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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021edge-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge_clip	.969
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.963
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.944
4	dinov2_vitg14_reg_lc	.938
5	eva02_large_in22k	.931
6	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.925
7	vit_large_patch14_clip_224:laion2b_ft_in1k	.925
8	vit_huge_clip336_laion	.919
9	dinov2_vitg14_lc	.912
10	vit_large_patch14_clip_336:laion2b_ft_in1k	.906
11	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.900
12	convnext_large_clip_laion2b_finelayers	.900
13	vit_large_patch14_clip_224:openai_ft_in1k	.894
14	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.894
15	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.894
16	vit_large_clip336_openai	.887
17	resnext101_32x32d_wsl	.881
18	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.881
19	convnext_base:clip_laiona_augreg_ft_in1k_384	.863
20	convnext_large:fb_in22k_ft_in1k	.844
21	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.825
22	dinov2_vitl14_lc_res336	.825
23	convnext_xlarge:fb_in22k_ft_in1k	.812
24	dinov2_vitl14_reg_lc	.806
25	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.800
26	convnext_base_fb_in22k_ft_in1k	.787
27	convnext_large_in22k_supervised	.787
28	resnext101_32x48d_wsl	.775
29	resnext101_32x8d_wsl	.769
30	resnext101_32x16d_wsl	.762
31	vit_base_patch16_clip_224:openai_ft_in1k	.756
32	fixres_resnext101_32x48d_wsl	.731
33	effnetv2m_custom384	.719
34	dinov2_vitl14_lc	.706
35	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.700
36	convnext_tiny:in12k_ft_in1k	.694
37	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.669
38	AdvProp_efficientnet-b7	.662
39	convnext_base_fb_in1k	.637
40	deit3_base_patch16_224_fb_in22k_ft_in1k	.625
41	AdvProp_efficientnet-b4	.600
42	AdvProp_efficientnet-b6	.600
43	AT_efficientnet-b4	.600
44	AlexNet_SIN	.581
45	AlexNet_SIN_fov4	.581
46	AlexNet_SIN_fov12	.581
47	AlexNet_SIN_fov16	.581
48	AdvProp_efficientnet-b8	.575
49	effnetb1_272x240	.569
50	convnext_base_fb_in1k_gram_aligned_dinov3	.531
51	tv_efficientnet-b1	.506
52	grcnn_109	.506
53	CLIP-RN50	.481
54	resnet50-SIN	.469
55	AT_efficientnet-b2	.469
56	AdvProp_efficientnet-b2	.469
57	vit_relpos_base_patch16_clsgap_224:sw_in1k	.438
58	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.438
59	deit3_base_patch16_224_fb_in1k	.438
60	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.425
61	convnext_large_imagenet_full_seed-0	.412
62	convnext_base_imagenet_full_seed-0	.400
63	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.400
64	convnext_small_imagenet_full_seed-0	.394
65	AdvProp_efficientnet-b0	.388
66	focalnet_tiny_lrf_in1k	.388
67	densenet-201-keras	.381
68	densenet-201	.381
69	densenet_201_pytorch	.381
70	mobilenet_v2_0.5_224-tf	.369
