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("Geirhos2021rotation-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitg14_reg_lc	.989
2	eva02_large_in22k	.986
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.985
4	dinov2_vitl14_reg_lc	.983
5	convnext_xxlarge_clip	.979
6	dinov2_vitl14_lc	.977
7	dinov2_vitg14_lc	.976
8	dinov2_vitl14_lc_res336	.975
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.969
10	vit_huge_clip336_laion	.969
11	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.966
12	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.966
13	vit_large_clip336_openai	.965
14	vit_large_patch14_clip_224:openai_ft_in1k	.964
15	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.960
16	convnext_large_clip_laion2b_finelayers	.955
17	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.954
18	vit_large_patch14_clip_336:laion2b_ft_in1k	.953
19	vit_large_patch14_clip_224:laion2b_ft_in1k	.951
20	custom_model_cv_18_dagger_408	.945
21	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.945
22	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.930
23	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.923
24	convnext_base:clip_laiona_augreg_ft_in1k_384	.922
25	convnext_large_in22k_supervised	.919
26	deit3_base_patch16_224_fb_in22k_ft_in1k	.915
27	resnet-152_v2_pytorch	.907
28	convnext_xlarge:fb_in22k_ft_in1k	.904
29	convnext_large:fb_in22k_ft_in1k	.903
30	effnetv2m_custom384	.898
31	resnet_101_v2	.896
32	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.896
33	resnext101_32x48d_wsl	.895
34	tv_efficientnet-b1	.892
35	convnext_tiny_sup	.891
36	vit_base_patch16_clip_224:openai_ft_in1k	.886
37	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.886
38	fixres_resnext101_32x48d_wsl	.885
39	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.882
40	convnext_base_fb_in22k_ft_in1k	.876
41	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.865
42	resnext101_32x32d_wsl	.864
43	resnet_152_v2	.864
44	resnext101_32x16d_wsl	.855
45	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.849
46	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.846
47	resnet_50_v2	.840
48	convnext_tiny:in12k_ft_in1k	.836
49	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.835
50	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
51	resnext101_32x8d_wsl	.832
52	deit_large_imagenet_full_seed-0	.829
53	deit3_base_patch16_224_fb_in1k	.820
54	convnext_small_imagenet_full_seed-0	.799
55	convnext_base_fb_in1k	.797
56	convnext_base_imagenet_full_seed-0	.796
57	convnext_large_imagenet_full_seed-0	.795
58	nasnet_large	.795
59	deit_base_imagenet_full_seed-0	.793
60	effnetb1_272x240	.787
61	regnety_032	.782
62	pnasnet_large	.780
63	nasnet_large-tf	.779
64	cv_18_dagger_408_pretrained	.778
65	pnasnet_large_halfPrecision	.778
66	seresnext50_32x4d	.777
67	pnasnet_large-tf	.776
68	deit_small_imagenet_full_seed-0	.772
69	cvt_cvt-13-224-in1k_4_LucyV4	.771
70	inception_v4	.767
71	inception_v4-tf	.766
72	focalnet_tiny_lrf_in1k	.765
73	AdvProp_efficientnet-b7	.764
