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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	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.963
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.944
3	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.925
4	vit_large_patch14_clip_224:laion2b_ft_in1k	.925
5	vit_large_patch14_clip_336:laion2b_ft_in1k	.906
6	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.900
7	vit_large_patch14_clip_224:openai_ft_in1k	.894
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.894
9	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.894
10	resnext101_32x32d_wsl	.881
11	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.881
12	convnext_base:clip_laiona_augreg_ft_in1k_384	.863
13	convnext_large:fb_in22k_ft_in1k	.844
14	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.825
15	convnext_xlarge:fb_in22k_ft_in1k	.812
16	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.800
17	convnext_base_fb_in22k_ft_in1k	.787
18	resnext101_32x48d_wsl	.775
19	resnext101_32x8d_wsl	.769
20	resnext101_32x16d_wsl	.762
21	vit_base_patch16_clip_224:openai_ft_in1k	.756
22	fixres_resnext101_32x48d_wsl	.731
23	effnetv2m_custom384	.719
24	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.700
25	convnext_tiny:in12k_ft_in1k	.694
26	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.669
27	AdvProp_efficientnet-b7	.662
28	convnext_base_fb_in1k	.637
29	deit3_base_patch16_224_fb_in22k_ft_in1k	.625
30	AdvProp_efficientnet-b4	.600
31	AdvProp_efficientnet-b6	.600
32	AT_efficientnet-b4	.600
33	AlexNet_SIN	.581
34	AlexNet_SIN_fov4	.581
35	AlexNet_SIN_fov12	.581
36	AlexNet_SIN_fov16	.581
37	AdvProp_efficientnet-b8	.575
38	effnetb1_272x240	.569
39	convnext_base_fb_in1k_gram_aligned_dinov3	.531
40	tv_efficientnet-b1	.506
41	grcnn_109	.506
42	CLIP-RN50	.481
43	resnet50-SIN	.469
44	AT_efficientnet-b2	.469
45	AdvProp_efficientnet-b2	.469
46	vit_relpos_base_patch16_clsgap_224:sw_in1k	.438
47	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.438
48	deit3_base_patch16_224_fb_in1k	.438
49	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.425
50	convnext_large_imagenet_full_seed-0	.412
51	convnext_base_imagenet_full_seed-0	.400
52	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.400
53	convnext_small_imagenet_full_seed-0	.394
54	AdvProp_efficientnet-b0	.388
55	focalnet_tiny_lrf_in1k	.388
56	densenet-201-keras	.381
57	densenet-201	.381
58	densenet_201_pytorch	.381
59	mobilenet_v2_0.5_224-tf	.369
60	mobilenet_v2_0.75_192-tf	.369
61	efficientnet_b0	.362
62	efficientnet-b7	.362
63	mobilenet_v2_1.3_224-tf	.362
64	mobilenet_v2_0.75_224-tf	.362
65	mobilenet_v2_1_0_128	.362
66	cvt_cvt-21-224-in1k_4_LucyV4	.356
67	mobilenet_v2_0.5_128	.350
68	blt_vs	.350
69	mobilenet_v2_0_5_224	.350
70	mobilenet_v2_1_3_224	.350
71	mobilenet_v2_0.35_160	.344
72	imagenet_l2_10_0	.344
73	mobilenet_v2_0_75_224	.344
74	mobilenet_v2_0_75_192	.344
75	convnext_tiny_imagenet_full_seed-0	.344
76	inception_v4-tf	.338
77	mobilenet_v1_0.25_160	.338
78	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.338
79	mobilenet_v2_0.35_224	.331
80	mobilenet_v2_1.4_224-tf	.331
81	resnet152_imagenet_full	.331
82	convnext_femto_ols:d1_in1k	.331
83	BiT-S-R101x3	.325
84	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.325
85	densenet-169-keras	.325
86	mobilenet_v1_0.75_192	.325
87	resnet50_linf_8_robust	.325
88	efficientnet_b0_imagenet_full	.325
89	mobilenet_v2_1-4_224_pytorch	.325
90	resnet18_imagenet_full	.325
91	mobilenet_v2_1_4_224	.325
92	densenet-169	.325
93	mobilenet_v2_0.75_128	.319
94	mobilenet_v2_0.35_192	.319
95	convnext_tiny_sup	.319
96	antialiased-rnext101_32x8d	.319
97	BiT-S-R101x1	.312
98	mobilenet_v2_0.5_192-tf	.312
99	mobilenet_v1_0.5_128	.312
100	resnet50_ewconplus_wzc	.312
101	efficientnet_b1_imagenet_full	.312