71	mobilenet_v2_0.75_192-tf	.369
72	efficientnet_b0	.362
73	efficientnet-b7	.362
74	mobilenet_v2_1.3_224-tf	.362
75	mobilenet_v2_0.75_224-tf	.362
76	mobilenet_v2_1_0_128	.362
77	cvt_cvt-21-224-in1k_4_LucyV4	.356
78	mobilenet_v2_0.5_128	.350
79	blt_vs	.350
80	mobilenet_v2_0_5_224	.350
81	mobilenet_v2_1_3_224	.350
82	mobilenet_v2_0.35_160	.344
83	imagenet_l2_10_0	.344
84	mobilenet_v2_0_75_224	.344
85	mobilenet_v2_0_75_192	.344
86	convnext_tiny_imagenet_full_seed-0	.344
87	inception_v4-tf	.338
88	mobilenet_v1_0.25_160	.338
89	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.338
90	mobilenet_v2_0.35_224	.331
91	mobilenet_v2_1.4_224-tf	.331
92	resnet152_imagenet_full	.331
93	convnext_femto_ols:d1_in1k	.331
94	BiT-S-R101x3	.325
95	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.325
96	densenet-169-keras	.325
97	mobilenet_v1_0.75_192	.325
98	resnet50_linf_8_robust	.325
99	efficientnet_b0_imagenet_full	.325
100	mobilenet_v2_1-4_224_pytorch	.325
101	resnet18_imagenet_full	.325
102	mobilenet_v2_1_4_224	.325
103	densenet-169	.325
104	mobilenet_v2_0.75_128	.319
105	mobilenet_v2_0.35_192	.319
106	convnext_tiny_sup	.319
107	antialiased-rnext101_32x8d	.319
108	BiT-S-R101x1	.312
109	mobilenet_v2_0.5_192-tf	.312
110	mobilenet_v1_0.5_128	.312
111	resnet50_ewconplus_wzc	.312
112	efficientnet_b1_imagenet_full	.312
113	cvt_cvt-13-384-in1k_4_LucyV4	.312
114	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.312
115	mobilenet_v2_1.0_192-tf	.306
116	mobilenet_v1_0.5_192	.306
117	mobilenet_v2_0.35_96	.306
118	resnet50_l2_3_robust	.306
119	inception_v4	.306
120	resnet50_st_wzc_seed7_2_323	.306
121	resnet50_ewconplus_wzc_seed5_2__323	.306
122	mobilenet_v2_1.0_160-tf	.300
123	mobilenet_v2_1.0_224-tf	.300
124	mobilenet_v2_0_5_192	.300
125	mobilenet_v2_0_75_160	.300
126	mobilenet_v2_1_0_192	.300
127	convnext_small_imagenet_100_seed-0	.300
128	mobilenet_v2_0.5_160	.294
129	alexnet	.294
130	mobilenet_v1_1.0_192	.294
131	mobilenet_v1_0.5_160	.294
132	alexnet_ks_torevert	.294
133	alexnet_fov4	.294
134	alexnet_fov12	.294
135	alexnet_fov16	.294
136	resnet101_imagenet_full	.294
137	cvt_cvt-13-224-in1k_4_LucyV4	.294
138	mobilenet_v2_1_0_224	.294
139	mobilenet_v2_1.0_128-tf	.287
140	mobilenet_v2_0.75_160-tf	.287
141	resnet_50_v2	.287
142	resnet-50-robust	.281
143	resnet-101_v2-tf	.281
144	resnet-152_v2-tf	.281
145	mobilenet_v2_0.35_128	.281
146	alexnet_l2_3_robust	.281
147	imagenet_l2_3_0	.281
148	resnet50_robust_l2_eps3	.281
149	resnet50-vitoimagevidnet8	.281
150	mobilenet_v1_0.5_224	.275
151	mobilenet_v1_1.0_160	.275
152	alexnet_early_checkpoint	.275
153	ReAlnet07	.275
154	inception_v3	.275
155	resnet50_ewconplus_wzc_seed2_2__323	.275
156	mobilenet_v2_0.75_96	.269
157	mobilenet_v1_1.0_128	.269
158	mobilenet_v1_1.0_224	.269
159	resnet50_st_wzc_2	.269
160	mobilenet_v2_1_0_160	.269
161	inception_v3_pytorch	.269
162	deit_large_imagenet_full_seed-0	.269