74	convnext_tiny_imagenet_full_seed-0	.764
75	vit_relpos_base_patch16_clsgap_224:sw_in1k	.760
76	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.758
77	AdvProp_efficientnet-b0	.757
78	AT_efficientnet-b2	.752
79	AdvProp_efficientnet-b2	.752
80	AdvProp_efficientnet-b6	.750
81	resnet-152_v2-tf	.745
82	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.743
83	efficientnet-b7	.742
84	cvt_cvt-13-384-in1k_4_LucyV4	.742
85	cvt_cvt-21-224-in1k_4_LucyV4	.738
86	efficientnet_b0	.736
87	antialias-resnet152	.736
88	resnet50-moclr8deg	.734
89	resnet-101_v2-tf	.733
90	xception-keras	.733
91	densenet-201-keras	.729
92	densenet-201	.729
93	densenet_201_pytorch	.729
94	resnet_152_v1	.729
95	cvt_cvt-21-384-in1k_4_LucyV4	.727
96	resnet50_st_wzc_seed6_2_323	.727
97	resnet50_st_wzc_seed7_2_323	.727
98	BiT-S-R101x3	.726
99	BiT-S-R152x4	.725
100	BiT-S-R152x2	.725
101	CLIP-RN50	.725
102	resnet50_barlowtwins_linhead	.724
103	resnet50-VITO-8deg-cc	.724
104	efficientnet_b2_imagenet_full	.723
105	resnet152_imagenet_full	.722
106	resnet50_byol_linhead	.721
107	resnet50_st_wzc_2	.720
108	efficientnet_b1_imagenet_full	.720
109	resnet50-vitoimagevidnet8	.720
110	densenet-169-keras	.719
111	AdvProp_efficientnet-b4	.719
112	AT_efficientnet-b4	.719
113	densenet-169	.718
114	BiT-S-R101x1	.718
115	inception_v3-tf	.713
116	antialiased-rnext101_32x8d	.709
117	resnet50_simclr_linhead_01norm	.709
118	resnet50_ewconplus_wzc_seed2_2__323	.707
119	inception_v3	.705
120	convnext_femto_ols:d1_in1k	.704
121	eBarlow_lmda_02_1000ep	.703
122	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.702
123	resnet50_vicreg_linhead	.702
124	BiT-S-R50x1	.701
125	resnet101_imagenet_full	.701
126	blt_vs	.699
127	resnet-152_v1-tf	.698
128	resnet50_hvs_wzc	.697
129	Res2Net50_26w_4s	.696
130	BiT-S-R50x3	.695
131	inception_v2-tf	.695
132	resnet-50_v2-tf	.694
133	densenet-121-keras	.693
134	resnet-50_v1-tf	.692
135	densenet-121	.692
136	resnet50_moco_v2	.691
137	antialiased-r50	.691
138	grcnn_109	.691
139	mobilenet_v2_1.3_224-tf	.690
140	resnet50	.690
141	resnet50_imagenet_full	.689
142	resnet50_ewconplus_wzc_seed5_2__323	.689
143	resnet-101_v1-tf	.685
144	resnet-50-pytorch	.684
145	mobilenet_v2_1.4_224-tf	.684
146	resnet50-sup	.684
147	resnet50_tutorial	.684
148	nasnet_mobile	.684
149	resnet_50_v1	.684
150	resnet_101_v1	.680
151	resnet50_ewconplus_wzc	.679
152	resnet_SIN_IN_FT_IN	.678
153	voneresnet-50-non_stochastic	.678
154	resnet50-SIN_IN_IN	.678
155	grcnn	.676
156	mobilenet_v2_1_3_224	.676
157	resnet50_simsiam_linhead	.675
158	resnet50_eMMCR_Vanilla	.674
159	efficientnet_b0_imagenet_full	.673
160	ReAlnet01	.672
161	vonegrcnn_62e_nobn	.671
162	vonegrcnn_52e_full	.670
163	ReAlnet05	.669
164	ReAlnet04	.668
165	ReAlnet09	.667
166	ijepa_vith14_linhead	.667
167	ReAlnet07	.666
168	ReAlnet08	.665
169	vonegrcnn_62e_nobn	.665
170	ViT_L_32_imagenet1k	.665
171	inception_v1-tf	.662
172	regnet_y_400mf	.662
173	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.662
174	ReAlnet03	.661
