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("Geirhos2021lowpass-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	SWSL_resnext101_32x8d	.730
2	resnext101_32x32d_wsl	.695
3	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.690
4	convnext_large:fb_in22k_ft_in1k	.667
5	vit_large_patch14_clip_224:openai_ft_in1k	.663
6	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.648
7	fixres_resnext101_32x48d_wsl	.630
8	resnet50-VITO-8deg-cc	.625
9	vit_large_patch14_clip_336:laion2b_ft_in1k	.623
10	SWSL_resnet50	.613
11	vit_large_patch14_clip_224:laion2b_ft_in1k	.603
12	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.602
13	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.600
14	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.589
15	resnext101_32x48d_wsl	.579
16	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.578
17	resnext101_32x8d_wsl	.563
18	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.554
19	CLIP_resnet50	.544
20	CLIP_resnet50_float32	.544
21	deit_large_imagenet_full_seed-0	.543
22	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.537
23	resnext101_32x16d_wsl	.535
24	vit_base_patch16_clip_224:openai_ft_in1k	.535
25	convnext_xlarge:fb_in22k_ft_in1k	.527
26	effnetv2m_custom384	.527
27	convnext_base:clip_laiona_augreg_ft_in1k_384	.516
28	vision_transformer_vit_large_patch16_224	.499
29	resnet_152_v2	.498
30	effnetb1_272x240	.497
31	CLIP_ViT-B_32	.496
32	cvt_cvt-13-384-in1k_4_LucyV4	.492
33	convnext_large_imagenet_full_seed-0	.471
34	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.463
35	vit_relpos_base_patch16_clsgap_224:sw_in1k	.463
36	deit_small_imagenet_full_seed-0	.460
37	deit_base_imagenet_full_seed-0	.460
38	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.454
39	focalnet_tiny_lrf_in1k	.436
40	convnext_tiny:in12k_ft_in1k	.435
41	CLIP-RN50	.419
42	convnext_tiny_imagenet_full_seed-0	.419
43	resnet_50_v2	.415
44	pnasnet_large	.410
45	ViT_B_16_imagenet1k	.409
46	ViT_L_32_imagenet1k	.406
47	inception_v4	.400
48	resnet_101_v2	.397
49	nasnet_large	.396
50	cvt_cvt-21-384-in1k_4_LucyV4	.391
51	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.385
52	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.382
53	convnext_small_imagenet_full_seed-0	.379
54	convnext_femto_ols:d1_in1k	.379
55	resnet-152_v2_pytorch	.371
56	cvt_cvt-21-224-in1k_4_LucyV4	.368
57	cvt_cvt-13-224-in1k_4_LucyV4	.361
58	convnext_base_imagenet_full_seed-0	.354
59	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.352
60	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.338
61	pnasnet_large-tf	.338
62	antialias-resnet152	.326
63	xception-keras	.317
64	cv_18_dagger_408_pretrained	.314
65	resnet101	.313
66	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.311
67	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.306
68	nasnet_large-tf	.305
69	inception_v3-tf	.299
70	inception_v4-tf	.295
71	resnet152_imagenet_full	.290
72	resnet-152_v2-tf	.285
73	resnet50_byol	.274
74	resnet_152_v1	.270
75	resnet_101_v1	.268
76	antialiased-rnext101_32x8d	.268
77	inception_v3	.260
78	convnext_tiny_sup	.260
79	AdvProp_efficientnet-b4	.258
80	AT_efficientnet-b4	.258
81	grcnn_109	.252
82	inception_v3_pytorch	.252
83	resnet50	.251
84	ViT_B_32_imagenet1k	.244
85	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.243
86	resnet50_moco_v2	.232
