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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021cueconflict-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.943
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.938
3	convnext_xxlarge_clip	.937
4	dinov2_vitg14_reg_lc	.933
5	dinov2_vitg14_lc	.881
6	eva02_large_in22k	.873
7	vit_large_patch14_clip_224:laion2b_ft_in1k	.855
8	dinov2_vitl14_lc_res336	.846
9	dinov2_vitl14_reg_lc	.845
10	vit_large_patch14_clip_224:openai_ft_in1k	.840
11	convnext_large_clip_laion2b_finelayers	.825
12	vit_huge_clip336_laion	.816
13	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.804
14	dinov2_vitl14_lc	.804
15	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.784
16	vit_large_clip336_openai	.782
17	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.780
18	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.752
19	vit_large_patch14_clip_336:laion2b_ft_in1k	.748
20	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.740
21	convnext_large:fb_in22k_ft_in1k	.698
22	convnext_base:clip_laiona_augreg_ft_in1k_384	.686
23	vision_transformer_vit_large_patch16_224	.656
24	convnext_xlarge:fb_in22k_ft_in1k	.651
25	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.633
26	convnext_large_in22k_supervised	.628
27	fixres_resnext101_32x48d_wsl	.611
28	convnext_base_fb_in22k_ft_in1k	.600
29	resnext101_32x32d_wsl	.596
30	resnext101_32x16d_wsl	.595
31	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.571
32	resnext101_32x48d_wsl	.560
33	vit_base_patch16_clip_224:openai_ft_in1k	.560
34	SWSL_resnext101_32x8d	.546
35	resnext101_32x8d_wsl	.540
36	deit3_base_patch16_224_fb_in1k	.519
37	CLIP_ViT-B_32	.482
38	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.477
39	resnet50-VITO-8deg-cc	.451
40	effnetv2m_custom384	.448
41	cvt_cvt-13-384-in1k_4_LucyV4	.441
42	resnet-152_v2-tf	.405
43	resnet_152_v2	.402
44	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.394
45	resnet_101_v2	.393
46	SWSL_resnet50	.390
47	resnet_50_v2	.383
48	vit_relpos_base_patch16_clsgap_224:sw_in1k	.380
49	ViT_B_16_imagenet1k	.376
50	cvt_cvt-21-384-in1k_4_LucyV4	.372
51	CLIP_resnet50	.371
52	CLIP_resnet50_float32	.371
53	pnasnet_large_halfPrecision	.357
54	effnetb1_272x240	.357
55	pnasnet_large	.355
56	efficientnet_b0	.346
57	inception_v3	.345
58	ViT_L_32_imagenet1k	.344
59	xception-keras	.343
60	resnet50_ewconplus_wzc_seed5_2__323	.339
61	nasnet_large	.332
62	cv_18_dagger_408_pretrained	.328
63	pnasnet_large-tf	.327
64	convnext_femto_ols:d1_in1k	.325
65	regnety_032	.323
66	convnext_tiny_imagenet_full_seed-0	.321
67	CLIP-RN50	.317
68	pnasnet_large_pytorch	.316
69	resnet101	.316
70	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.316
71	deit3_base_patch16_224_fb_in22k_ft_in1k	.315
72	focalnet_tiny_lrf_in1k	.313
73	inception_v3-tf	.311
74	ViT_B_32_imagenet1k	.309
75	resnet152_imagenet_full	.309
76	cvt_cvt-21-224-in1k_4_LucyV4	.309
77	mehrer2020_alexnet_training_seed_01_fov4	.301
78	inception_v3_pytorch	.300
79	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.299
80	convnext_tiny:in12k_ft_in1k	.297
81	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.294
82	resnet50_st_wzc_seed7_2_323	.294
83	resnet50_ewconplus_wzc	.293
84	xception	.292