163	efficientnet_b2_imagenet_full	.269
164	nasnet_large-tf	.263
165	inception_v3-tf	.263
166	BiT-S-R50x3	.263
167	mobilenet_v1_0.75_224	.263
168	mobilenet_v1_0.25_224	.263
169	voneresnet-50-robust	.263
170	alexnet_random_linf8_perturb	.263
171	resnet34_imagenet_full	.263
172	resnet50_imagenet_full	.263
173	BiT-S-R152x2	.256
174	mobilenet_v1_0.25_192	.256
175	grcnn	.256
176	resnet50_hvs_wzc	.256
177	resnet50_st_wzc_seed6_2_323	.256
178	CORnet-S	.250
179	inception_v1-tf	.250
180	mobilenet_v2_1.0_96	.250
181	mobilenet_v1_0.75_128	.250
182	mobilenet_v1_0.75_160	.250
183	mobilenet_v1_0.25_128	.250
184	resnet-152_v2_pytorch	.250
185	pnasnet_large_pytorch	.250
186	nasnet_large	.250
187	densenet-121-keras	.244
188	BiT-S-R50x1	.244
189	resnet-152_v1-tf	.244
190	resnet-50_v2-tf	.244
191	vgg-19-keras	.244
192	xception-keras	.244
193	cv_18_dagger_408_pretrained	.244
194	custom_model_cv_18_dagger_408	.244
195	cvt_cvt-21-384-in1k_4_LucyV4	.244
196	densenet-121	.244
197	vgg-16-keras	.237
198	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.237
199	resnet_101_v2	.237
200	resnet_101_v1	.237
201	ReAlnet03	.237
202	pnasnet_large-tf	.231
203	resnet50_moco_v2	.231
204	resnet50-VITO-8deg-cc	.231
205	nasnet_mobile-tf	.225
206	ReAlnet04	.225
207	deit_base_imagenet_full_seed-0	.225
208	nasnet_mobile	.225
209	resnet50_ewconplus_wzc_seed6_2_323	.225
210	mobilenet_v2_0.5_96	.219
211	resnet50-SIN_IN	.219
212	BiT-S-R152x4	.219
213	alexnet_robust_correct	.219
214	resnet50-moclr8deg	.219
215	ReAlnet08	.219
216	ReAlnet09	.219
217	deit_small_imagenet_full_seed-0	.219
218	inception_v1	.219
219	resnet50	.212
220	antialias-resnet152	.212
221	pnasnet_large_halfPrecision	.212
222	pnasnet_large	.212
223	ReAlnet02	.212
224	resnet50_robust_l2_eps1	.206
225	resnet_152_v1	.206
226	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.200
227	ViT_L_32_imagenet1k	.200
228	resnet-18	.200
229	ReAlnet10	.200
230	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.194
231	alexnet_linf_8_robust	.194
232	regnet_y_400mf	.194
233	Res2Net50_26w_4s	.194
234	resnet50_eMMCR_Vanilla	.194
235	resnet_SIN_IN_FT_IN	.188
236	vonegrcnn_47e	.188
237	resnet50-SIN_IN_IN	.188
238	inception_v2-tf	.188
239	vgg_19	.188
240	xception	.188
241	vonegrcnn_62e_nobn	.181
242	ReAlnet06	.181
243	ReAlnet01	.181
244	vonegrcnn_47e	.181
245	resnet-50_v1-tf	.175
246	vonegrcnn_52e_full	.169
247	resnet-101_v1-tf	.169
248	voneresnet-50	.169
249	vonegrcnn_62e_nobn	.169
250	vonegrcnn_52e_full	.169
251	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.163
252	0.5x_resnet-18_LC_w_sh_1_iter	.163
253	resnet-34	.163
254	deit_small_imagenet_100_seed-0	.156
255	ReAlnet05	.156
256	squeezenet1_0	.150
257	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.150
258	resnet_152_v2	.150
259	squeezenet1_1	.144
260	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.144
261	vgg_16	.144
262	resnet50-vicregl0p75	.144
263	resnet-50-pytorch	.138
