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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021colour-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_large_patch14_clip_224:laion2b_ft_in1k	.998
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.998
3	vit_large_patch14_clip_336:laion2b_ft_in1k	.998
4	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.998
5	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.998
6	deit3_base_patch16_224_fb_in22k_ft_in1k	.998
7	eva02_large_in22k	.998
8	vit_large_clip336_openai	.998
9	dinov2_vitg14_reg_lc	.998
10	resnext101_32x32d_wsl	.997
11	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.997
12	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.997
13	convnext_base:clip_laiona_augreg_ft_in1k_384	.997
14	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.997
15	convnext_large_clip_laion2b_finelayers	.997
16	convnext_large_in22k_supervised	.997
17	dinov2_vitl14_reg_lc	.997
18	dinov2_vitg14_lc	.997
19	dinov2_vitl14_lc_res336	.997
20	convnext_xxlarge_clip	.997
21	vit_huge_clip336_laion	.997
22	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.995
23	vit_large_patch14_clip_224:openai_ft_in1k	.995
24	convnext_xlarge:fb_in22k_ft_in1k	.995
25	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.995
26	convnext_large_imagenet_full_seed-0	.995
27	convnext_base_fb_in22k_ft_in1k	.995
28	deit3_base_patch16_224_fb_in1k	.995
29	dinov2_vitl14_lc	.995
30	fixres_resnext101_32x48d_wsl	.994
31	resnext101_32x48d_wsl	.994
32	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.994
33	vit_base_patch16_clip_224:openai_ft_in1k	.994
34	vit_relpos_base_patch16_clsgap_224:sw_in1k	.994
35	convnext_large:fb_in22k_ft_in1k	.994
36	convnext_base_fb_in1k	.994
37	AdvProp_efficientnet-b7	.992
38	deit_large_imagenet_full_seed-0	.992
39	deit_base_imagenet_full_seed-0	.992
40	nasnet_large-tf	.991
41	effnetv2m_custom384	.991
42	resnext101_32x16d_wsl	.991
43	focalnet_tiny_lrf_in1k	.991
44	convnext_base_imagenet_full_seed-0	.991
45	convnext_tiny:in12k_ft_in1k	.991
46	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.991
47	convnext_tiny_imagenet_full_seed-0	.991
48	nasnet_large	.991
49	regnety_032	.991
50	pnasnet_large-tf	.989
51	resnext101_32x8d_wsl	.989
52	AdvProp_efficientnet-b6	.989
53	convnext_tiny_sup	.989
54	antialiased-rnext101_32x8d	.989
55	convnext_small_imagenet_full_seed-0	.989
56	AT_efficientnet-b2	.988
57	AdvProp_efficientnet-b2	.988
58	cvt_cvt-13-224-in1k_4_LucyV4	.988
59	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.988
60	inception_v3-tf	.986
61	inception_v4-tf	.986
62	cvt_cvt-21-224-in1k_4_LucyV4	.986
63	pnasnet_large_halfPrecision	.986
64	pnasnet_large	.986
65	seresnext50_32x4d	.986
66	BiT-S-R152x4	.984
67	AdvProp_efficientnet-b0	.984
68	antialias-resnet152	.984
69	eBarlow_lmda_02_1000ep	.984
70	resnet50_simsiam_linhead	.984
71	BiT-S-R50x3	.983
72	BiT-S-R101x3	.983
73	cv_18_dagger_408_pretrained	.983
74	cvt_cvt-13-384-in1k_4_LucyV4	.983
75	resnet-152_v2_pytorch	.983
76	cvt_cvt-21-384-in1k_4_LucyV4	.983
77	resnet50_vicreg_linhead	.983
