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("Geirhos2021uniformnoise-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:openai_ft_in1k	.821
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.818
3	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.816
4	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.805
5	deit_base_imagenet_full_seed-0	.799
6	deit_large_imagenet_full_seed-0	.796
7	convnext_xlarge:fb_in22k_ft_in1k	.776
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.772
9	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.772
10	convnext_large:fb_in22k_ft_in1k	.762
11	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.757
12	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.750
13	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.743
14	convnext_tiny:in12k_ft_in1k	.730
15	AdvProp_efficientnet-b7	.724
16	effnetv2m_custom384	.720
17	AdvProp_efficientnet-b6	.708
18	convnext_large_imagenet_full_seed-0	.704
19	resnext101_32x32d_wsl	.701
20	convnext_base_imagenet_full_seed-0	.701
21	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.701
22	vit_large_patch14_clip_336:laion2b_ft_in1k	.700
23	resnext101_32x48d_wsl	.696
24	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.696
25	resnext101_32x16d_wsl	.693
26	deit_small_imagenet_full_seed-0	.689
27	convnext_base:clip_laiona_augreg_ft_in1k_384	.686
28	focalnet_tiny_lrf_in1k	.680
29	efficientnet-b7	.674
30	fixres_resnext101_32x48d_wsl	.671
31	vit_large_patch14_clip_224:laion2b_ft_in1k	.670
32	convnext_small_imagenet_full_seed-0	.669
33	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.657
34	AdvProp_efficientnet-b4	.656
35	AT_efficientnet-b4	.656
36	pnasnet_large-tf	.654
37	resnext101_32x8d_wsl	.650
38	nasnet_large-tf	.649
39	vit_base_patch16_clip_224:openai_ft_in1k	.644
40	pnasnet_large	.641
41	resnet50-SIN	.632
42	vit_relpos_base_patch16_clsgap_224:sw_in1k	.632
43	inception_v4-tf	.627
44	convnext_tiny_imagenet_full_seed-0	.627
45	cv_18_dagger_408_pretrained	.626
46	cvt_cvt-21-224-in1k_4_LucyV4	.621
47	pnasnet_large_pytorch	.621
48	ViT_L_32_imagenet1k	.618
49	AT_efficientnet-b2	.618
50	AdvProp_efficientnet-b2	.618
51	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.616
52	nasnet_large	.616
53	AdvProp_efficientnet-b8	.613
54	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.604
55	resnet-101_v2-tf	.599
56	resnet-152_v2-tf	.595
57	ViT_B_32_imagenet1k	.586
58	resnet-152_v2_pytorch	.579
59	inception_v4	.578
60	inception_v2-tf	.575
61	resnet_101_v2	.573
62	resnet50-moclr8deg	.571
63	cvt_cvt-21-384-in1k_4_LucyV4	.568
64	densenet-201-keras	.561
65	densenet-169-keras	.560
66	densenet-201	.560
67	densenet_201_pytorch	.560
68	densenet-169	.560
69	resnet-50_v2-tf	.554
70	inception_v3_pytorch	.554
71	AdvProp_efficientnet-b0	.551
72	xception-keras	.549
73	xception	.547
74	cvt_cvt-13-224-in1k_4_LucyV4	.546
75	inception_v3-tf	.542
76	cvt_cvt-13-384-in1k_4_LucyV4	.542
77	convnext_tiny_sup	.540
78	antialias-resnet152	.540
79	effnetb1_272x240	.535
80	BiT-S-R101x1	.530
81	resnet152_imagenet_full	.530
82	inception_v1-tf	.524
83	resnet50_ewconplus_wzc	.522
84	resnet_152_v1	.516
85	inception_v3	.515
86	antialiased-rnext101_32x8d	.514
