_aggregation
334	0.5x_resnet-18_LC
335	CORnetZ_CIFAR10
336	resnet18-deepcluster
337	resnet18-colorization
338	r3m_resnet18
339	CORnet-Z
340	resnet18-instance_recognition
341	my-model
342	vggface
343	0.5x_resnet-18_LC_w_sh_10_iter
344	r3m_resnet50
345	r3m_resnet34
346	resnet-18-LC_m
347	r3m_resnet50_nocrop
348	resnet18-supervised
349	resnet-18-LC_1st_conv_m
350	resnet-18-LC_conv_init_m
351	resnet18-contrastive_multiview
352	0.5x_resnet-18
353	RN50
354	0.5x_resnet-18_LC_w_sh_100_iter
355	RN50
356	resnet18-relative_position
357	resnet18-autoencoder
358	resnet18-simclr
359	ViT_L_32
360	ViT_B_32
361	resnet18-depth_prediction
362	ViT_B_16
363	r3m_resnet34_nocrop
364	hmax
365	resnet18-contrastive_predictive
366	omnivore_swinT
367	resnet-18-LC_untrained
368	resnet-18_untrained
369	resnet-50x2_untrained
370	dcgan
371	v1-pyr-nodown
372	unet_entire
373	CORnetZ_CIFAR10_bs32_20_04
374	pixels
375	dorinet_cornet_z
376	resnet50
377	openclip
378	resnet50-cifar
379	resnet50_pretrained_with_retinal_waves
380	resnet50_ImageNet
381	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
382	yudixie_resnet50_random_0_240908
383	yudixie_resnet50_imagenet1kpret_0_240908
384	yudixie_resnet50_cat_obj_class_all_latents_0_240908
385	yudixie_resnet50_object_class_0_240908
386	yudixie_resnet50_category_class_0_240908
387	resnet18_imagenet21kP
388	ConvLSTM
389	PredRNN
390	yudixie_resnet50_distance_reg_0_240908
391	SimVP
392	TAU
393	MIM
394	vit_base_patch14_reg4_dinov2-lvd142m
395	ReAlnet01_cornet
396	inception_v3_pytorch
397	yolos_tiny
398	yudixie_resnet50_imagenet1kpret_0_240312
399	yudixie_resnet18_translation_reg_0_240719
400	briaai_rmbg_1_4
401	yudixie_resnet18_distance_reg_0_240719
402	ReAlnet03_cornet
403	yudixie_resnet18_rotation_reg_0_240719
404	yudixie_resnet18_imagenet1kpret_0_240719
405	eBarlow_lmda_02_1000ep
406	compact_resnet50_V4
407	ReAlnet02_cornet
408	vit_base_patch16_dinov3-lvd1689m
409	resnet18_ecoset_full
410	resnet34_ecoset_full
411	vit_base_patch14_dinov2-lvd142m
412	VOneCORnet-S
413	resnet50_ecoset_full
414	compact_resnet50_robust_V4
415	resnet101_ecoset_full
416	ReAlnet01_cornet_fov12
417	yudixie_resnet50_distance_translation_0_240908
418	yudixie_resnet18_distance_translation_0_240719
419	ReAlnet04_cornet
420	yudixie_resnet18_translation_rotation_0_240719
421	yudixie_resnet18_category_class_0_240719
422	yudixie_resnet50_distance_rotation_0_240908
423	compact_vgg19_V4
424	compact_resnet50_IT
425	ReAlnet05_cornet
426	yudixie_resnet50_rotation_reg_0_240908
427	yudixie_resnet18_random_0_240719
428	yudixie_resnet18_cat_obj_class_all_latents_0_240719
429	resnet-18_test_m
430	ReAlnet01_cornet_fov4
431	SeLaVi-AVE
432	yudixie_resnet18_object_class_0_240719
433	yudixie_resnet50_translation_reg_0_240908
434	ReAlnet06_cornet
435	ReAlnet01_cornet_fov16
436	compact_vgg19_IT
437	r3d_18
438	yudixie_resnet50_translation_rotation_0_240908
439	mc3_18
440	ReAlnet01_ALL
441	ReAlnet07_cornet
442	s3d
443	mvit_v1_b
444	aughost_fair_resnet18
445	ReAlnet02_ALL
446	ReAlnet08_cornet
447	compact_cornets_V4
448	omnivore_swinB
449	ReAlnet04_ALL
450	SeLaVi-Kinetics400
451	ReAlnet09_cornet
452	SeLaVi-VGG-Sound
453	compact_cornets_IT
454	ReAlnet05_ALL
455	SeLaVi-Kinetics-Sound
456	omnivore_swinS
457	r2plus1d_18
458	mvit_v2_s
459	compact_resnet50_robust_IT
460	ReAlnet10_cornet
461	resnet152_ecoset_full
462	ReAlnet07_ALL
463	yudixie_resnet18_distance_rotation_0_240719
464	ReAlnet08_ALL
465	yudixie_resnet50_distance_translation_rotation_0_240908
466	yudixie_resnet18_distance_translation_rotation_0_240719
467	ReAlnet09_ALL
468	resnet50_primary_visual_cortex
469	ReAlnet10_ALL
470	ReAlnet03_ALL
471	ReAlnet06_ALL
472	resnet18_fair
473	pr1_stl10_disentangled_alpha04
474	predictive_coding_pc
475	yudixie_wbh_object_class_scaling_0415_run_0
476	yudixie_wbh_object_class_scaling_0415_run_3
477	yudixie_wbh_object_class_scaling_0415_imagenet
478	yudixie_wbh_object_class_scaling_0415_run_2
479	yudixie_wbh_object_class_scaling_0415_run_1
480	deepeisnn_ei_cifar10_vgg19
481	deepeisnn_ei_cifar10_resnet18
482	deepeisnn_ei_imagenet_resnet18

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: Geirhos2021contrast

Metric: error_consistency