78	AdvProp_efficientnet-b4	.981
79	resnet-152_v2-tf	.981
80	AT_efficientnet-b4	.981
81	ViT_B_16_imagenet1k	.981
82	antialiased-r50	.981
83	resnet50_st_wzc_2	.981
84	deit_small_imagenet_full_seed-0	.981
85	inception_v4	.981
86	resnet_101_v2	.981
87	resnet-101_v2-tf	.980
88	resnet_152_v1	.980
89	resnet50_ewconplus_wzc	.980
90	resnet50-vitoimagevidnet8	.980
91	resnet50_st_wzc_seed7_2_323	.980
92	resnet_SIN_IN_FT_IN	.978
93	BiT-S-R101x1	.978
94	resnet50-SIN_IN_IN	.978
95	densenet-201-keras	.978
96	inception_v2-tf	.978
97	Res2Net50_26w_4s	.978
98	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.978
99	densenet-201	.978
100	densenet_201_pytorch	.978
101	resnet152_imagenet_full	.978
102	grcnn	.978
103	ijepa_vith14_linhead	.978
104	efficientnet-b7	.977
105	resnet50-SIN_IN	.977
106	resnet-50_v1-tf	.977
107	effnetb1_272x240	.977
108	resnet50-moclr8deg	.977
109	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.977
110	resnet_101_v1	.977
111	resnet50_st_wzc_seed6_2_323	.977
112	BiT-S-R152x2	.975
113	BiT-S-R50x1	.975
114	efficientnet_b0	.975
115	resnet-101_v1-tf	.975
116	densenet-169-keras	.975
117	xception-keras	.975
118	resnet50_moco_v2	.975
119	resnet50_st_wzc_seed3_2_323	.975
120	resnet101_imagenet_full	.975
121	resnet_152_v2	.975
122	densenet-169	.975
123	ViT_L_32_imagenet1k	.973
124	resnet-152_v1-tf	.973
125	inception_v3	.973
126	voneresnet-50-non_stochastic	.972
127	resnet-50_v2-tf	.972
128	CORnet-S	.972
129	resnet50_imagenet_full	.972
130	tv_efficientnet-b1	.972
131	grcnn_109	.972
132	convnext_femto_ols:d1_in1k	.972
133	resnet50_ewconplus_wzc_seed5_2__323	.972
134	vonegrcnn_47e	.970
135	resnet50_barlowtwins_linhead	.970
136	densenet-121-keras	.969
137	vonegrcnn_62e_nobn	.969
138	resnet-50-pytorch	.969
139	mobilenet_v2_1.4_224-tf	.969
140	mobilenet_v2_1.3_224-tf	.969
141	vonegrcnn_47e	.969
142	vgg-16-keras	.969
143	vgg-19-keras	.969
144	resnet50-sup	.969
145	resnet50_tutorial	.969
146	resnet_50_v1	.969
147	densenet-121	.969
148	mobilenet_v2_1.0_192-tf	.967
149	efficientnet_b2_imagenet_full	.967
150	resnet50_ewconplus_wzc_seed2_2__323	.967
151	mobilenet_v2_1.0_224-tf	.966
152	voneresnet-50	.966
153	vgg_19	.966
154	resnet50-VITO-8deg-cc	.966
155	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.966
156	resnet50_hvs_wzc	.966
157	resnet_50_v2	.966
158	resnet50_simclr_linhead_01norm	.966
159	resnet50_byol_linhead	.966
160	mobilenet_v2_1.0_160-tf	.964
161	resnet50	.964
162	mobilenet_v2_1_3_224	.964
163	efficientnet_b1_imagenet_full	.963
164	nasnet_mobile	.963
165	vonegrcnn_52e_full	.963
166	resnet-34	.961
167	regnet_y_400mf	.961
168	vgg_16	.961
169	vonegrcnn_62e_nobn	.961
170	vonegrcnn_52e_full	.959
171	ViT_B_32_imagenet1k	.959
172	resnet50_robust_l2_eps1	.959
173	xception	.959
174	mobilenet_v1_1.0_224	.958
175	custom_model_cv_18_dagger_408	.956
176	resnet_50_v1_spiking	.956
177	inception_v1-tf	.955
178	resnet-18	.955
179	resnet34_imagenet_full	.955
180	resnet18_imagenet_full	.955
181	mobilenet_v1_0.75_224	.952
182	mobilenet_v1_1.0_192	.952
183	mobilenet_v1_1.0_160	.952
184	blt_vs	.952
185	ReAlnet06	.948
186	resnet50_eMMCR_Vanilla	.948