85	resnet-50_v2-tf	.292
86	convnext_base_fb_in1k	.289
87	resnet50_ewconplus_wzc_seed2_2__323	.289
88	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.284
89	convnext_large_imagenet_full_seed-0	.284
90	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.282
91	convnext_base_imagenet_full_seed-0	.278
92	resnet50-SIN_IN	.272
93	resnet_101_v1	.271
94	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.271
95	nasnet_large-tf	.266
96	resnet-152_v2_pytorch	.260
97	ijepa_vith14_linhead	.260
98	resnet50_st_wzc_seed3_2_323	.257
99	resnet50_ewconplus_wzc_seed6_2_323	.256
100	resnet_152_v1	.255
101	inception_v4	.254
102	resnet50_byol	.254
103	AlexNet_SIN_fov4	.253
104	antialias-resnet152	.253
105	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.250
106	resnet50_imagenet_full	.244
107	resnet101_imagenet_full	.242
108	resnet50_hvs_wzc	.241
109	resnet50_st_wzc_2	.241
110	antialiased-rnext101_32x8d	.240
111	AdvProp_efficientnet-b7	.238
112	resnet_50_v1_spiking	.237
113	densenet-201	.236
114	densenet_201_pytorch	.236
115	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.235
116	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.235
117	custom_model_cv_18_dagger_408	.235
118	cvt_cvt-13-224-in1k_4_LucyV4	.233
119	resnet50	.233
120	densenet-201-keras	.233
121	resnet34_imagenet_full	.233
122	AT_efficientnet-b2	.232
123	AdvProp_efficientnet-b2	.232
124	resnet50-moclr8deg	.229
125	tv_efficientnet-b1	.229
126	efficientnet-b7	.228
127	resnet50-SIN_IN_IN	.228
128	resnet_SIN_IN_FT_IN	.228
129	resnet50_tutorial	.226
130	resnet_50_v1	.226
131	resnet-50-pytorch	.226
132	resnet50-sup	.226
133	resnet50_random_l2_perturb	.220
134	AdvProp_efficientnet-b6	.219
135	Res2Net50_26w_4s	.218
136	densenet-121-keras	.213
137	AdvProp_efficientnet-b4	.213
138	AT_efficientnet-b4	.213
139	densenet-121	.212
140	mobilenet_v2_0_5_224	.211
141	mobilenet_v2_1-4_224_pytorch	.210
142	mobilenet_v2_1_4_224	.210
143	inception_v4-tf	.210
144	alexnet_fov4	.208
145	grcnn_109	.208
146	convnext_small_imagenet_full_seed-0	.206
147	convnext_base_fb_in1k_gram_aligned_dinov3	.204
148	voneresnet-50-non_stochastic	.204
149	ReAlnet04	.204
150	texture_shape_resnet50_trained_on_SIN	.202
151	resnet50_simsiam_linhead	.201
152	seresnext50_32x4d	.201
153	resnet-152_v1-tf	.196
154	eBarlow_lmda_02_1000ep	.195
155	resnet50_moco_v2	.191
156	cornet_s	.191
157	nasnet_mobile	.190
158	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.189
159	mobilenet_v2_1.4_224-tf	.189
160	resnet-101_v1-tf	.189
161	BiT-S-R152x4	.189
162	vgg_16	.188
163	ReAlnet03	.187
164	resnet18_imagenet_full	.186
165	ReAlnet09	.184
166	antialiased-r50	.182
167	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.181
168	ReAlnet01	.181
169	deit_large_imagenet_full_seed-0	.181
170	resnet-50_v1-tf	.180
171	ReAlnet10	.179
172	grcnn	.179
173	resnet50_random_linf8_perturb	.177
174	BiT-S-R101x1	.177
175	blt_vs	.177
176	CORnet-S	.175
177	resnet50_linf_4_robust	.175
178	ReAlnet08	.173
179	resnet50_linf_8_robust	.173
180	BiT-S-R50x1	.173
181	mobilenet_v2_1_0_224	.171
182	inception_v1	.167
183	densenet-169	.166
184	ReAlnet06	.166
185	mobilenet_v1_0.75_224	.165
186	texture_shape_alexnet_trained_on_SIN	.164
187	mobilenet_v2_1_0_160	.164