87	BiT-S-R152x2	.511
88	nasnet_mobile	.507
89	convnext_femto_ols:d1_in1k	.507
90	densenet-121-keras	.506
91	densenet-121	.506
92	BiT-S-R152x4	.505
93	resnet-152_v1-tf	.505
94	resnet50_moco_v2	.501
95	efficientnet_b0	.499
96	resnet50-vitoimagevidnet8	.499
97	resnet_152_v2	.497
98	resnet_SIN_IN_FT_IN	.496
99	resnet50-SIN_IN_IN	.496
100	resnet50-SIN_IN	.496
101	resnet_101_v1	.487
102	resnet-101_v1-tf	.486
103	resnet50-VITO-8deg-cc	.486
104	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.481
105	grcnn_109	.480
106	BiT-S-R50x3	.479
107	voneresnet-50-non_stochastic	.479
108	voneresnet-50	.477
109	resnet101_imagenet_full	.476
110	BiT-S-R101x3	.475
111	tv_efficientnet-b1	.475
112	CLIP-RN50	.471
113	BiT-S-R50x1	.469
114	vgg-19-keras	.469
115	vonegrcnn_62e_nobn	.468
116	vgg-16-keras	.464
117	resnet-50_v1-tf	.463
118	vonegrcnn_62e_nobn	.461
119	resnet_50_v2	.455
120	resnet-34	.453
121	Res2Net50_26w_4s	.449
122	vonegrcnn_47e	.449
123	resnet-50-pytorch	.445
124	resnet50-sup	.445
125	resnet50_tutorial	.445
126	resnet_50_v1	.445
127	mobilenet_v2_1-4_224_pytorch	.443
128	mobilenet_v2_1_4_224	.443
129	vonegrcnn_47e	.440
130	vonegrcnn_52e_full	.440
131	vonegrcnn_52e_full	.435
132	resnet50_imagenet_full	.430
133	resnet50	.427
134	antialiased-r50	.427
135	resnet_50_v1_spiking	.420
136	grcnn	.417
137	voneresnet-50-robust	.415
138	mobilenet_v2_1.4_224-tf	.414
139	mobilenet_v1_0.75_192	.410
140	mobilenet_v2_1_3_224	.410
141	mobilenet_v2_1.3_224-tf	.407
142	resnet34_imagenet_full	.406
143	mobilenet_v1_1.0_192	.405
144	blt_vs	.405
145	mobilenet_v2_1.0_192-tf	.404
146	mobilenet_v1_1.0_160	.404
147	inception_v1	.396
148	nasnet_mobile-tf	.395
149	CORnet-S	.394
150	efficientnet_b2_imagenet_full	.393
151	mobilenet_v1_0.5_160	.384
152	efficientnet_b0_imagenet_full	.383
153	resnet50_eMMCR_Vanilla	.381
154	convnext_small_imagenet_100_seed-0	.380
155	efficientnet_b1_imagenet_full	.380
156	mobilenet_v1_0.75_160	.375
157	mobilenet_v1_0.75_224	.374
158	resnet18_imagenet_full	.372
159	mobilenet_v1_1.0_128	.371
160	mobilenet_v2_0.75_192-tf	.369
161	mobilenet_v1_1.0_224	.366
162	regnet_y_400mf	.366
163	mobilenet_v2_1.0_160-tf	.359
164	mobilenet_v1_0.75_128	.357
165	mobilenet_v2_1_0_160	.355
166	vgg_16	.351
167	mobilenet_v2_0.5_192-tf	.350
168	vgg_19	.350
169	mobilenet_v2_1_0_128	.345
170	ReAlnet04	.345
171	mobilenet_v1_0.5_192	.344
172	AlexNet_SIN	.343
173	ReAlnet09	.341
174	mobilenet_v2_1.0_128-tf	.340
175	resnet_50_v1_spiking_l4a	.340
176	mobilenet_v1_0.5_224	.339
177	mobilenet_v2_0.75_160-tf	.339
178	mobilenet_v2_0_75_160	.335
179	resnet-18	.330
180	custom_model_cv_18_dagger_408	.330
181	mobilenet_v2_1_0_192	.330
182	ReAlnet06	.329
183	ReAlnet01	.329
184	mobilenet_v2_1.0_224-tf	.326
185	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.324
186	resnet50_robust_l2_eps1	.323
187	mobilenet_v2_1_0_224	.319
188	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.318
189	mobilenet_v2_0_75_192	.318
190	ReAlnet02	.318
191	ReAlnet08	.316
192	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.315
193	mobilenet_v2_0.75_224-tf	.314
194	ReAlnet05	.314
195	mobilenet_v2_0.75_128	.311
196	mobilenet_v1_0.5_128	.311
197	ReAlnet03	.310
198	mobilenet_v2_0_75_224	.309
