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("Geirhos2021stylized-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50-SIN_IN	.910
2	resnet50-SIN	.910
3	AlexNet_SIN	.786
4	AlexNet_SIN_fov4	.786
5	AlexNet_SIN_fov12	.786
6	AlexNet_SIN_fov16	.786
7	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.748
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.700
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.695
10	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.657
11	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.655
12	AdvProp_efficientnet-b7	.654
13	AdvProp_efficientnet-b6	.650
14	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.649
15	vit_large_patch14_clip_224:laion2b_ft_in1k	.649
16	vit_large_patch14_clip_224:openai_ft_in1k	.637
17	convnext_xlarge:fb_in22k_ft_in1k	.631
18	convnext_large:fb_in22k_ft_in1k	.613
19	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.609
20	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.605
21	AdvProp_efficientnet-b4	.599
22	AT_efficientnet-b4	.599
23	vit_large_patch14_clip_336:laion2b_ft_in1k	.599
24	AdvProp_efficientnet-b8	.595
25	efficientnet-b7	.594
26	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.588
27	effnetv2m_custom384	.586
28	vit_base_patch16_clip_224:openai_ft_in1k	.574
29	deit_large_imagenet_full_seed-0	.571
30	vit_relpos_base_patch16_clsgap_224:sw_in1k	.571
31	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.568
32	AT_efficientnet-b2	.566
33	AdvProp_efficientnet-b2	.566
34	convnext_base:clip_laiona_augreg_ft_in1k_384	.561
35	convnext_tiny_sup	.559
36	convnext_small_imagenet_full_seed-0	.557
37	convnext_large_imagenet_full_seed-0	.556
38	focalnet_tiny_lrf_in1k	.551
39	resnext101_32x16d_wsl	.547
40	resnext101_32x32d_wsl	.546
41	deit_base_imagenet_full_seed-0	.546
42	convnext_base_imagenet_full_seed-0	.546
43	convnext_tiny:in12k_ft_in1k	.544
44	convnext_tiny_imagenet_full_seed-0	.544
45	resnext101_32x48d_wsl	.540
46	resnext101_32x8d_wsl	.521
47	AdvProp_efficientnet-b0	.521
48	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.515
49	effnetb1_272x240	.514
50	deit_small_imagenet_full_seed-0	.512
51	ViT_L_32_imagenet1k	.492
52	fixres_resnext101_32x48d_wsl	.492
53	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.485
54	cvt_cvt-13-224-in1k_4_LucyV4	.482
55	cvt_cvt-13-384-in1k_4_LucyV4	.481
56	ViT_B_32_imagenet1k	.476
57	efficientnet_b0	.475
58	resnet-101_v2-tf	.466
59	cvt_cvt-21-224-in1k_4_LucyV4	.466
60	nasnet_large-tf	.464
61	cv_18_dagger_408_pretrained	.464
62	resnet-152_v2-tf	.458
63	efficientnet_b2_imagenet_full	.455
64	resnet_SIN_IN_FT_IN	.450
65	resnet50-SIN_IN_IN	.450
66	inception_v3_pytorch	.450
67	voneresnet-50-robust	.448
68	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.445
69	inception_v3-tf	.444
70	resnet50_robust_l2_eps1	.441
71	antialiased-rnext101_32x8d	.440
72	antialias-resnet152	.440
73	nasnet_large	.438
74	pnasnet_large-tf	.434
75	resnet-152_v1-tf	.431
76	convnext_small_imagenet_100_seed-0	.430
77	resnet-50_v2-tf	.427
78	efficientnet_b0_imagenet_full	.427
79	densenet-169-keras	.426
80	regnet_y_400mf	.426
81	resnet50_ewconplus_wzc	.426
82	inception_v3	.425
83	densenet-169	.424
84	mobilenet_v2_1.0_192-tf	.422
85	mobilenet_v2_0.75_192-tf	.422
86	efficientnet_b1_imagenet_full	.421