188	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.163
189	resnet50_byol_linhead	.163
190	BiT-S-R50x3	.163
191	resnet-18	.163
192	resnet50-vitoimagevidnet8	.162
193	voneresnet-50-robust	.162
194	resnet50_eMMCR_Vanilla	.160
195	inception_v2-tf	.160
196	deit_base_imagenet_full_seed-0	.160
197	AdvProp_efficientnet-b8	.159
198	resnet50_vicreg_linhead	.158
199	resnet50_barlowtwins_linhead	.158
200	ReAlnet05	.157
201	regnet_y_400mf	.157
202	mobilenet_v1_0.5_192	.157
203	vonealexnet_gaussian_noise_std4_fixed	.157
204	BiT-S-R152x2	.156
205	mobilenet_v1_1.0_224	.156
206	resnet50_l2_3_robust	.155
207	alexnet_reduced_aliasing_early_checkpoint	.155
208	inception_v1-tf	.154
209	alexnet_training_seed_03	.153
210	mobilenet_v2_1.0_224-tf	.153
211	ReAlnet07	.153
212	mobilenet_v2_1_3_224	.153
213	alexnet_random_linf8_perturb	.153
214	ReAlnet02	.153
215	mobilenet_v2_0.5_224-tf	.153
216	vonegrcnn_52e_full	.153
217	mobilenet_v2_1.3_224-tf	.152
218	resnet50_simclr	.152
219	densenet-169-keras	.149
220	mehrer2020_alexnet_training_seed_05	.147
221	mobilenet_v1_1.0_192	.147
222	vgg-16-keras	.146
223	mehrer2020_alexnet_training_seed_01	.146
224	0.5x_resnet-18_LC_w_sh_1_iter	.146
225	squeezenet1_1	.146
226	efficientnet_b1_imagenet_full	.145
227	vonegrcnn_47e	.144
228	resnet50_robust_l2_eps1	.144
229	resnet50-SIN	.144
230	efficientnet_b2_imagenet_full	.144
231	BiT-S-R101x3	.144
232	vgg_19	.142
233	alexnet_random_l2_3_perturb	.142
234	mobilenet_v2_0.5_96	.141
235	eicircuit_resnet18_bn_20260919	.141
236	mobilenet_v1_1.0_128	.140
237	mehrer2020_alexnet_training_seed_03	.140
238	mehrer2020_alexnet_training_seed_04	.140
239	mobilenet_v2_1.0_160-tf	.137
240	vonegrcnn_62e_nobn	.137
241	mobilenet_v1_0.75_192	.136
242	resnet-34	.136
243	mobilenet_v2_1_0_128	.135
244	AdvProp_efficientnet-b0	.135
245	alexnet_early_checkpoint	.135
246	efficientnet_b0_imagenet_full	.134
247	mobilenet_v2_0.35_128	.134
248	convnext_small_imagenet_100_seed-0	.133
249	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.133
250	mobilenet_v2_0.35_96	.133
251	konkle_alexnetgn_ipcl_ref01_primary_model	.132
252	mobilenet_v2_1.0_128-tf	.132
253	mobilenet_v1_0.25_224	.132
254	mobilenet_v2_0.75_224-tf	.132
255	AlexNet_SIN	.132
256	vonegrcnn_52e_full	.132
257	resnet-50-robust	.131
258	imagenet_l2_3_0	.131
259	resnet50_robust_l2_eps3	.131
260	mobilenet_v2_1_0_192	.130
261	alexnet_ks_torevert	.128
262	alexnet	.128
263	resnet50_simclr_linhead_01norm	.128
264	mobilenet_v2_0.5_192-tf	.128
265	resnet50_imagenet_100_seed-0	.127
266	vgg-19-keras	.127
267	vonegrcnn_62e_nobn	.127
268	mobilenet_v2_0_75_224	.125
269	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.125
270	mobilenet_v2_1.0_192-tf	.125
271	shufflenet_v2_x1_0	.123
272	mobilenet_v1_0.75_128	.122
273	voneresnet-50	.121
274	vonegrcnn_47e	.121
275	mobilenet_v2_0.75_96	.119
276	mobilenet_v2_0.5_160	.117
277	mobilenet_v1_1.0_160	.114
278	mobilenet_v1_0.25_192	.112
279	convnext_tiny_sup	.112
280	alexnet_l2_3_robust	.110
281	squeezenet1_0	.110
282	mobilenet_v2_0.5_128	.109
283	mehrer2020_alexnet_training_seed_02	.109
284	mobilenet_v2_0_75_192	.107
285	mobilenet_v2_0_5_192	.106
286	AlexNet_SIN_fov12	.104
287	mobilenet_v2_0.35_160	.102
288	mobilenet_v2_0.35_192	.102
289	mobilenet_v1_0.5_128	.102