264	resnet50-sup	.138
265	antialiased-r50	.138
266	resnet_50_v1_spiking	.138
267	resnet50_tutorial	.138
268	resnet_50_v1	.138
269	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.131
270	voneresnet-50-non_stochastic	.125
271	ViT_B_16_imagenet1k	.125
272	resnet50_imagenet_10_seed-0	.119
273	ViT_B_32_imagenet1k	.106
274	resnet_50_v1_spiking_l4	.106
275	resnet_50_v1_spiking_l4a	.106
276	shufflenet_v2_x1_0	.100
277	alexnet_training_seed_09	.094
278	resnet50-simclr-vissl	.087
279	barlow-twins-resnet50	.081
280	resnet50_imagenet_100_seed-0	.081
281	convnext_small_imagenet_10_seed-0	.069
282	alexnet_training_seed_04	.069
283	alexnet_training_seed_07	.069
284	alexnet_training_seed_01	.069
285	alexnet_training_seed_01_fov4	.069
286	alexnet_training_seed_01_fov12	.069
287	alexnet_training_seed_01_fov16	.069
288	resnet-50_untrained	.062
289	mobilevit_small	.062
290	alexnet_training_seed_02	.062
291	alexnet_training_seed_08	.062
292	alexnet_training_seed_10	.062
293	deit_small_imagenet_10_seed-0	.062
294	convnext_small_imagenet_1_seed-0	.062
295	resnet50_imagenet_1_seed-0	.062
296	deit_small_imagenet_1_seed-0	.062
297	alexnet_training_seed_03	.062
298	alexnet_training_seed_05	.056
299	alexnet_training_seed_06	.056
300	resnet_50_v1_spiking_l3	.050
301	artResNet18_1	.044
302	resnet50-barlow	.037
303	resnet50-vicregl0p9	.037
304	ViT-B/32
305	resnet-18-LC_w_sh_100_iter_conv_init_m
306	BiT-M-R50x1
307	resnet-18-LC_w_sh_1_iter_conv_init_m
308	BiT-M-R152x2
309	resnet-18-LC_w_sh_1_iter_m
310	resnet-18-LC_w_sh_10_iter_m
311	BiT-M-R50x3
312	resnet-18-LC_w_sh_100_iter_m
313	resnet-18-LC_w_sh_10_iter_conv_init_m
314	FrankRobWobv0
315	0.5x_resnet-18_LC
316	CORnetZ_CIFAR10
317	resnet18-local_aggregation
318	r3m_resnet18
319	resnet18-deepcluster
320	CORnet-Z
321	vggface
322	my-model
323	resnet18-instance_recognition
324	0.5x_resnet-18_LC_w_sh_10_iter
325	r3m_resnet50
326	r3m_resnet34
327	resnet-18-LC_m
328	resnet18-supervised
329	r3m_resnet50_nocrop
330	resnet-18-LC_1st_conv_m
331	resnet-18-LC_conv_init_m
332	resnet18-contrastive_multiview
333	0.5x_resnet-18
334	RN50
335	0.5x_resnet-18_LC_w_sh_100_iter
336	RN50
337	resnet18-colorization
338	resnet18-relative_position
339	resnet18-autoencoder
340	resnet18-simclr
341	ViT_L_32
342	ViT_B_32
343	resnet18-depth_prediction
344	ViT_B_16
345	r3m_resnet34_nocrop
346	resnet18-contrastive_predictive
347	resnet-18-LC_untrained
348	resnet-18_untrained
349	resnet-50x2_untrained
350	dcgan
351	unet_entire
352	CORnetZ_CIFAR10_bs32_20_04
353	v1-pyr-nodown
354	pixels
355	dorinet_cornet_z
356	omnivore_swinT
357	omnivore_swinS
358	openclip
359	vonealexnet_gaussian_noise_std4_fixed
360	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
361	yudixie_resnet50_category_class_0_240908
362	yudixie_resnet50_distance_reg_0_240908
363	ConvLSTM
364	PredRNN
365	SimVP
366	TAU
367	briaai_rmbg_1_4
368	MIM
369	yolos_tiny
370	ReAlnet01_cornet