87	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.225
88	AdvProp_efficientnet-b6	.221
89	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.218
90	tv_efficientnet-b1	.215
91	densenet-121-keras	.214
92	antialiased-r50	.214
93	resnet50_imagenet_full	.213
94	voneresnet-50-non_stochastic	.209
95	convnext_small_imagenet_100_seed-0	.207
96	densenet-169-keras	.203
97	AdvProp_efficientnet-b7	.203
98	resnet34_imagenet_full	.203
99	resnet-50_v2-tf	.202
100	densenet-121	.201
101	densenet-201-keras	.197
102	grcnn	.194
103	resnet_50_v1_spiking	.190
104	resnet50-moclr8deg	.187
105	densenet-169	.186
106	mobilenet_v2_1_0_224	.186
107	resnet50_tutorial	.185
108	resnet_50_v1	.185
109	resnet-50-pytorch	.185
110	resnet50-sup	.185
111	efficientnet-b7	.185
112	vgg_19	.184
113	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.180
114	BiT-S-R152x4	.175
115	pnasnet_large_pytorch	.175
116	Res2Net50_26w_4s	.174
117	xception	.168
118	resnet-50_v1-tf	.167
119	resnet101_imagenet_full	.165
120	AT_efficientnet-b2	.165
121	AdvProp_efficientnet-b2	.165
122	resnet18_imagenet_full	.163
123	densenet-201	.161
124	densenet_201_pytorch	.161
125	ReAlnet04	.156
126	custom_model_cv_18_dagger_408	.156
127	resnet-101_v1-tf	.155
128	vonegrcnn_62e_nobn	.153
129	efficientnet_b1_imagenet_full	.153
130	efficientnet_b0	.152
131	inception_v1-tf	.144
132	deit_small_imagenet_100_seed-0	.143
133	vonegrcnn_47e	.141
134	efficientnet_b2_imagenet_full	.140
135	resnet50_random_linf8_perturb	.140
136	vonegrcnn_52e_full	.139
137	resnet-152_v1-tf	.138
138	mobilenet_v2_1.0_224-tf	.135
139	ReAlnet03	.135
140	nasnet_mobile	.133
141	mobilenet_v2_1.4_224-tf	.133
142	voneresnet-50	.132
143	ReAlnet09	.132
144	vonegrcnn_62e_nobn	.130
145	resnet50-SIN_IN	.129
146	BiT-S-R50x3	.129
147	blt_vs	.129
148	mobilenet_v2_1_0_192	.127
149	BiT-S-R101x3	.127
150	ReAlnet07	.127
151	vonegrcnn_52e_full	.126
152	vonegrcnn_47e	.126
153	ReAlnet08	.126
154	resnet50_random_l2_perturb	.126
155	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.125
156	inception_v2-tf	.124
157	cornet_s	.124
158	AdvProp_efficientnet-b8	.123
159	mobilenet_v2_1-4_224_pytorch	.122
160	mobilenet_v2_1_4_224	.122
161	ReAlnet02	.121
162	voneresnet-50-robust	.119
163	mobilenet_v2_0_5_192	.116
164	ReAlnet06	.115
165	nasnet_mobile-tf	.113
166	resnet50-vitoimagevidnet8	.113
167	mobilenet_v1_0.75_224	.112
168	ReAlnet10	.112
169	mobilenet_v2_0_5_224	.111
170	vgg-19-keras	.111
171	resnet50_l2_3_robust	.110
172	resnet50_linf_4_robust	.110
173	inception_v1	.109
174	resnet50-SIN_IN_IN	.109
175	resnet_SIN_IN_FT_IN	.109
176	mobilenet_v2_1.0_160-tf	.109
177	resnet_50_v1_spiking_l4a	.108
178	mobilenet_v2_1_0_160	.108
179	resnet50_linf_8_robust	.107
180	resnet-50-robust	.103
181	imagenet_l2_3_0	.103
182	resnet50_robust_l2_eps3	.103
183	vgg_16	.100
184	ReAlnet01	.100
185	BiT-S-R50x1	.100
186	CORnet-S	.097
187	vgg-16-keras	.097
188	efficientnet_b0_imagenet_full	.096
189	mobilenet_v2_1_3_224	.096
190	mobilenet_v2_0.5_192-tf	.096
191	mobilenet_v2_0.75_192-tf	.095
192	mobilenet_v1_1.0_160	.095
193	ReAlnet05	.094
194	mobilenet_v2_1.3_224-tf	.091
195	resnet50_eMMCR_Vanilla	.090
196	regnet_y_400mf	.087
197	imagenet_l2_10_0	.086
198	mobilenet_v2_1.0_192-tf	.085
199	resnet50_imagenet_10_seed-0	.085
200	deit_small_imagenet_10_seed-0	.085
201	deit_small_imagenet_1_seed-0	.085
202	mobilenet_v2_0.75_160-tf	.085