87	blt_vs	.420
88	tv_efficientnet-b1	.420
89	densenet-201-keras	.419
90	resnet-34	.419
91	densenet-201	.419
92	resnet_101_v1	.417
93	mobilenet_v2_0.75_224-tf	.416
94	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.416
95	resnet_152_v1	.416
96	nasnet_mobile	.415
97	convnext_femto_ols:d1_in1k	.414
98	mobilenet_v2_0.75_160-tf	.412
99	mobilenet_v2_1.0_160-tf	.410
100	vonegrcnn_62e_nobn	.410
101	BiT-S-R101x3	.410
102	pnasnet_large	.410
103	resnet_101_v2	.410
104	BiT-S-R101x1	.409
105	vonegrcnn_52e_full	.407
106	resnet-50-robust	.407
107	imagenet_l2_3_0	.407
108	resnet50_robust_l2_eps3	.407
109	vonegrcnn_47e	.407
110	resnet50-vitoimagevidnet8	.406
111	mobilenet_v2_0.5_160	.404
112	xception-keras	.404
113	vonegrcnn_52e_full	.404
114	vonegrcnn_47e	.403
115	BiT-S-R50x1	.401
116	inception_v2-tf	.401
117	mobilenet_v2_1_0_192	.401
118	vonegrcnn_62e_nobn	.401
119	voneresnet-50	.400
120	mobilenet_v2_1_0_160	.400
121	inception_v4-tf	.399
122	resnet-101_v1-tf	.399
123	mobilenet_v2_0.5_192-tf	.399
124	resnet50_l2_3_robust	.399
125	mobilenet_v2_1.0_128-tf	.398
126	mobilenet_v2_0.75_128	.398
127	resnet50-VITO-8deg-cc	.398
128	mobilenet_v2_0_75_160	.398
129	grcnn_109	.398
130	inception_v1-tf	.395
131	mobilenet_v2_0.75_96	.395
132	voneresnet-50-non_stochastic	.395
133	BiT-S-R152x2	.393
134	grcnn	.393
135	mobilenet_v1_0.75_160	.390
136	resnet50_linf_8_robust	.388
137	shufflenet_v2_x1_0	.386
138	cvt_cvt-21-384-in1k_4_LucyV4	.386
139	inception_v4	.386
140	mobilenet_v2_1.0_224-tf	.385
141	mobilenet_v2_1_0_128	.385
142	BiT-S-R50x3	.384
143	mobilenet_v2_0_75_224	.384
144	mobilenet_v2_1.4_224-tf	.383
145	inception_v1	.383
146	densenet-121-keras	.381
147	mobilenet_v1_0.75_128	.381
148	densenet-121	.381
149	antialiased-r50	.379
150	mobilenet_v2_0_75_192	.379
151	resnet-50_v1-tf	.378
152	resnet-18	.378
153	resnet_50_v2	.378
154	resnet_50_v1_spiking	.375
155	mobilenet_v2_1_0_224	.374
156	mobilenet_v1_0.75_192	.372
157	resnet-50-pytorch	.371
158	vgg-19-keras	.371
159	resnet50-sup	.371
160	mobilenet_v2_1.0_96	.371
161	resnet50_tutorial	.371
162	resnet_50_v1	.371
163	mobilenet_v2_1.3_224-tf	.370
164	mobilenet_v2_0_5_192	.370
165	mobilenet_v1_1.0_128	.369
166	ReAlnet03	.367
167	CORnet-S	.366
168	custom_model_cv_18_dagger_408	.366
169	ReAlnet07	.366
170	ReAlnet09	.366
171	mobilenet_v2_0_5_224	.365
172	ReAlnet10	.364
173	mobilenet_v2_0.35_192	.361
174	mobilenet_v2_0.5_224-tf	.360
175	resnet50	.359
176	ReAlnet08	.359
177	ReAlnet05	.359
178	mobilenet_v1_1.0_160	.356
179	mobilenet_v2_1_3_224	.356
180	mobilenet_v1_0.5_128	.355
181	ReAlnet04	.355
182	nasnet_mobile-tf	.354
183	Res2Net50_26w_4s	.354
184	mobilenet_v2_0.35_224	.352
185	resnet34_imagenet_full	.352
186	ReAlnet06	.352
187	xception	.352
188	mobilenet_v2_0.5_128	.351
189	resnet50_imagenet_full	.351
190	ReAlnet01	.351
191	mobilenet_v1_1.0_192	.347
192	mobilenet_v2_0.5_96	.346
193	mobilenet_v1_0.75_224	.346
194	resnet50_moco_v2	.346
195	mobilenet_v1_0.5_160	.345
196	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.344
197	mobilenet_v2_0.35_160	.344
198	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.343
199	BiT-S-R152x4	.341
200	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.341
201	ReAlnet02	.341
202	CLIP-RN50	.340
203	imagenet_l2_10_0	.338
204	pnasnet_large_pytorch	.338