371	compact_resnet50_V4
372	ReAlnet02_cornet
373	yudixie_resnet18_rotation_reg_0_240719
374	yudixie_resnet50_rotation_reg_0_240908
375	eBarlow_lmda_02_1000ep
376	vit_base_patch14_dinov2-lvd142m
377	vit_base_patch14_reg4_dinov2-lvd142m
378	yudixie_resnet50_distance_rotation_0_240908
379	compact_resnet50_IT
380	yudixie_resnet50_distance_translation_0_240908
381	ReAlnet01_cornet_fov4
382	resnet18_ecoset_full
383	VOneCORnet-S
384	ReAlnet04_cornet
385	resnet101_ecoset_full
386	ReAlnet01_cornet_fov12
387	compact_vgg19_V4
388	vit_base_patch16_dinov3-lvd1689m
389	resnet152_ecoset_full
390	ReAlnet03_cornet
391	yudixie_resnet18_distance_translation_0_240719
392	aughost_fair_resnet18
393	resnet-18_test_m
394	yudixie_resnet18_distance_rotation_0_240719
395	ReAlnet05_cornet
396	yudixie_resnet18_category_class_0_240719
397	yudixie_resnet50_translation_reg_0_240908
398	compact_resnet50_robust_V4
399	yudixie_resnet18_translation_reg_0_240719
400	yudixie_resnet18_distance_translation_rotation_0_240719
401	compact_vgg19_IT
402	SeLaVi-AVE
403	hmax
404	ReAlnet06_cornet
405	ReAlnet01_cornet_fov16
406	yudixie_resnet50_translation_rotation_0_240908
407	ReAlnet01_ALL
408	r3d_18
409	yudixie_resnet18_distance_reg_0_240719
410	ReAlnet02_ALL
411	ReAlnet07_cornet
412	mc3_18
413	s3d
414	omnivore_swinB
415	resnet50-vicreg
416	ReAlnet08_cornet
417	mvit_v1_b
418	compact_cornets_V4
419	ReAlnet03_ALL
420	ReAlnet04_ALL
421	resnet18_imagenet21kP
422	ReAlnet09_cornet
423	compact_cornets_IT
424	SeLaVi-Kinetics400
425	ReAlnet05_ALL
426	SeLaVi-VGG-Sound
427	SeLaVi-Kinetics-Sound
428	ReAlnet06_ALL
429	compact_resnet50_robust_IT
430	ReAlnet10_cornet
431	yudixie_resnet50_imagenet1kpret_0_240908
432	yudixie_resnet50_distance_translation_rotation_0_240908
433	ReAlnet07_ALL
434	r2plus1d_18
435	mvit_v2_s
436	resnet34_ecoset_full
437	resnet50_ecoset_full
438	ReAlnet08_ALL
439	yudixie_resnet18_object_class_0_240719
440	yudixie_resnet50_cat_obj_class_all_latents_0_240908
441	yudixie_resnet18_cat_obj_class_all_latents_0_240719
442	yudixie_resnet18_random_0_240719
443	ReAlnet09_ALL
444	yudixie_resnet18_translation_rotation_0_240719
445	yudixie_resnet50_imagenet1kpret_0_240312
446	yudixie_resnet18_imagenet1kpret_0_240719
447	resnet50_primary_visual_cortex
448	yudixie_resnet50_object_class_0_240908
449	ReAlnet10_ALL
450	yudixie_resnet50_random_0_240908
451	resnet18_fair
452	pr1_stl10_disentangled_alpha04
453	predictive_coding_pc
454	yudixie_wbh_object_class_scaling_0415_run_0
455	yudixie_wbh_object_class_scaling_0415_run_3
456	yudixie_wbh_object_class_scaling_0415_imagenet
457	yudixie_wbh_object_class_scaling_0415_run_2
458	yudixie_wbh_object_class_scaling_0415_run_1
459	deepeisnn_ei_cifar10_vgg19
460	deepeisnn_ei_cifar10_resnet18
461	deepeisnn_ei_imagenet_resnet18
462	dinov2_vitl14_reg_lc_featread

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: Geirhos2021edge

Metric: top1