102	cvt_cvt-13-384-in1k_4_LucyV4	.312
103	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.312
104	mobilenet_v2_1.0_192-tf	.306
105	mobilenet_v1_0.5_192	.306
106	mobilenet_v2_0.35_96	.306
107	resnet50_l2_3_robust	.306
108	inception_v4	.306
109	resnet50_st_wzc_seed7_2_323	.306
110	resnet50_ewconplus_wzc_seed5_2__323	.306
111	mobilenet_v2_1.0_160-tf	.300
112	mobilenet_v2_1.0_224-tf	.300
113	mobilenet_v2_0_5_192	.300
114	mobilenet_v2_0_75_160	.300
115	mobilenet_v2_1_0_192	.300
116	convnext_small_imagenet_100_seed-0	.300
117	resnet50_st_wzc_seed5_2_323	.300
118	mobilenet_v2_0.5_160	.294
119	alexnet	.294
120	mobilenet_v1_1.0_192	.294
121	mobilenet_v1_0.5_160	.294
122	alexnet_ks_torevert	.294
123	alexnet_fov4	.294
124	alexnet_fov12	.294
125	alexnet_fov16	.294
126	resnet101_imagenet_full	.294
127	cvt_cvt-13-224-in1k_4_LucyV4	.294
128	mobilenet_v2_1_0_224	.294
129	resnet50_ewconplus_noseed_2_323	.294
130	resnet50_ewconplus_wzc_seed3_2_323	.294
131	resnet50_ewconplus_wzc_2_323	.294
132	mobilenet_v2_1.0_128-tf	.287
133	mobilenet_v2_0.75_160-tf	.287
134	resnet_50_v2	.287
135	resnet50_ewconplus_wzc_seed4_2_323	.287
136	resnet-50-robust	.281
137	resnet-101_v2-tf	.281
138	resnet-152_v2-tf	.281
139	mobilenet_v2_0.35_128	.281
140	alexnet_l2_3_robust	.281
141	imagenet_l2_3_0	.281
142	resnet50_robust_l2_eps3	.281
143	resnet50-vitoimagevidnet8	.281
144	resnet50_ewconplus_wzc_seed7_2_323	.281
145	resnet50_st_wzc_seed4_2_323	.281
146	mobilenet_v1_0.5_224	.275
147	mobilenet_v1_1.0_160	.275
148	alexnet_early_checkpoint	.275
149	ReAlnet07	.275
150	inception_v3	.275
151	resnet50_st_wzc_noseed_2_323	.275
152	resnet50_ewconplus_wzc_seed2_2__323	.275
153	mobilenet_v2_0.75_96	.269
154	mobilenet_v1_1.0_128	.269
155	mobilenet_v1_1.0_224	.269
156	resnet50_st_wzc_2	.269
157	mobilenet_v2_1_0_160	.269
158	inception_v3_pytorch	.269
159	deit_large_imagenet_full_seed-0	.269
160	efficientnet_b2_imagenet_full	.269
161	resnet50_st_wzc_2_323	.269
162	nasnet_large-tf	.263
163	inception_v3-tf	.263
164	BiT-S-R50x3	.263
165	mobilenet_v1_0.75_224	.263
166	mobilenet_v1_0.25_224	.263
167	voneresnet-50-robust	.263
168	alexnet_random_linf8_perturb	.263
169	resnet34_imagenet_full	.263
170	resnet50_imagenet_full	.263
171	BiT-S-R152x2	.256
172	mobilenet_v1_0.25_192	.256
173	grcnn	.256
174	resnet50_st_wzc_seed6_2_323	.256
175	CORnet-S	.250
176	inception_v1-tf	.250
177	mobilenet_v2_1.0_96	.250
178	mobilenet_v1_0.75_128	.250
179	mobilenet_v1_0.75_160	.250
180	mobilenet_v1_0.25_128	.250
181	resnet-152_v2_pytorch	.250
182	pnasnet_large_pytorch	.250
183	nasnet_large	.250
184	densenet-121-keras	.244
185	BiT-S-R50x1	.244
186	resnet-152_v1-tf	.244
187	resnet-50_v2-tf	.244
188	vgg-19-keras	.244
189	xception-keras	.244
190	cv_18_dagger_408_pretrained	.244
191	custom_model_cv_18_dagger_408	.244
192	cvt_cvt-21-384-in1k_4_LucyV4	.244
193	densenet-121	.244
194	vgg-16-keras	.237
195	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.237
196	resnet_101_v2	.237
197	resnet_101_v1	.237
198	ReAlnet03	.237
199	pnasnet_large-tf	.231
200	resnet50_moco_v2	.231
201	resnet50-VITO-8deg-cc	.231
202	nasnet_mobile-tf	.225
203	ReAlnet04	.225
204	deit_base_imagenet_full_seed-0	.225
205	nasnet_mobile	.225
206	resnet50_ewconplus_wzc_seed6_2_323	.225
207	mobilenet_v2_0.5_96	.219
208	resnet50-SIN_IN	.219
209	BiT-S-R152x4	.219
210	alexnet_robust_correct	.219
211	resnet50-moclr8deg	.219
212	ReAlnet08	.219
213	ReAlnet09	.219
214	deit_small_imagenet_full_seed-0	.219
215	inception_v1	.219
216	resnet50	.212
217	antialias-resnet152	.212
218	pnasnet_large_halfPrecision	.212
219	pnasnet_large	.212
220	ReAlnet02	.212
221	resnet50_robust_l2_eps1	.206
222	resnet_152_v1	.206
223	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.200
224	ViT_L_32_imagenet1k	.200
225	resnet-18	.200
226	ReAlnet10	.200