290	mobilenet_v2_0.75_160-tf	.101
291	nasnet_mobile-tf	.101
292	mobilenet_v2_0_75_160	.098
293	mobilenet_v1_0.25_160	.098
294	mobilenet_v1_0.75_160	.097
295	deit_small_imagenet_full_seed-0	.096
296	mobilenet_v2_0.75_128	.096
297	convnext_small_imagenet_1_seed-0	.096
298	mobilenet_v2_0.35_224	.093
299	convnext_small_imagenet_10_seed-0	.091
300	deit_small_imagenet_10_seed-0	.090
301	mobilenet_v2_0.75_192-tf	.090
302	alexnet_fov12	.088
303	deit_small_imagenet_1_seed-0	.087
304	mehrer2020_alexnet_training_seed_01_fov12	.086
305	AlexNet_SIN_fov16	.083
306	mobilenet_v1_0.5_224	.083
307	resnet_50_v1_spiking_l4a	.081
308	mobilevit_small	.079
309	mobilenet_v2_1.0_96	.078
310	alexnet_training_seed_02	.068
311	alexnet_training_seed_04	.068
312	alexnet_training_seed_08	.068
313	alexnet_training_seed_10	.068
314	alexnet_training_seed_09	.067
315	alexnet_training_seed_07	.066
316	alexnet_robust_correct	.063
317	resnet_50_v1_spiking_l4	.060
318	mobilenet_v1_0.25_128	.059
319	mobilenet_v1_0.5_160	.055
320	barlow-twins-resnet50	.053
321	alexnet_training_seed_06	.050
322	resnet50-vicreg	.049
323	alexnet_fov16	.047
324	mehrer2020_alexnet_training_seed_01_fov16	.047
325	resnet50-barlow	.046
326	alexnet_linf_8_robust	.045
327	imagenet_l2_10_0	.034
328	resnet_50_v1_spiking_l3	.034
329	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.033
330	resnet50_FractalDB	.032
331	resnet50-vicregl0p9	.032
332	resnet-50_untrained	.031
333	deit_small_imagenet_100_seed-0	.028
334	artResNet18_1	.013
335	resnet50_imagenet_1_seed-0	.011
336	resnet50-simclr-vissl	.011
337	resnet50-vicregl0p75	.011
338	resnet50_imagenet_10_seed-0	.003
339	alexnet_training_seed_05	.003
340	alexnet_training_seed_01	.003
341	alexnet_training_seed_01_fov4	.003
342	alexnet_training_seed_01_fov12	.003
343	alexnet_training_seed_01_fov16	.003
344	resnet-18-LC_w_sh_100_iter_conv_init_m
345	ViT-B/32
346	BiT-M-R50x3
347	BiT-M-R50x1
348	BiT-M-R152x2
349	resnet-18-LC_w_sh_1_iter_conv_init_m
350	resnet-18-LC_w_sh_1_iter_m
351	resnet-18-LC_w_sh_10_iter_m
352	yudixie_resnet50_random_0_240908
353	resnet-18-LC_w_sh_100_iter_m
354	resnet-18-LC_w_sh_10_iter_conv_init_m
355	FrankRobWobv0
356	resnet18-local_aggregation
357	0.5x_resnet-18_LC
358	CORnetZ_CIFAR10
359	resnet18-deepcluster
360	r3m_resnet18
361	resnet18-colorization
362	CORnet-Z
363	resnet18-instance_recognition
364	my-model
365	vggface
366	0.5x_resnet-18_LC_w_sh_10_iter
367	r3m_resnet50
368	r3m_resnet34
369	resnet-18-LC_m
370	r3m_resnet50_nocrop
371	resnet18-supervised
372	resnet-18-LC_1st_conv_m
373	resnet-18-LC_conv_init_m
374	resnet18-contrastive_multiview
375	0.5x_resnet-18
376	RN50
377	0.5x_resnet-18_LC_w_sh_100_iter
378	RN50
379	resnet18-relative_position
380	resnet18-autoencoder
381	resnet18-simclr
382	ViT_L_32
383	ViT_L_16_imagenet1k
384	ViT_B_32
385	resnet18-depth_prediction
386	ViT_B_16
387	r3m_resnet34_nocrop
388	resnet18-contrastive_predictive
389	omnivore_swinT
390	resnet-18-LC_untrained
391	resnet-18_untrained
392	resnet-50x2_untrained
393	dcgan
394	v1-pyr-nodown
395	unet_entire
396	CORnetZ_CIFAR10_bs32_20_04
397	pixels
398	dorinet_cornet_z
399	my-model
400	openclip
401	resnet50-cifar
402	resnet50_pretrained_with_retinal_waves
403	resnet50_ImageNet