187	efficientnet_b0_imagenet_full	.947
188	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.945
189	AdvProp_efficientnet-b8	.944
190	mobilenet_v1_0.75_192	.944
191	ReAlnet09	.944
192	ReAlnet03	.944
193	eicircuit_resnet18_bn_20260919	.944
194	mobilenet_v2_0.75_192-tf	.941
195	mobilenet_v2_1.0_128-tf	.939
196	mobilenet_v2_0.75_224-tf	.939
197	mobilenet_v1_0.5_224	.939
198	voneresnet-50-robust	.939
199	mobilenet_v2_1_0_192	.939
200	ReAlnet02	.939
201	convnext_base_fb_in1k_gram_aligned_dinov3	.939
202	mobilenet_v1_0.75_160	.938
203	ReAlnet07	.938
204	shufflenet_v2_x1_0	.936
205	mobilenet_v2_1_0_224	.936
206	mobilenet_v2_0.75_160-tf	.934
207	ReAlnet01	.934
208	nasnet_mobile-tf	.931
209	ReAlnet04	.931
210	mobilenet_v2_1_0_160	.931
211	inception_v1	.930
212	ReAlnet05	.930
213	ReAlnet08	.927
214	ReAlnet10	.925
215	mobilenet_v2_0.5_224-tf	.923
216	mobilenet_v1_1.0_128	.923
217	mobilenet_v2_0_75_224	.923
218	mobilenet_v2_0_75_192	.923
219	resnet50-SIN	.922
220	mobilenet_v2_0_75_160	.920
221	mobilenet_v2_0.75_128	.919
222	resnet_50_v1_spiking_l4a	.917
223	mobilenet_v2_0.5_192-tf	.912
224	0.5x_resnet-18_LC_w_sh_1_iter	.912
225	mobilenet_v1_0.75_128	.911
226	mobilenet_v2_1_0_128	.911
227	mobilenet_v1_0.5_192	.909
228	CLIP-RN50	.908
229	mobilenet_v2_1.0_96	.906
230	mobilenet_v2_0.5_160	.905
231	mobilenet_v1_0.5_160	.903
232	mobilenet_v2_0_5_224	.903
233	mobilenet_v2_0.75_96	.902
234	resnet-50-robust	.902
235	imagenet_l2_3_0	.902
236	resnet50_robust_l2_eps3	.902
237	mobilenet_v2_1-4_224_pytorch	.902
238	mobilenet_v2_1_4_224	.902
239	mehrer2020_alexnet_training_seed_01	.902
240	mehrer2020_alexnet_training_seed_01_fov12	.902
241	mehrer2020_alexnet_training_seed_01_fov16	.902
242	mehrer2020_alexnet_training_seed_01_fov4	.902
243	mobilenet_v2_0.35_192	.900
244	mobilenet_v2_0_5_192	.900
245	resnet50_l2_3_robust	.889
246	mehrer2020_alexnet_training_seed_04	.886
247	mobilenet_v2_0.35_224	.884
248	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.884
249	mobilenet_v2_0.5_128	.884
250	mehrer2020_alexnet_training_seed_05	.884
251	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.883
252	mehrer2020_alexnet_training_seed_02	.881
253	mehrer2020_alexnet_training_seed_03	.878
254	mobilenet_v2_0.35_160	.872
255	squeezenet1_1	.870
256	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.866
257	alexnet	.864
258	alexnet_random_linf8_perturb	.864
259	alexnet_ks_torevert	.864
260	alexnet_fov4	.864
261	alexnet_fov12	.864
262	alexnet_fov16	.864
263	mobilenet_v1_0.5_128	.863
264	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.859
265	convnext_small_imagenet_100_seed-0	.859
266	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.850
267	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.844
268	squeezenet1_0	.842
269	mobilenet_v1_0.25_224	.833
270	alexnet_early_checkpoint	.830
271	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.830
272	mobilenet_v2_0.5_96	.823
273	mobilenet_v1_0.25_192	.819
274	mobilenet_v2_0.35_128	.819
275	resnet50_linf_8_robust	.812
276	mobilenet_v1_0.25_160	.808
277	mobilenet_v2_0.35_96	.797