205	resnet152_imagenet_full	.335
206	mobilenet_v2_0.35_128	.331
207	resnet101_imagenet_full	.331
208	mobilenet_v1_0.5_192	.329
209	resnet50_eMMCR_Vanilla	.329
210	resnet_152_v2	.328
211	mobilenet_v1_0.5_224	.325
212	mobilenet_v1_1.0_224	.325
213	resnet50-moclr8deg	.321
214	mobilenet_v2_0.35_96	.315
215	resnet18_imagenet_full	.315
216	mobilenet_v2_1-4_224_pytorch	.312
217	mobilenet_v2_1_4_224	.312
218	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.311
219	resnet-152_v2_pytorch	.309
220	vgg-16-keras	.306
221	alexnet_l2_3_robust	.306
222	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.305
223	alexnet_random_linf8_perturb	.305
224	squeezenet1_1	.302
225	alexnet_early_checkpoint	.302
226	mobilenet_v1_0.25_224	.301
227	alexnet	.299
228	mobilenet_v1_0.25_192	.297
229	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.290
230	0.5x_resnet-18_LC_w_sh_1_iter	.289
231	mobilenet_v1_0.25_160	.287
232	alexnet_robust_correct	.282
233	alexnet-baseline	.279
234	alexnet	.279
235	alexnet	.279
236	alexnet	.279
237	alexnet	.279
238	alexnet	.279
239	alexnet	.279
240	alexnet	.279
241	alexnet	.279
242	alexnet_ks_torevert	.279
243	alexnet_fov12	.279
244	alexnet_fov4	.279
245	alexnet_fov16	.279
246	alexnet_linf_8_robust	.265
247	vgg_16	.265
248	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.263
249	vgg_19	.255
250	squeezenet1_0	.254
251	mobilenet_v1_0.25_128	.253
252	resnet50_imagenet_100_seed-0	.251
253	resnet_50_v1_spiking_l4a	.241
254	deit_small_imagenet_100_seed-0	.184
255	resnet_50_v1_spiking_l4	.160
256	resnet50_imagenet_10_seed-0	.087
257	resnet50-vicregl0p9	.084
258	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.083
259	convnext_small_imagenet_10_seed-0	.072
260	mobilevit_small	.070
261	alexnet_training_seed_06	.070
262	convnext_small_imagenet_1_seed-0	.068
263	deit_small_imagenet_10_seed-0	.066
264	barlow-twins-resnet50	.065
265	alexnet_training_seed_09	.065
266	deit_small_imagenet_1_seed-0	.065
267	alexnet_training_seed_07	.064
268	resnet50-meshes-lt-100-original-scratch	.062
269	alexnet_training_seed_05	.062
270	alexnet_training_seed_02	.062
271	alexnet_training_seed_04	.062
272	alexnet_training_seed_10	.062
273	alexnet_training_seed_08	.062
274	alexnet_training_seed_01	.062
275	alexnet_training_seed_01_fov4	.062
276	alexnet_training_seed_01_fov12	.062
277	alexnet_training_seed_01_fov16	.062
278	alexnet_training_seed_03	.062
279	resnet50-meshes-lt-100-original-pretrained	.061
280	artResNet18_1	.059
281	resnet-50_untrained	.058
282	resnet50-vicregl0p75	.058
283	resnet50_imagenet_1_seed-0	.055
284	resnet_50_v1_spiking_l3	.050
285	resnet50-simclr-vissl	.045
286	resnet50-barlow	.044
287	ViT-B/32
288	BiT-M-R50x1
289	resnet-18-LC_w_sh_100_iter_conv_init_m
290	resnet-18-LC_w_sh_1_iter_conv_init_m
291	BiT-M-R152x2
292	BiT-M-R50x3
293	resnet-18-LC_w_sh_10_iter_m
294	resnet-18_test_m
295	resnet-18-LC_w_sh_100_iter_m
296	resnet-18-LC_w_sh_10_iter_conv_init_m
297	FrankRobWobv0
298	resnet-18-LC_w_sh_1_iter_m
299	0.5x_resnet-18_LC
300	CORnetZ_CIFAR10
301	resnet18-local_aggregation
302	r3m_resnet18
303	CORnet-Z
304	vggface
305	my-model
306	resnet18-instance_recognition
307	resnet18-deepcluster
308	0.5x_resnet-18_LC_w_sh_10_iter
309	r3m_resnet50
310	r3m_resnet34
311	resnet-18-LC_m
312	resnet18-supervised