175	vonegrcnn_52e_full	.661
176	vonegrcnn_47e	.660
177	mobilenet_v1_1.0_224	.657
178	ReAlnet06	.656
179	CORnet-S	.655
180	mobilenet_v2_1.0_224-tf	.655
181	vgg-16-keras	.655
182	vgg-19-keras	.655
183	vgg_19	.654
184	vonegrcnn_47e	.654
185	resnet34_imagenet_full	.651
186	ReAlnet10	.651
187	mobilenet_v1_0.75_224	.648
188	ReAlnet02	.648
189	resnet-34	.647
190	resnet50-SIN_IN	.645
191	voneresnet-50	.644
192	mobilenet_v2_1.0_160-tf	.641
193	convnext_base_fb_in1k_gram_aligned_dinov3	.640
194	resnet_50_v1_spiking	.635
195	resnet50_robust_l2_eps1	.634
196	mobilenet_v2_0.75_224-tf	.633
197	mobilenet_v1_0.75_192	.633
198	resnet18_imagenet_full	.632
199	mobilenet_v1_1.0_160	.631
200	eicircuit_resnet18_bn_20260919	.630
201	mobilenet_v2_1.0_192-tf	.629
202	AdvProp_efficientnet-b8	.627
203	mobilenet_v2_0.75_192-tf	.626
204	nasnet_mobile-tf	.625
205	mobilenet_v2_1_0_224	.624
206	vgg_16	.623
207	inception_v1	.622
208	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.622
209	xception	.618
210	mobilenet_v1_1.0_192	.617
211	mobilenet_v2_0.75_160-tf	.613
212	mobilenet_v2_1_0_192	.613
213	mobilenet_v2_0_75_192	.603
214	mobilenet_v2_0.5_224-tf	.602
215	mobilenet_v2_1_0_160	.601
216	mobilenet_v2_0_75_224	.600
217	ViT_B_32_imagenet1k	.596
218	mobilenet_v1_0.5_224	.594
219	resnet-18	.593
220	mobilenet_v2_0.5_192-tf	.592
221	mobilenet_v1_0.75_160	.592
222	mobilenet_v2_0_75_160	.591
223	mobilenet_v1_1.0_128	.583
224	shufflenet_v2_x1_0	.583
225	mobilenet_v2_0.75_128	.580
226	mobilenet_v1_0.5_192	.575
227	resnet_50_v1_spiking_l4a	.574
228	mobilenet_v2_0_5_224	.573
229	mobilenet_v2_1.0_128-tf	.570
230	mobilenet_v1_0.5_160	.570
231	mobilenet_v2_0.35_192	.569
232	voneresnet-50-robust	.564
233	mobilenet_v2_1-4_224_pytorch	.561
234	pnasnet_large_pytorch	.561
235	mobilenet_v2_1_4_224	.561
236	mobilenet_v2_0.35_224	.561
237	mobilenet_v1_0.75_128	.560
238	mobilenet_v2_0_5_192	.555
239	mobilenet_v2_0.5_160	.544
240	convnext_small_imagenet_100_seed-0	.544
241	mobilenet_v1_0.25_224	.543
242	mobilenet_v2_1_0_128	.536
243	mehrer2020_alexnet_training_seed_02	.529
244	resnet50-SIN	.528
245	mehrer2020_alexnet_training_seed_04	.528
246	mehrer2020_alexnet_training_seed_03	.526
247	mehrer2020_alexnet_training_seed_01	.525
248	mehrer2020_alexnet_training_seed_01_fov12	.525
249	mehrer2020_alexnet_training_seed_01_fov4	.525
250	mehrer2020_alexnet_training_seed_01_fov16	.525
251	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.525
252	resnet-50-robust	.523
253	imagenet_l2_3_0	.523
254	resnet50_robust_l2_eps3	.523
255	mehrer2020_alexnet_training_seed_05	.522
256	mobilenet_v2_1.0_96	.520
257	mobilenet_v2_0.5_128	.519
258	resnet50_l2_3_robust	.518
259	squeezenet1_0	.517
260	mobilenet_v2_0.35_160	.515
261	mobilenet_v2_0.75_96	.511
262	squeezenet1_1	.502
263	mobilenet_v1_0.5_128	.497
264	0.5x_resnet-18_LC_w_sh_1_iter	.490
265	alexnet_random_linf8_perturb	.489
266	mobilenet_v1_0.25_192	.487
267	alexnet	.482
268	alexnet_ks_torevert	.482
269	alexnet_fov4	.482
270	alexnet_fov12	.482
271	alexnet_fov16	.482