227	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.194
228	alexnet_linf_8_robust	.194
229	regnet_y_400mf	.194
230	Res2Net50_26w_4s	.194
231	resnet50_eMMCR_Vanilla	.194
232	resnet_SIN_IN_FT_IN	.188
233	vonegrcnn_47e	.188
234	resnet50-SIN_IN_IN	.188
235	inception_v2-tf	.188
236	vgg_19	.188
237	xception	.188
238	vonegrcnn_62e_nobn	.181
239	ReAlnet06	.181
240	ReAlnet01	.181
241	vonegrcnn_47e	.181
242	resnet-50_v1-tf	.175
243	vonegrcnn_52e_full	.169
244	resnet-101_v1-tf	.169
245	voneresnet-50	.169
246	vonegrcnn_62e_nobn	.169
247	vonegrcnn_52e_full	.169
248	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.163
249	0.5x_resnet-18_LC_w_sh_1_iter	.163
250	resnet-34	.163
251	deit_small_imagenet_100_seed-0	.156
252	ReAlnet05	.156
253	squeezenet1_0	.150
254	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.150
255	resnet_152_v2	.150
256	squeezenet1_1	.144
257	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.144
258	vgg_16	.144
259	resnet50-vicregl0p75	.144
260	resnet-50-pytorch	.138
261	resnet50-sup	.138
262	antialiased-r50	.138
263	resnet_50_v1_spiking	.138
264	resnet50_tutorial	.138
265	resnet_50_v1	.138
266	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.131
267	voneresnet-50-non_stochastic	.125
268	ViT_B_16_imagenet1k	.125
269	resnet50_imagenet_10_seed-0	.119
270	ViT_B_32_imagenet1k	.106
271	resnet_50_v1_spiking_l4	.106
272	resnet_50_v1_spiking_l4a	.106
273	shufflenet_v2_x1_0	.100
274	alexnet_training_seed_09	.094
275	resnet50-simclr-vissl	.087
276	barlow-twins-resnet50	.081
277	resnet50_imagenet_100_seed-0	.081
278	resnet50-meshes-lt-100-original-scratch	.069
279	convnext_small_imagenet_10_seed-0	.069
280	alexnet_training_seed_04	.069
281	alexnet_training_seed_07	.069
282	alexnet_training_seed_01	.069
283	alexnet_training_seed_01_fov4	.069
284	alexnet_training_seed_01_fov12	.069
285	alexnet_training_seed_01_fov16	.069
286	resnet-50_untrained	.062
287	resnet50-meshes-lt-100-original-pretrained	.062
288	mobilevit_small	.062
289	alexnet_training_seed_02	.062
290	alexnet_training_seed_08	.062
291	alexnet_training_seed_10	.062
292	deit_small_imagenet_10_seed-0	.062
293	convnext_small_imagenet_1_seed-0	.062
294	resnet50_imagenet_1_seed-0	.062
295	deit_small_imagenet_1_seed-0	.062
296	alexnet_training_seed_03	.062
297	alexnet_training_seed_05	.056
298	alexnet_training_seed_06	.056
299	resnet_50_v1_spiking_l3	.050
300	artResNet18_1	.044
301	resnet50-barlow	.037
302	resnet50-vicregl0p9	.037
303	ViT-B/32
304	resnet-18-LC_w_sh_100_iter_conv_init_m
305	BiT-M-R50x1
306	resnet-18-LC_w_sh_1_iter_conv_init_m
307	BiT-M-R152x2
308	resnet-18-LC_w_sh_1_iter_m
309	resnet-18-LC_w_sh_10_iter_m
310	BiT-M-R50x3
311	resnet-18-LC_w_sh_100_iter_m
312	resnet-18-LC_w_sh_10_iter_conv_init_m
313	FrankRobWobv0
314	0.5x_resnet-18_LC
315	CORnetZ_CIFAR10
316	resnet18-local_aggregation
317	r3m_resnet18
318	resnet18-deepcluster
319	CORnet-Z
320	vggface
321	my-model
322	resnet18-instance_recognition
323	0.5x_resnet-18_LC_w_sh_10_iter
324	r3m_resnet50
325	r3m_resnet34
326	resnet-18-LC_m
327	resnet18-supervised
328	r3m_resnet50_nocrop
329	resnet-18-LC_1st_conv_m
330	resnet-18-LC_conv_init_m
331	resnet18-contrastive_multiview
332	0.5x_resnet-18
333	RN50
334	0.5x_resnet-18_LC_w_sh_100_iter
335	RN50
336	resnet18-colorization
337	resnet18-relative_position
338	resnet18-autoencoder
339	resnet18-simclr
340	ViT_L_32
341	ViT_B_32
342	resnet18-depth_prediction
343	ViT_B_16
344	r3m_resnet34_nocrop
345	resnet18-contrastive_predictive
346	resnet-18-LC_untrained
347	resnet-18_untrained
348	resnet-50x2_untrained
349	dcgan
350	unet_entire
351	CORnetZ_CIFAR10_bs32_20_04
352	v1-pyr-nodown
353	pixels
354	dorinet_cornet_z
355	omnivore_swinT
356	omnivore_swinS
357	resnet50
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

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