313	r3m_resnet50_nocrop
314	resnet-18-LC_1st_conv_m
315	resnet-18-LC_conv_init_m
316	resnet18-contrastive_multiview
317	0.5x_resnet-18
318	0.5x_resnet-18_LC_w_sh_100_iter
319	RN50
320	RN50
321	resnet18-colorization
322	resnet18-relative_position
323	ViT_L_32
324	resnet18-simclr
325	resnet18-autoencoder
326	ViT_B_32
327	resnet18-depth_prediction
328	ViT_B_16
329	r3m_resnet34_nocrop
330	resnet18-contrastive_predictive
331	resnet-18-LC_untrained
332	resnet-18_untrained
333	resnet-50x2_untrained
334	dcgan
335	unet_entire
336	CORnetZ_CIFAR10_bs32_20_04
337	pixels
338	dorinet_cornet_z
339	v1-pyr-nodown
340	omnivore_swinT
341	resnet50
342	openclip
343	vonealexnet_gaussian_noise_std4_fixed
344	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
345	yudixie_resnet50_category_class_0_240908
346	yudixie_resnet50_distance_reg_0_240908
347	resnet18_imagenet21kP
348	ConvLSTM
349	PredRNN
350	SimVP
351	TAU
352	briaai_rmbg_1_4
353	MIM
354	yolos_tiny
355	densenet_201_pytorch
356	yudixie_resnet18_distance_translation_0_240719
357	ReAlnet01_cornet
358	hmax
359	yudixie_resnet18_translation_rotation_0_240719
360	compact_resnet50_V4
361	ReAlnet02_cornet
362	yudixie_resnet18_translation_reg_0_240719
363	yudixie_resnet18_distance_reg_0_240719
364	yudixie_resnet18_rotation_reg_0_240719
365	yudixie_resnet18_imagenet1kpret_0_240719
366	yudixie_resnet50_distance_rotation_0_240908
367	yudixie_resnet50_rotation_reg_0_240908
368	yudixie_resnet50_distance_translation_0_240908
369	resnet18_ecoset_full
370	resnet34_ecoset_full
371	ReAlnet01_cornet_fov4
372	ReAlnet03_cornet
373	ReAlnet01_cornet_fov12
374	resnet50_ecoset_full
375	compact_resnet50_IT
376	resnet101_ecoset_full
377	resnet152_ecoset_full
378	compact_vgg19_V4
379	yudixie_resnet18_distance_rotation_0_240719
380	ReAlnet05_cornet
381	yudixie_resnet18_category_class_0_240719
382	yudixie_resnet18_random_0_240719
383	SeLaVi-AVE
384	compact_vgg19_IT
385	compact_resnet50_robust_V4
386	ReAlnet06_cornet
387	ReAlnet01_cornet_fov16
388	r3d_18
389	yudixie_resnet50_translation_rotation_0_240908
390	ReAlnet07_cornet
391	mc3_18
392	ReAlnet02_ALL
393	s3d
394	VOneCORnet-S
395	ReAlnet08_cornet
396	omnivore_swinB
397	resnet50-vicreg
398	mvit_v1_b
399	ReAlnet03_ALL
400	compact_cornets_V4
401	ReAlnet09_cornet
402	compact_cornets_IT
403	omnivore_swinS
404	SeLaVi-Kinetics400
405	ReAlnet05_ALL
406	SeLaVi-VGG-Sound
407	ReAlnet06_ALL
408	ReAlnet10_cornet
409	yudixie_resnet50_distance_translation_rotation_0_240908
410	compact_resnet50_robust_IT
411	yudixie_resnet50_random_0_240908
412	ReAlnet07_ALL
413	SeLaVi-Kinetics-Sound
414	mvit_v2_s
415	r2plus1d_18
416	yudixie_resnet50_imagenet1kpret_0_240908
417	ReAlnet08_ALL
418	yudixie_resnet18_object_class_0_240719
419	yudixie_resnet18_cat_obj_class_all_latents_0_240719
420	ReAlnet09_ALL
421	yudixie_resnet18_distance_translation_rotation_0_240719
422	yudixie_resnet50_imagenet1kpret_0_240312
423	yudixie_resnet50_translation_reg_0_240908
424	ReAlnet04_cornet
425	yudixie_resnet50_object_class_0_240908
426	resnet50_primary_visual_cortex
427	yudixie_resnet50_cat_obj_class_all_latents_0_240908
428	ReAlnet10_ALL
429	ReAlnet01_ALL
430	ReAlnet04_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

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021stylized

Metric: top1