199	ReAlnet10	.307
200	ReAlnet07	.301
201	mobilenet_v2_0.5_160	.300
202	mobilenet_v1_0.25_192	.294
203	deit_small_imagenet_100_seed-0	.292
204	mobilenet_v1_0.25_160	.291
205	mobilenet_v2_0.5_128	.291
206	mobilenet_v2_0_5_192	.290
207	mobilenet_v1_0.25_224	.287
208	mobilenet_v2_1.0_96	.285
209	shufflenet_v2_x1_0	.284
210	mobilenet_v2_0.75_96	.281
211	resnet50_l2_3_robust	.273
212	resnet-50-robust	.269
213	mobilenet_v2_0.35_192	.269
214	imagenet_l2_3_0	.269
215	resnet50_robust_l2_eps3	.269
216	0.5x_resnet-18_LC_w_sh_1_iter	.265
217	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.259
218	mobilenet_v2_0.35_128	.259
219	mobilenet_v2_0.5_224-tf	.258
220	mobilenet_v2_0_5_224	.256
221	mobilenet_v2_0.35_160	.255
222	mobilenet_v2_0.5_96	.250
223	mobilenet_v1_0.25_128	.247
224	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.242
225	resnet_50_v1_spiking_l4	.231
226	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.230
227	alexnet_early_checkpoint	.229
228	mobilenet_v2_0.35_224	.226
229	alexnet_random_linf8_perturb	.221
230	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.214
231	squeezenet1_1	.212
232	alexnet	.212
233	squeezenet1_0	.211
234	imagenet_l2_10_0	.201
235	mobilenet_v2_0.35_96	.196
236	alexnet_robust_correct	.194
237	resnet50_imagenet_100_seed-0	.181
238	alexnet_l2_3_robust	.180
239	alexnet-baseline	.177
240	alexnet	.177
241	alexnet	.177
242	alexnet	.177
243	alexnet	.177
244	alexnet	.177
245	alexnet	.177
246	alexnet	.177
247	alexnet_ks_torevert	.177
248	resnet50_linf_8_robust	.158
249	alexnet_linf_8_robust	.117
250	convnext_small_imagenet_10_seed-0	.090
251	deit_small_imagenet_1_seed-0	.089
252	resnet50-vicregl0p75	.087
253	convnext_small_imagenet_1_seed-0	.080
254	resnet50_imagenet_10_seed-0	.077
255	deit_small_imagenet_10_seed-0	.076
256	resnet50_imagenet_1_seed-0	.072
257	barlow-twins-resnet50	.069
258	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.066
259	resnet50-simclr-vissl	.064
260	resnet50-meshes-lt-100-original-pretrained	.062
261	resnet50-meshes-lt-100-original-scratch	.062
262	alexnet_training_seed_05	.062
263	alexnet_training_seed_06	.062
264	alexnet_training_seed_02	.062
265	alexnet_training_seed_04	.062
266	alexnet_training_seed_08	.062
267	alexnet_training_seed_10	.062
268	alexnet_training_seed_01	.062
269	alexnet_training_seed_03	.062
270	mobilevit_small	.060
271	resnet50-vicregl0p9	.060
272	alexnet_training_seed_09	.059
273	resnet50-barlow	.058
274	resnet-50_untrained	.058
275	artResNet18_1	.058
276	alexnet_training_seed_07	.056
277	resnet_50_v1_spiking_l3	.051
278	ViT-B/32
279	BiT-M-R50x1
280	resnet-18-LC_w_sh_100_iter_conv_init_m
281	resnet-18-LC_w_sh_1_iter_conv_init_m
282	BiT-M-R152x2
283	BiT-M-R50x3
284	resnet-18-LC_w_sh_10_iter_m
285	resnet-18-LC_w_sh_100_iter_m
286	resnet-18-LC_w_sh_10_iter_conv_init_m
287	FrankRobWobv0
288	resnet-18-LC_w_sh_1_iter_m
289	0.5x_resnet-18_LC
290	CORnetZ_CIFAR10
291	resnet18-local_aggregation
292	r3m_resnet18
293	CORnet-Z
294	vggface
295	my-model
296	resnet18-instance_recognition
297	resnet18-deepcluster
298	0.5x_resnet-18_LC_w_sh_10_iter
299	r3m_resnet50
300	r3m_resnet34
301	resnet-18-LC_m
302	resnet18-supervised
303	r3m_resnet50_nocrop
