Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021sketch-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.776
2	vit_large_patch14_clip_224:openai_ft_in1k	.776
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.746
4	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.742
5	vit_large_patch14_clip_336:laion2b_ft_in1k	.734
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.700
7	SWSL_resnext101_32x8d	.699
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.678
9	vit_large_patch14_clip_224:laion2b_ft_in1k	.669
10	CLIP_resnet50	.666
11	CLIP_resnet50_float32	.666
12	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.663
13	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.658
14	convnext_base:clip_laiona_augreg_ft_in1k_384	.658
15	CLIP-RN50	.630
16	convnext_xlarge:fb_in22k_ft_in1k	.594
17	vit_base_patch16_clip_224:openai_ft_in1k	.585
18	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.578
19	fixres_resnext101_32x48d_wsl	.576
20	CLIP_ViT-B_32	.559
21	convnext_large:fb_in22k_ft_in1k	.556
22	resnext101_32x16d_wsl	.539
23	resnext101_32x48d_wsl	.512
24	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.481
25	SWSL_resnet50	.461
26	resnext101_32x32d_wsl	.460
27	effnetv2m_custom384	.452
28	resnext101_32x8d_wsl	.425
29	vision_transformer_vit_large_patch16_224	.421
30	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.382
31	convnext_tiny:in12k_ft_in1k	.336
32	cvt_cvt-13-384-in1k_4_LucyV4	.331
33	vit_relpos_base_patch16_clsgap_224:sw_in1k	.314
34	cvt_cvt-21-384-in1k_4_LucyV4	.293
35	convnext_large_imagenet_full_seed-0	.287
36	effnetb1_272x240	.283
37	convnext_small_imagenet_full_seed-0	.278
38	convnext_tiny_imagenet_full_seed-0	.276
39	convnext_base_imagenet_full_seed-0	.274
40	focalnet_tiny_lrf_in1k	.274
41	cv_18_dagger_408_pretrained	.271
42	pnasnet_large	.267
43	resnet_152_v2	.253
44	convnext_femto_ols:d1_in1k	.247
45	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.245
46	cvt_cvt-13-224-in1k_4_LucyV4	.242
47	resnet_50_v2	.242
48	cvt_cvt-21-224-in1k_4_LucyV4	.234
49	pnasnet_large-tf	.232
50	nasnet_large	.221
51	resnet-152_v2_pytorch	.220
52	resnet-152_v2-tf	.220
53	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.213
54	inception_v4	.212
55	inception_v3	.207
56	resnet_101_v2	.205
57	xception-keras	.204
58	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.202
59	convnext_tiny_sup	.198
60	deit_large_imagenet_full_seed-0	.198
61	resnet101	.191
62	resnet152_imagenet_full	.177
63	inception_v3-tf	.172
64	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.169
65	vgg_19	.163
66	resnet101_imagenet_full	.163
67	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.161
68	resnet50_random_l2_perturb	.161
69	nasnet_large-tf	.160
70	antialias-resnet152	.159
71	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.157
72	resnet_101_v1	.155
73	resnet50_imagenet_full	.155
74	deit_base_imagenet_full_seed-0	.153
75	inception_v4-tf	.153
76	resnet50-VITO-8deg-cc	.149
77	densenet-121-keras	.147
78	resnet-50_v2-tf	.145
79	AdvProp_efficientnet-b6	.143
80	resnet50_ewconplus_wzc	.143
81	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.142
82	densenet-121	.141
83	antialiased-rnext101_32x8d	.139
84	AdvProp_efficientnet-b4	.138
85	AT_efficientnet-b4	.138
86	resnet50_random_linf8_perturb	.136
87	resnet50	.135
88	efficientnet_b0	.132
89	resnet_152_v1	.131
90	resnet_50_v1_spiking	.127