272	alexnet_early_checkpoint	.459
273	mobilenet_v2_0.35_128	.451
274	mobilenet_v2_0.5_96	.447
275	resnet50_linf_8_robust	.440
276	mobilenet_v1_0.25_160	.435
277	deit_small_imagenet_100_seed-0	.425
278	imagenet_l2_10_0	.420
279	mobilenet_v2_0.35_96	.406
280	mobilenet_v1_0.25_128	.405
281	resnet_50_v1_spiking_l4	.399
282	resnet50_imagenet_100_seed-0	.391
283	alexnet_robust_correct	.355
284	AlexNet_SIN	.354
285	AlexNet_SIN_fov4	.354
286	AlexNet_SIN_fov12	.354
287	AlexNet_SIN_fov16	.354
288	alexnet_l2_3_robust	.346
289	alexnet_linf_8_robust	.297
290	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.145
291	resnet50_imagenet_10_seed-0	.122
292	deit_small_imagenet_10_seed-0	.079
293	deit_small_imagenet_1_seed-0	.077
294	alexnet_training_seed_06	.074
295	convnext_small_imagenet_10_seed-0	.074
296	resnet50_imagenet_1_seed-0	.074
297	artResNet18_1	.072
298	resnet50-barlow	.071
299	resnet_50_v1_spiking_l3	.068
300	resnet50-simclr-vissl	.068
301	convnext_small_imagenet_1_seed-0	.064
302	resnet-50_untrained	.062
303	alexnet_training_seed_05	.062
304	alexnet_training_seed_02	.062
305	alexnet_training_seed_04	.062
306	alexnet_training_seed_08	.062
307	alexnet_training_seed_10	.062
308	alexnet_training_seed_01	.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	barlow-twins-resnet50	.060
314	mobilevit_small	.060
315	alexnet_training_seed_07	.059
316	alexnet_training_seed_09	.056
317	resnet50-vicregl0p9	.054
318	resnet50-vicregl0p75	.049
319	ViT-B/32
320	resnet-18-LC_w_sh_100_iter_conv_init_m
321	BiT-M-R50x1
322	resnet-18-LC_w_sh_1_iter_conv_init_m
323	BiT-M-R152x2
324	BiT-M-R50x3
325	resnet-18-LC_w_sh_10_iter_m
326	resnet-18-LC_w_sh_100_iter_m
327	resnet-18-LC_w_sh_10_iter_conv_init_m
328	FrankRobWobv0
329	resnet-18-LC_w_sh_1_iter_m
330	0.5x_resnet-18_LC
331	CORnetZ_CIFAR10
332	resnet18-local_aggregation
333	r3m_resnet18
334	resnet18-deepcluster
335	CORnet-Z
336	vggface
337	resnet18-instance_recognition
338	my-model
339	0.5x_resnet-18_LC_w_sh_10_iter
340	r3m_resnet50
341	r3m_resnet34
342	resnet-18-LC_m
343	resnet18-supervised
344	r3m_resnet50_nocrop
345	resnet-18-LC_1st_conv_m
346	resnet-18-LC_conv_init_m
347	resnet18-contrastive_multiview
348	0.5x_resnet-18
349	0.5x_resnet-18_LC_w_sh_100_iter
350	RN50
351	RN50
352	resnet18-colorization
353	resnet18-relative_position
354	resnet18-autoencoder
355	resnet18-simclr
356	ViT_L_32
357	ViT_B_32
358	resnet18-depth_prediction
359	ViT_B_16
360	r3m_resnet34_nocrop
361	resnet18-contrastive_predictive
362	resnet-18-LC_untrained
363	resnet-18_untrained
364	resnet-50x2_untrained
365	dcgan
366	unet_entire
367	CORnetZ_CIFAR10_bs32_20_04
368	v1-pyr-nodown
369	pixels
370	dorinet_cornet_z
371	omnivore_swinT
372	openclip
373	vonealexnet_gaussian_noise_std4_fixed
374	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
375	yudixie_resnet50_imagenet1kpret_0_240312
376	yudixie_resnet50_category_class_0_240908
377	yudixie_resnet50_distance_reg_0_240908
378	resnet18_imagenet21kP
379	ConvLSTM
380	PredRNN
381	SimVP
382	yolos_tiny