304	resnet-18-LC_1st_conv_m
305	resnet-18-LC_conv_init_m
306	resnet18-contrastive_multiview
307	0.5x_resnet-18
308	0.5x_resnet-18_LC_w_sh_100_iter
309	RN50
310	RN50
311	resnet18-colorization
312	resnet18-relative_position
313	v1-pyr-nodown
314	resnet18-simclr
315	resnet18-autoencoder
316	ViT_L_32
317	ViT_B_32
318	resnet18-depth_prediction
319	ViT_B_16
320	yudixie_resnet50_cat_obj_class_all_latents_0_240908
321	r3m_resnet34_nocrop
322	resnet18-contrastive_predictive
323	resnet-18-LC_untrained
324	resnet-18_untrained
325	resnet-50x2_untrained
326	dcgan
327	unet_entire
328	CORnetZ_CIFAR10_bs32_20_04
329	pixels
330	dorinet_cornet_z
331	omnivore_swinT
332	resnet50
333	openclip
334	vonealexnet_gaussian_noise_std4_fixed
335	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
336	yudixie_resnet50_imagenet1kpret_0_240312
337	yudixie_resnet50_category_class_0_240908
338	yudixie_resnet50_distance_reg_0_240908
339	resnet18_imagenet21kP
340	ConvLSTM
341	PredRNN
342	SimVP
343	TAU
344	MIM
345	hmax
346	yolos_tiny
347	ReAlnet01_cornet
348	briaai_rmbg_1_4
349	ReAlnet03_cornet
350	yudixie_resnet18_translation_reg_0_240719
351	yudixie_resnet18_distance_reg_0_240719
352	yudixie_resnet18_rotation_reg_0_240719
353	yudixie_resnet18_imagenet1kpret_0_240719
354	compact_resnet50_V4
355	yudixie_resnet50_rotation_reg_0_240908
356	yudixie_resnet50_distance_translation_0_240908
357	yudixie_resnet50_distance_rotation_0_240908
358	resnet18_ecoset_full
359	resnet34_ecoset_full
360	compact_resnet50_IT
361	resnet101_ecoset_full
362	resnet152_ecoset_full
363	ReAlnet04_cornet
364	compact_vgg19_V4
365	yudixie_resnet18_translation_rotation_0_240719
366	omnivore_swinS
367	resnet-18_test_m
368	yudixie_resnet18_category_class_0_240719
369	ReAlnet05_cornet
370	yudixie_resnet18_random_0_240719
371	yudixie_resnet50_translation_reg_0_240908
372	yudixie_resnet18_cat_obj_class_all_latents_0_240719
373	compact_vgg19_IT
374	ReAlnet06_cornet
375	SeLaVi-AVE
376	compact_resnet50_robust_V4
377	r3d_18
378	yudixie_resnet50_translation_rotation_0_240908
379	ReAlnet01_ALL
380	mc3_18
381	ReAlnet02_ALL
382	s3d
383	VOneCORnet-S
384	resnet50-vicreg
385	ReAlnet08_cornet
386	omnivore_swinB
387	ReAlnet04_ALL
388	mvit_v1_b
389	compact_cornets_V4
390	ReAlnet03_ALL
391	ReAlnet09_cornet
392	compact_cornets_IT
393	SeLaVi-Kinetics400
394	ReAlnet05_ALL
395	SeLaVi-VGG-Sound
396	ReAlnet06_ALL
397	mvit_v2_s
398	ReAlnet10_cornet
399	compact_resnet50_robust_IT
400	yudixie_resnet50_distance_translation_rotation_0_240908
401	ReAlnet07_ALL
402	SeLaVi-Kinetics-Sound
403	r2plus1d_18
404	resnet50_ecoset_full
405	yudixie_resnet18_object_class_0_240719
406	yudixie_resnet50_imagenet1kpret_0_240908
407	ReAlnet08_ALL
408	yudixie_resnet18_distance_translation_rotation_0_240719
409	yudixie_resnet18_distance_rotation_0_240719
410	ReAlnet09_ALL
411	yudixie_resnet18_distance_translation_0_240719
412	ReAlnet02_cornet
413	ReAlnet07_cornet
414	yudixie_resnet50_random_0_240908
415	yudixie_resnet50_object_class_0_240908
416	resnet50_primary_visual_cortex
417	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

1.00.

Note that scores are relative to this ceiling.

Data: Geirhos2021uniformnoise

Metric: top1