278	AlexNet_SIN	.797
279	AlexNet_SIN_fov4	.797
280	AlexNet_SIN_fov12	.797
281	AlexNet_SIN_fov16	.797
282	imagenet_l2_10_0	.781
283	mobilenet_v1_0.25_128	.777
284	alexnet_l2_3_robust	.767
285	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.767
286	alexnet_robust_correct	.756
287	deit_small_imagenet_100_seed-0	.744
288	resnet50_imagenet_100_seed-0	.731
289	alexnet_linf_8_robust	.625
290	resnet_50_v1_spiking_l4	.584
291	resnet50_imagenet_10_seed-0	.200
292	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.170
293	convnext_small_imagenet_10_seed-0	.127
294	deit_small_imagenet_10_seed-0	.114
295	deit_small_imagenet_1_seed-0	.089
296	resnet50-barlow	.080
297	resnet50-vicregl0p75	.077
298	alexnet_training_seed_06	.075
299	alexnet_training_seed_09	.067
300	resnet-50_untrained	.062
301	alexnet_training_seed_05	.062
302	alexnet_training_seed_02	.062
303	alexnet_training_seed_04	.062
304	alexnet_training_seed_08	.062
305	convnext_small_imagenet_1_seed-0	.062
306	alexnet_training_seed_10	.062
307	alexnet_training_seed_01	.062
308	resnet_50_v1_spiking_l3	.062
309	alexnet_training_seed_01_fov4	.062
310	alexnet_training_seed_01_fov12	.062
311	alexnet_training_seed_01_fov16	.062
312	alexnet_training_seed_03	.062
313	resnet50-simclr-vissl	.061
314	resnet50_imagenet_1_seed-0	.061
315	barlow-twins-resnet50	.058
316	resnet50-vicregl0p9	.058
317	alexnet_training_seed_07	.056
318	mobilevit_small	.045
319	artResNet18_1	.033
320	ViT-B/32
321	resnet-18-LC_w_sh_100_iter_conv_init_m
322	BiT-M-R50x1
323	resnet-18-LC_w_sh_1_iter_conv_init_m
324	resnet-18-LC_w_sh_1_iter_m
325	BiT-M-R152x2
326	resnet-18-LC_w_sh_10_iter_m
327	BiT-M-R50x3
328	resnet-18-LC_w_sh_100_iter_m
329	resnet-18-LC_w_sh_10_iter_conv_init_m
330	FrankRobWobv0
331	0.5x_resnet-18_LC
332	CORnetZ_CIFAR10
333	resnet18-local_aggregation
334	r3m_resnet18
335	CORnet-Z
336	resnet18-deepcluster
337	vggface
338	my-model
339	resnet18-instance_recognition
340	0.5x_resnet-18_LC_w_sh_10_iter
341	r3m_resnet50
342	r3m_resnet34
343	resnet-18-LC_m
344	r3m_resnet50_nocrop
345	resnet18-supervised
346	resnet-18-LC_1st_conv_m
347	resnet-18-LC_conv_init_m
348	resnet18-contrastive_multiview
349	0.5x_resnet-18
350	RN50
351	0.5x_resnet-18_LC_w_sh_100_iter
352	RN50
353	resnet18-colorization
354	resnet18-relative_position
355	resnet18-autoencoder
356	resnet18-simclr
357	ViT_L_32
358	ViT_B_32
359	resnet18-depth_prediction
360	ViT_B_16
361	r3m_resnet34_nocrop
362	resnet18-contrastive_predictive
363	resnet-18-LC_untrained
364	resnet-18_untrained
365	resnet-50x2_untrained
366	dcgan
367	unet_entire
368	CORnetZ_CIFAR10_bs32_20_04
369	v1-pyr-nodown
370	pixels
371	dorinet_cornet_z
372	omnivore_swinT
373	openclip
374	vonealexnet_gaussian_noise_std4_fixed
375	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
376	yudixie_resnet50_category_class_0_240908
377	yudixie_resnet50_distance_reg_0_240908
378	ConvLSTM
379	PredRNN
380	SimVP
381	TAU
382	MIM
383	yolos_tiny
384	pnasnet_large_pytorch
385	inception_v3_pytorch
386	yudixie_resnet18_distance_translation_0_240719
387	briaai_rmbg_1_4
388	compact_resnet50_V4