91	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.127
92	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.125
93	efficientnet-b7	.125
94	efficientnet_b0_imagenet_full	.125
95	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.124
96	densenet-169-keras	.124
97	densenet-201	.121
98	grcnn_109	.120
99	Res2Net50_26w_4s	.119
100	densenet-169	.119
101	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.119
102	densenet-201-keras	.118
103	resnet50_byol	.118
104	cornet_s	.117
105	efficientnet_b2_imagenet_full	.117
106	AdvProp_efficientnet-b7	.116
107	AT_efficientnet-b2	.115
108	AdvProp_efficientnet-b2	.115
109	antialiased-r50	.115
110	BiT-S-R101x3	.114
111	resnet50-SIN_IN_IN	.114
112	resnet_SIN_IN_FT_IN	.114
113	resnet-34	.113
114	custom_model_cv_18_dagger_408	.112
115	resnet18_imagenet_full	.112
116	mobilenet_v2_1_0_192	.112
117	resnet34_imagenet_full	.111
118	convnext_small_imagenet_100_seed-0	.111
119	BiT-S-R152x4	.111
120	BiT-S-R50x3	.110
121	vgg_16	.109
122	resnet-152_v1-tf	.107
123	mobilenet_v2_1_0_224	.105
124	nasnet_mobile-tf	.104
125	mobilenet_v2_1_3_224	.104
126	resnet50_tutorial	.103
127	resnet_50_v1	.103
128	resnet-50-pytorch	.103
129	resnet50-sup	.103
130	deit_small_imagenet_full_seed-0	.102
131	BiT-S-R50x1	.102
132	resnet50-SIN_IN	.101
133	tv_efficientnet-b1	.101
134	grcnn	.099
135	mobilenet_v2_1.4_224-tf	.098
136	xception	.097
137	voneresnet-50-non_stochastic	.097
138	nasnet_mobile	.097
139	ViT_B_16_imagenet1k	.095
140	inception_v1	.095
141	efficientnet_b1_imagenet_full	.094
142	resnet50-moclr8deg	.093
143	ViT_L_32_imagenet1k	.092
144	ReAlnet06	.091
145	mobilenet_v2_0_5_224	.091
146	ReAlnet01	.090
147	mobilenet_v2_1.3_224-tf	.090
148	mobilenet_v1_1.0_224	.088
149	resnet50_moco_v2	.088
150	inception_v2-tf	.088
151	ReAlnet03	.088
152	resnet50-vitoimagevidnet8	.086
153	resnet-101_v1-tf	.084
154	BiT-S-R152x2	.083
155	ReAlnet04	.082
156	ReAlnet02	.080
157	CORnet-S	.078
158	mobilenet_v2_1_0_160	.077
159	mobilenet_v2_0_75_224	.076
160	mobilenet_v1_1.0_192	.075
161	ReAlnet09	.075
162	inception_v1-tf	.073
163	vonegrcnn_52e_full	.073
164	mobilenet_v2_1.0_224-tf	.072
165	resnet-18	.072
166	mobilenet_v1_1.0_160	.070
167	ReAlnet07	.070
168	ReAlnet05	.070
169	ReAlnet08	.069
170	blt_vs	.068
171	vonegrcnn_52e_full	.068
172	vonegrcnn_62e_nobn	.068
173	AdvProp_efficientnet-b8	.068
174	resnet-50_v1-tf	.067
175	ViT_B_32_imagenet1k	.067
176	ReAlnet10	.067
177	regnet_y_400mf	.066
178	mobilenet_v2_0_5_192	.066
179	mobilenet_v2_1-4_224_pytorch	.064
180	mobilenet_v2_1_4_224	.064
181	vonegrcnn_62e_nobn	.064
182	vgg-16-keras	.063
183	resnet_50_v1_spiking_l4a	.063
184	vonegrcnn_47e	.063
185	mobilenet_v2_1.0_192-tf	.062
186	voneresnet-50	.062
187	vonegrcnn_47e	.061
188	mobilenet_v2_0_75_160	.060
189	mobilenet_v2_1.0_160-tf	.058
190	mobilenet_v1_0.75_160	.058
191	mobilenet_v2_0.75_160-tf	.057
192	BiT-S-R101x1	.057
193	resnet50_linf_4_robust	.056
194	mobilenet_v2_0.75_224-tf	.056
195	mobilenet_v2_1_0_128	.055
196	mobilenet_v2_0_75_192	.055
197	squeezenet1_0	.055
198	mobilenet_v1_0.5_224	.054
199	mobilenet_v2_0.35_160	.053
200	mobilenet_v1_0.75_224	.053
201	mobilenet_v2_0.5_192-tf	.053
202	squeezenet1_1	.052
203	mobilenet_v2_0.75_128	.052
204	resnet_50_v1_spiking_l4	.052
205	mobilenet_v2_0.5_224-tf	.051
206	voneresnet-50-robust	.051
207	mobilenet_v2_0.75_192-tf	.049
208	resnet50_imagenet_100_seed-0	.049
209	mobilenet_v2_0.5_160	.049