203	mobilenet_v2_0.5_224-tf	.084
204	mobilenet_v2_0_75_160	.084
205	resnet50_robust_l2_eps1	.082
206	mobilenet_v1_0.75_192	.081
207	alexnet_linf_8_robust	.081
208	resnet-18	.081
209	mobilenet_v2_0.75_96	.081
210	resnet-34	.080
211	alexnet	.079
212	convnext_small_imagenet_10_seed-0	.078
213	mobilenet_v2_1.0_96	.078
214	mobilenet_v2_0_75_192	.077
215	mobilenet_v2_0.35_224	.077
216	mobilenet_v2_0.5_96	.077
217	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.075
218	alexnet_training_seed_05	.074
219	alexnet_training_seed_01	.074
220	resnet50-meshes-lt-100-original-scratch	.074
221	mobilenet_v2_0.75_128	.072
222	texture_shape_resnet50_trained_on_SIN	.071
223	alexnet_random_l2_3_perturb	.070
224	alexnet_l2_3_robust	.070
225	mobilenet_v2_0.75_224-tf	.069
226	resnet-50_untrained	.067
227	vonealexnet_gaussian_noise_std4_fixed	.066
228	mobilenet_v2_1_0_128	.065
229	resnet50-SIN	.064
230	alexnet_reduced_aliasing_early_checkpoint	.063
231	mobilenet_v2_0.35_96	.061
232	mobilenet_v2_0_75_224	.061
233	mobilenet_v2_0.35_192	.061
234	alexnet_robust_correct	.060
235	shufflenet_v2_x1_0	.060
236	BiT-S-R152x2	.059
237	texture_shape_alexnet_trained_on_SIN	.059
238	alexnet_training_seed_03	.058
239	alexnet_training_seed_09	.057
240	squeezenet1_1	.057
241	mobilenet_v1_0.75_128	.056
242	alexnet_ks_torevert	.056
243	alexnet-baseline	.056
244	alexnet	.056
245	alexnet	.056
246	alexnet	.056
247	alexnet	.056
248	alexnet	.056
249	alexnet	.056
250	alexnet	.056
251	alexnet	.056
252	alexnet	.056
253	AdvProp_efficientnet-b0	.055
254	mobilenet_v1_0.5_224	.055
255	resnet50-simclr-vissl	.054
256	AlexNet_SIN	.054
257	barlow-twins-resnet50	.052
258	alexnet_random_linf8_perturb	.049
259	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.049
260	resnet50_simclr	.047
261	mobilenet_v1_1.0_224	.045
262	mobilenet_v1_1.0_192	.045
263	mobilenet_v2_0.35_128	.044
264	BiT-S-R101x1	.044
265	alexnet_early_checkpoint	.043
266	resnet50-vicreg	.038
267	resnet50-vicregl0p9	.038
268	mobilenet_v2_1.0_128-tf	.037
269	artResNet18_1	.032
270	resnet_50_v1_spiking_l4	.032
271	alexnet_training_seed_02	.031
272	alexnet_training_seed_08	.031
273	alexnet_training_seed_04	.031
274	alexnet_training_seed_10	.031
275	mobilenet_v2_0.5_160	.030
276	mobilenet_v2_0.35_160	.029
277	0.5x_resnet-18_LC_w_sh_1_iter	.028
278	mobilenet_v1_0.25_160	.026
279	resnet50_FractalDB	.026
280	resnet50_imagenet_1_seed-0	.025
281	resnet_50_v1_spiking_l3	.024
282	alexnet_training_seed_06	.024
283	mobilenet_v1_0.25_224	.022
284	mobilenet_v2_0.5_128	.020
285	mobilenet_v1_0.25_192	.019
286	mobilenet_v1_0.25_128	.017
287	resnet50-meshes-lt-100-original-pretrained	.016
288	mobilenet_v1_1.0_128	.016
289	squeezenet1_0	.014
290	mobilenet_v1_0.5_192	.013
291	alexnet_training_seed_07	.013
292	mobilevit_small	.013
293	mobilenet_v1_0.75_160	.013
294	konkle_alexnetgn_ipcl_ref01_primary_model	.013
295	resnet50_imagenet_100_seed-0	.007
296	mobilenet_v1_0.5_160	.006
297	resnet50-barlow	.006
298	convnext_small_imagenet_1_seed-0	.005
299	mobilenet_v1_0.5_128	.003
300	resnet50-vicregl0p75	.003
301	resnet-18-LC_w_sh_100_iter_conv_init_m
302	ViT-B/32
303	BiT-M-R50x3
304	BiT-M-R50x1
305	BiT-M-R152x2
306	resnet-18-LC_w_sh_1_iter_conv_init_m
307	resnet-18-LC_w_sh_10_iter_m
308	resnet-18-LC_w_sh_100_iter_m
309	resnet-18-LC_w_sh_10_iter_conv_init_m
310	resnet-18-LC_w_sh_1_iter_m
311	FrankRobWobv0