389	ReAlnet01_cornet
390	yudixie_resnet18_imagenet1kpret_0_240719
391	yudixie_resnet50_distance_rotation_0_240908
392	yudixie_resnet50_rotation_reg_0_240908
393	yudixie_resnet50_translation_reg_0_240908
394	vit_base_patch14_reg4_dinov2-lvd142m
395	yudixie_resnet50_distance_translation_0_240908
396	compact_resnet50_IT
397	ReAlnet01_cornet_fov4
398	vit_base_patch14_dinov2-lvd142m
399	ReAlnet02_cornet
400	resnet34_ecoset_full
401	ReAlnet01_cornet_fov12
402	resnet101_ecoset_full
403	yudixie_resnet50_translation_rotation_0_240908
404	compact_vgg19_V4
405	ReAlnet04_cornet
406	resnet152_ecoset_full
407	resnet-18_test_m
408	yudixie_resnet18_category_class_0_240719
409	compact_resnet50_robust_V4
410	yudixie_resnet18_random_0_240719
411	yudixie_resnet18_cat_obj_class_all_latents_0_240719
412	compact_vgg19_IT
413	yudixie_resnet18_distance_translation_rotation_0_240719
414	SeLaVi-AVE
415	yudixie_resnet18_object_class_0_240719
416	yudixie_resnet18_rotation_reg_0_240719
417	yudixie_resnet18_translation_reg_0_240719
418	yudixie_resnet18_distance_reg_0_240719
419	hmax
420	r3d_18
421	ReAlnet01_ALL
422	omnivore_swinB
423	mc3_18
424	ReAlnet02_ALL
425	s3d
426	resnet50-vicreg
427	ReAlnet08_cornet
428	mvit_v1_b
429	compact_cornets_V4
430	ReAlnet03_ALL
431	resnet18_imagenet21kP
432	compact_cornets_IT
433	ReAlnet04_ALL
434	omnivore_swinS
435	SeLaVi-Kinetics400
436	ReAlnet05_ALL
437	vit_base_patch16_dinov3-lvd1689m
438	SeLaVi-VGG-Sound
439	SeLaVi-Kinetics-Sound
440	ReAlnet06_ALL
441	compact_resnet50_robust_IT
442	yudixie_resnet50_random_0_240908
443	ReAlnet10_cornet
444	r2plus1d_18
445	ReAlnet07_ALL
446	yudixie_resnet50_distance_translation_rotation_0_240908
447	mvit_v2_s
448	yudixie_resnet50_imagenet1kpret_0_240908
449	resnet18_ecoset_full
450	ReAlnet08_ALL
451	yudixie_resnet18_distance_rotation_0_240719
452	ReAlnet09_ALL
453	yudixie_resnet18_translation_rotation_0_240719
454	yudixie_resnet50_imagenet1kpret_0_240312
455	yudixie_resnet50_object_class_0_240908
456	yudixie_resnet50_cat_obj_class_all_latents_0_240908
457	resnet50_primary_visual_cortex
458	ReAlnet09_cornet
459	ReAlnet10_ALL
460	ReAlnet01_cornet_fov16
461	ReAlnet05_cornet
462	ReAlnet06_cornet
463	ReAlnet07_cornet
464	ReAlnet03_cornet
465	VOneCORnet-S
466	resnet18_fair
467	resnet50_ecoset_full
468	pr1_stl10_disentangled_alpha04
469	predictive_coding_pc
470	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3
471	yudixie_wbh_object_class_scaling_0415_run_0
472	yudixie_wbh_object_class_scaling_0415_run_3
473	yudixie_wbh_object_class_scaling_0415_imagenet
474	yudixie_wbh_object_class_scaling_0415_run_2
475	yudixie_wbh_object_class_scaling_0415_run_1
476	deepeisnn_ei_cifar10_vgg19
477	deepeisnn_ei_cifar10_resnet18
478	deepeisnn_ei_imagenet_resnet18
479	deepeisnn_cifar10_resnet18_lif
480	dinov2_vitl14_reg_lc_featread
481	gabor_filter_entropy_4x4
482	gabor_filter_entropy_4x4_v2
483	gabor_filter_entropy_4x4_v2_forcedCosine
484	gabor_filter_mean_abs_4x4_v2

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

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021colour

Metric: top1