210	mobilenet_v1_0.75_192	.049
211	mobilenet_v2_0.5_128	.048
212	alexnet_reduced_aliasing_early_checkpoint	.048
213	alexnet	.047
214	mobilenet_v1_0.5_192	.047
215	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.047
216	shufflenet_v2_x1_0	.046
217	alexnet_random_l2_3_perturb	.046
218	vonealexnet_gaussian_noise_std4_fixed	.046
219	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.046
220	alexnet_random_linf8_perturb	.045
221	mobilenet_v2_0.35_192	.045
222	resnet50_l2_3_robust	.045
223	resnet50_eMMCR_Vanilla	.044
224	mobilenet_v1_0.75_128	.043
225	resnet50_robust_l2_eps1	.043
226	mobilenet_v2_1.0_96	.043
227	resnet50_linf_8_robust	.042
228	texture_shape_resnet50_trained_on_SIN	.042
229	mobilenet_v2_0.35_224	.042
230	mobilenet_v2_0.35_128	.042
231	mobilenet_v2_1.0_128-tf	.041
232	resnet50_simclr	.041
233	alexnet-baseline	.041
234	alexnet	.041
235	alexnet	.041
236	alexnet	.041
237	alexnet	.041
238	alexnet	.041
239	alexnet	.041
240	alexnet	.041
241	alexnet	.041
242	alexnet	.041
243	alexnet_ks_torevert	.041
244	vgg-19-keras	.040
245	alexnet_early_checkpoint	.039
246	mobilenet_v1_0.5_128	.039
247	AdvProp_efficientnet-b0	.039
248	alexnet_robust_correct	.039
249	alexnet_l2_3_robust	.038
250	mobilenet_v2_0.75_96	.038
251	mobilenet_v2_0.35_96	.038
252	alexnet_linf_8_robust	.036
253	mobilenet_v1_0.5_160	.035
254	0.5x_resnet-18_LC_w_sh_1_iter	.034
255	konkle_alexnetgn_ipcl_ref01_primary_model	.034
256	mobilenet_v1_1.0_128	.032
257	mobilenet_v2_0.5_96	.032
258	deit_small_imagenet_100_seed-0	.032
259	mobilenet_v1_0.25_192	.032
260	resnet50-vicreg	.032
261	mobilenet_v1_0.25_224	.031
262	AlexNet_SIN	.031
263	texture_shape_alexnet_trained_on_SIN	.031
264	resnet-50-robust	.030
265	imagenet_l2_3_0	.030
266	resnet50_robust_l2_eps3	.030
267	mobilenet_v1_0.25_160	.029
268	imagenet_l2_10_0	.028
269	resnet50-simclr-vissl	.026
270	deit_small_imagenet_10_seed-0	.025
271	convnext_small_imagenet_10_seed-0	.025
272	deit_small_imagenet_1_seed-0	.025
273	alexnet_training_seed_02	.024
274	alexnet_training_seed_04	.024
275	alexnet_training_seed_08	.024
276	alexnet_training_seed_10	.024
277	alexnet_training_seed_07	.024
278	alexnet_training_seed_09	.023
279	resnet_50_v1_spiking_l3	.023
280	resnet50-meshes-lt-100-original-pretrained	.023
281	resnet-50_untrained	.022
282	resnet50-SIN	.022
283	mobilenet_v1_0.25_128	.021
284	resnet50_imagenet_10_seed-0	.020
285	convnext_small_imagenet_1_seed-0	.020
286	resnet50-meshes-lt-100-original-scratch	.018
287	barlow-twins-resnet50	.014
288	resnet50-vicregl0p9	.014
289	artResNet18_1	.014
290	resnet50_FractalDB	.011
291	alexnet_training_seed_06	.009
292	alexnet_training_seed_03	.005
293	resnet50_imagenet_1_seed-0	.003
294	resnet50-vicregl0p75	.003
295	alexnet_training_seed_05	.002
296	alexnet_training_seed_01	.002
297	resnet50-barlow	.001
298	resnet-18-LC_w_sh_100_iter_conv_init_m
299	ViT-B/32
300	BiT-M-R50x3
301	BiT-M-R50x1
302	BiT-M-R152x2
303	resnet-18-LC_w_sh_1_iter_conv_init_m
304	resnet-18-LC_w_sh_1_iter_m
305	resnet-18-LC_w_sh_10_iter_m
306	resnet-18_test_m
307	resnet-18-LC_w_sh_100_iter_m
308	resnet-18-LC_w_sh_10_iter_conv_init_m
309	FrankRobWobv0
310	0.5x_resnet-18_LC
311	CORnetZ_CIFAR10
312	resnet18-local_aggregation
313	resnet18-deepcluster
314	r3m_resnet18
315	CORnet-Z
316	vggface
317	my-model
318	resnet18-instance_recognition
319	0.5x_resnet-18_LC_w_sh_10_iter
320	r3m_resnet50