312	0.5x_resnet-18_LC
313	CORnetZ_CIFAR10
314	resnet18-local_aggregation
315	resnet18-deepcluster
316	r3m_resnet18
317	CORnet-Z
318	resnet18-instance_recognition
319	vggface
320	my-model
321	0.5x_resnet-18_LC_w_sh_10_iter
322	r3m_resnet50
323	resnet18-colorization
324	r3m_resnet34
325	resnet-18-LC_m
326	r3m_resnet50_nocrop
327	resnet18-supervised
328	resnet-18-LC_1st_conv_m
329	resnet-18-LC_conv_init_m
330	resnet18-contrastive_multiview
331	0.5x_resnet-18
332	RN50
333	0.5x_resnet-18_LC_w_sh_100_iter
334	RN50
335	resnet18-relative_position
336	resnet18-autoencoder
337	resnet18-simclr
338	ViT_L_32
339	ViT_B_32
340	resnet18-depth_prediction
341	ViT_B_16
342	r3m_resnet34_nocrop
343	resnet18-contrastive_predictive
344	omnivore_swinT
345	resnet-18-LC_untrained
346	resnet-18_untrained
347	resnet-50x2_untrained
348	dcgan
349	unet_entire
350	v1-pyr-nodown
351	CORnetZ_CIFAR10_bs32_20_04
352	pixels
353	dorinet_cornet_z
354	my-model
355	resnet50
356	openclip
357	resnet50-cifar
358	resnet50_pretrained_with_retinal_waves
359	resnet50_ImageNet
360	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
361	yudixie_resnet50_random_0_240908
362	yudixie_resnet50_imagenet1kpret_0_240908
363	yudixie_resnet50_cat_obj_class_all_latents_0_240908
364	yudixie_resnet50_imagenet1kpret_0_240312
365	yudixie_resnet50_category_class_0_240908
366	resnet18_imagenet21kP
367	yudixie_resnet50_distance_reg_0_240908
368	ConvLSTM
369	PredRNN
370	SimVP
371	TAU
372	MIM
373	hmax
374	ReAlnet01_cornet
375	yolos_tiny
376	resnet152_ecoset_full
377	yudixie_resnet18_translation_reg_0_240719
378	yudixie_resnet18_distance_reg_0_240719
379	ReAlnet03_cornet
380	yudixie_resnet18_rotation_reg_0_240719
381	ReAlnet02_cornet
382	yudixie_resnet18_imagenet1kpret_0_240719
383	resnet34_ecoset_full
384	resnet50_ecoset_full
385	resnet101_ecoset_full
386	yudixie_resnet50_distance_translation_0_240908
387	omnivore_swinB
388	yudixie_resnet18_distance_rotation_0_240719
389	yudixie_resnet50_distance_rotation_0_240908
390	yudixie_resnet18_category_class_0_240719
391	yudixie_resnet18_random_0_240719
392	ReAlnet05_cornet
393	yudixie_resnet18_cat_obj_class_all_latents_0_240719
394	yudixie_resnet50_rotation_reg_0_240908
395	resnet-18_test_m
396	yudixie_resnet18_distance_translation_rotation_0_240719
397	yudixie_resnet18_object_class_0_240719
398	SeLaVi-AVE
399	r3d_18
400	ReAlnet06_cornet
401	yudixie_resnet50_translation_reg_0_240908
402	yudixie_resnet50_translation_rotation_0_240908
403	ReAlnet01_ALL
404	mc3_18
405	ReAlnet07_cornet
406	s3d
407	mvit_v1_b
408	ReAlnet08_cornet
409	ReAlnet02_ALL
410	ReAlnet03_ALL
411	VOneCORnet-S
412	ReAlnet04_ALL
413	ReAlnet09_cornet
414	SeLaVi-Kinetics400
415	SeLaVi-VGG-Sound
416	ReAlnet05_ALL
417	SeLaVi-Kinetics-Sound
418	omnivore_swinS
419	mvit_v2_s
420	ReAlnet06_ALL
421	r2plus1d_18
422	ReAlnet10_cornet
423	ReAlnet07_ALL
424	resnet18_ecoset_full
425	yudixie_resnet50_distance_translation_rotation_0_240908
426	ReAlnet08_ALL
427	yudixie_resnet18_translation_rotation_0_240719
428	yudixie_resnet18_distance_translation_0_240719
429	resnet50_primary_visual_cortex
430	ReAlnet04_cornet
431	ReAlnet09_ALL
432	yudixie_resnet50_object_class_0_240908
433	briaai_rmbg_1_4
434	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

0.47.

Note that scores are relative to this ceiling.

Data: Geirhos2021lowpass

Metric: error_consistency