383	TAU
384	MIM
385	hmax
386	inception_v3_pytorch
387	ReAlnet01_cornet
388	yudixie_resnet18_distance_translation_0_240719
389	vit_base_patch16_dinov3-lvd1689m
390	compact_resnet50_V4
391	yudixie_resnet18_translation_reg_0_240719
392	yudixie_resnet18_distance_reg_0_240719
393	yudixie_resnet18_imagenet1kpret_0_240719
394	ReAlnet03_cornet
395	yudixie_resnet50_distance_rotation_0_240908
396	yudixie_resnet50_distance_translation_0_240908
397	vit_base_patch14_dinov2-lvd142m
398	vit_base_patch14_reg4_dinov2-lvd142m
399	compact_resnet50_IT
400	resnet34_ecoset_full
401	ReAlnet04_cornet
402	ReAlnet01_cornet_fov12
403	resnet152_ecoset_full
404	yudixie_resnet18_translation_rotation_0_240719
405	compact_vgg19_V4
406	yudixie_resnet18_distance_rotation_0_240719
407	ReAlnet05_cornet
408	yudixie_resnet18_category_class_0_240719
409	resnet-18_test_m
410	yudixie_resnet18_random_0_240719
411	yudixie_resnet50_translation_reg_0_240908
412	yudixie_resnet18_cat_obj_class_all_latents_0_240719
413	yudixie_resnet18_distance_translation_rotation_0_240719
414	yudixie_resnet18_object_class_0_240719
415	SeLaVi-AVE
416	ReAlnet06_cornet
417	compact_resnet50_robust_V4
418	r3d_18
419	ReAlnet07_cornet
420	mc3_18
421	ReAlnet02_ALL
422	s3d
423	VOneCORnet-S
424	ReAlnet08_cornet
425	omnivore_swinB
426	resnet50-vicreg
427	ReAlnet01_cornet_fov16
428	mvit_v1_b
429	compact_cornets_V4
430	yudixie_resnet18_rotation_reg_0_240719
431	ReAlnet03_ALL
432	ReAlnet09_cornet
433	compact_cornets_IT
434	omnivore_swinS
435	SeLaVi-Kinetics400
436	ReAlnet05_ALL
437	SeLaVi-VGG-Sound
438	ReAlnet06_ALL
439	compact_vgg19_IT
440	ReAlnet10_cornet
441	SeLaVi-Kinetics-Sound
442	compact_resnet50_robust_IT
443	yudixie_resnet50_imagenet1kpret_0_240908
444	yudixie_resnet50_random_0_240908
445	ReAlnet07_ALL
446	r2plus1d_18
447	yudixie_resnet50_distance_translation_rotation_0_240908
448	mvit_v2_s
449	ReAlnet08_ALL
450	yudixie_resnet50_cat_obj_class_all_latents_0_240908
451	ReAlnet09_ALL
452	yudixie_resnet50_rotation_reg_0_240908
453	yudixie_resnet50_translation_rotation_0_240908
454	ReAlnet02_cornet
455	resnet50_primary_visual_cortex
456	yudixie_resnet50_object_class_0_240908
457	ReAlnet10_ALL
458	briaai_rmbg_1_4
459	ReAlnet04_ALL
460	ReAlnet01_ALL
461	ReAlnet01_cornet_fov4
462	resnet101_ecoset_full
463	resnet18_ecoset_full
464	resnet18_fair
465	resnet50_ecoset_full
466	pr1_stl10_disentangled_alpha04
467	predictive_coding_pc
468	yudixie_wbh_object_class_scaling_0415_run_0
469	yudixie_wbh_object_class_scaling_0415_run_3
470	yudixie_wbh_object_class_scaling_0415_imagenet
471	yudixie_wbh_object_class_scaling_0415_run_2
472	yudixie_wbh_object_class_scaling_0415_run_1
473	deepeisnn_ei_cifar10_vgg19
474	deepeisnn_ei_cifar10_resnet18
475	deepeisnn_ei_imagenet_resnet18
476	dinov2_vitl14_reg_lc_featread
477	gabor_filter_entropy_4x4
478	gabor_filter_mean_abs_4x4_v2
479	gabor_filter_entropy_4x4_v2
480	gabor_filter_entropy_4x4_v2_forcedCosine

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: Geirhos2021rotation

Metric: top1