321	r3m_resnet34
322	resnet-18-LC_m
323	r3m_resnet50_nocrop
324	resnet18-supervised
325	resnet-18-LC_1st_conv_m
326	resnet-18-LC_conv_init_m
327	resnet18-contrastive_multiview
328	0.5x_resnet-18
329	resnet18-colorization
330	RN50
331	0.5x_resnet-18_LC_w_sh_100_iter
332	RN50
333	resnet18-relative_position
334	resnet18-autoencoder
335	resnet18-simclr
336	omnivore_swinT
337	ViT_L_32
338	ViT_B_32
339	resnet18-depth_prediction
340	ViT_B_16
341	r3m_resnet34_nocrop
342	resnet18-contrastive_predictive
343	resnet-18-LC_untrained
344	resnet-18_untrained
345	resnet-50x2_untrained
346	dcgan
347	unet_entire
348	omnivore_swinS
349	v1-pyr-nodown
350	CORnetZ_CIFAR10_bs32_20_04
351	pixels
352	dorinet_cornet_z
353	my-model
354	resnet50
355	openclip
356	resnet50-cifar
357	resnet50_pretrained_with_retinal_waves
358	resnet50_ImageNet
359	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
360	yudixie_resnet50_random_0_240908
361	yudixie_resnet50_imagenet1kpret_0_240908
362	yudixie_resnet50_imagenet1kpret_0_240312
363	yudixie_resnet50_object_class_0_240908
364	yudixie_resnet50_category_class_0_240908
365	ConvLSTM
366	yudixie_resnet50_distance_reg_0_240908
367	PredRNN
368	SimVP
369	TAU
370	briaai_rmbg_1_4
371	MIM
372	hmax
373	densenet_201_pytorch
374	pnasnet_large_pytorch
375	ReAlnet01_cornet
376	inception_v3_pytorch
377	yolos_tiny
378	ReAlnet03_cornet
379	yudixie_resnet18_imagenet1kpret_0_240719
380	ReAlnet02_cornet
381	compact_resnet50_V4
382	resnet18_ecoset_full
383	resnet34_ecoset_full
384	resnet50_ecoset_full
385	resnet101_ecoset_full
386	compact_resnet50_robust_V4
387	ReAlnet04_cornet
388	resnet152_ecoset_full
389	yudixie_resnet50_distance_translation_0_240908
390	yudixie_resnet18_distance_translation_0_240719
391	yudixie_resnet18_translation_rotation_0_240719
392	yudixie_resnet18_distance_rotation_0_240719
393	compact_resnet50_IT
394	yudixie_resnet18_category_class_0_240719
395	yudixie_resnet50_distance_rotation_0_240908
396	ReAlnet05_cornet
397	yudixie_resnet50_rotation_reg_0_240908
398	yudixie_resnet18_random_0_240719
399	compact_vgg19_V4
400	yudixie_resnet18_distance_translation_rotation_0_240719
401	yudixie_resnet18_object_class_0_240719
402	SeLaVi-AVE
403	yudixie_resnet18_translation_reg_0_240719
404	yudixie_resnet18_distance_reg_0_240719
405	ReAlnet06_cornet
406	yudixie_resnet50_translation_reg_0_240908
407	r3d_18
408	compact_vgg19_IT
409	ReAlnet01_ALL
410	mc3_18
411	ReAlnet07_cornet
412	yudixie_resnet50_translation_rotation_0_240908
413	s3d
414	ReAlnet08_cornet
415	mvit_v1_b
416	ReAlnet02_ALL
417	yudixie_resnet18_rotation_reg_0_240719
418	omnivore_swinB
419	VOneCORnet-S
420	compact_cornets_V4
421	resnet18_imagenet21kP
422	ReAlnet03_ALL
423	ReAlnet09_cornet
424	ReAlnet04_ALL
425	SeLaVi-Kinetics400
426	compact_cornets_IT
427	SeLaVi-VGG-Sound
428	ReAlnet05_ALL
429	r2plus1d_18
430	ReAlnet06_ALL
431	ReAlnet10_cornet
432	SeLaVi-Kinetics-Sound
433	mvit_v2_s
434	yudixie_resnet50_distance_translation_rotation_0_240908
435	ReAlnet07_ALL
436	compact_resnet50_robust_IT
437	ReAlnet08_ALL
438	yudixie_resnet18_cat_obj_class_all_latents_0_240719
439	resnet50_primary_visual_cortex
440	ReAlnet09_ALL
441	yudixie_resnet50_cat_obj_class_all_latents_0_240908
442	ReAlnet10_ALL

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

0.37.

Note that scores are relative to this ceiling.

Data: Geirhos2021sketch

Metric: error_consistency