404	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
405	yudixie_resnet50_imagenet1kpret_0_240908
406	yudixie_resnet50_imagenet1kpret_0_240312
407	yudixie_resnet50_cat_obj_class_all_latents_0_240908
408	yudixie_resnet50_object_class_0_240908
409	yudixie_resnet50_category_class_0_240908
410	resnet18_imagenet21kP
411	ConvLSTM
412	PredRNN
413	yudixie_resnet50_distance_reg_0_240908
414	SimVP
415	briaai_rmbg_1_4
416	TAU
417	MIM
418	hmax
419	ReAlnet01_cornet
420	yolos_tiny
421	yudixie_resnet18_translation_reg_0_240719
422	ReAlnet02_cornet
423	ReAlnet03_cornet
424	yudixie_resnet18_distance_reg_0_240719
425	yudixie_resnet18_rotation_reg_0_240719
426	yudixie_resnet18_imagenet1kpret_0_240719
427	compact_resnet50_V4
428	vit_base_patch14_dinov2-lvd142m
429	vit_base_patch16_dinov3-lvd1689m
430	vit_base_patch14_reg4_dinov2-lvd142m
431	resnet18_ecoset_full
432	resnet34_ecoset_full
433	ReAlnet01_cornet_fov4
434	resnet50_ecoset_full
435	compact_resnet50_robust_V4
436	resnet101_ecoset_full
437	yudixie_resnet50_distance_rotation_0_240908
438	yudixie_resnet50_rotation_reg_0_240908
439	ReAlnet01_cornet_fov12
440	resnet152_ecoset_full
441	yudixie_resnet18_distance_translation_0_240719
442	yudixie_resnet50_distance_translation_0_240908
443	yudixie_resnet18_translation_rotation_0_240719
444	yudixie_resnet18_distance_rotation_0_240719
445	compact_vgg19_V4
446	yudixie_resnet18_category_class_0_240719
447	ReAlnet05_cornet
448	yudixie_resnet18_cat_obj_class_all_latents_0_240719
449	resnet-18_test_m
450	yudixie_resnet18_distance_translation_rotation_0_240719
451	compact_resnet50_IT
452	SeLaVi-AVE
453	ReAlnet06_cornet
454	r3d_18
455	compact_vgg19_IT
456	ReAlnet01_cornet_fov16
457	ReAlnet01_ALL
458	mc3_18
459	yudixie_resnet50_translation_rotation_0_240908
460	s3d
461	mvit_v1_b
462	ReAlnet02_ALL
463	ReAlnet03_ALL
464	compact_cornets_V4
465	VOneCORnet-S
466	ReAlnet04_ALL
467	ReAlnet09_cornet
468	SeLaVi-Kinetics400
469	SeLaVi-VGG-Sound
470	omnivore_swinB
471	compact_cornets_IT
472	SeLaVi-Kinetics-Sound
473	ReAlnet06_ALL
474	mvit_v2_s
475	omnivore_swinS
476	r2plus1d_18
477	compact_resnet50_robust_IT
478	ReAlnet10_cornet
479	ReAlnet07_ALL
480	yudixie_resnet18_object_class_0_240719
481	ReAlnet05_ALL
482	ReAlnet08_ALL
483	yudixie_resnet18_random_0_240719
484	ReAlnet09_ALL
485	yudixie_resnet50_translation_reg_0_240908
486	resnet50_primary_visual_cortex
487	yudixie_resnet50_distance_translation_rotation_0_240908
488	ReAlnet10_ALL
489	resnet18_fair
490	ReAlnet04_cornet
491	ReAlnet07_cornet
492	ReAlnet08_cornet
493	pr1_stl10_disentangled_alpha04
494	predictive_coding_pc
495	yudixie_wbh_object_class_scaling_0415_run_0
496	yudixie_wbh_object_class_scaling_0415_run_3
497	yudixie_wbh_object_class_scaling_0415_imagenet
498	yudixie_wbh_object_class_scaling_0415_run_2
499	yudixie_wbh_object_class_scaling_0415_run_1
500	deepeisnn_ei_cifar10_vgg19
501	deepeisnn_ei_cifar10_resnet18
502	deepeisnn_ei_imagenet_resnet18
503	dinov2_vitl14_reg_lc_featread
504	gabor_filter_entropy_4x4_v2
505	gabor_filter_entropy_4x4
506	gabor_filter_mean_abs_4x4_v2
507	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

0.33.

Note that scores are relative to this ceiling.

Data: Geirhos2021cueconflict

Metric: error_consistency