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("Geirhos2021phasescrambling-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	.895
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.894
3	vit_large_patch14_clip_224:openai_ft_in1k	.892
4	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.883
5	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.880
6	deit_large_imagenet_full_seed-0	.880
7	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.875
8	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.873
9	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.872
10	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.856
11	deit_base_imagenet_full_seed-0	.850
12	vit_large_patch14_clip_224:laion2b_ft_in1k	.844
13	vit_large_patch14_clip_336:laion2b_ft_in1k	.836
14	convnext_large:fb_in22k_ft_in1k	.836
15	convnext_xlarge:fb_in22k_ft_in1k	.833
16	focalnet_tiny_lrf_in1k	.822
17	convnext_base_imagenet_full_seed-0	.822
18	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.819
19	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.817
20	convnext_large_imagenet_full_seed-0	.817
21	convnext_small_imagenet_full_seed-0	.809
22	convnext_base:clip_laiona_augreg_ft_in1k_384	.805
23	vit_relpos_base_patch16_clsgap_224:sw_in1k	.803
24	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.800
25	cv_18_dagger_408_pretrained	.791
26	convnext_tiny_imagenet_full_seed-0	.789
27	convnext_tiny:in12k_ft_in1k	.786
28	effnetv2m_custom384	.784
29	vit_base_patch16_clip_224:openai_ft_in1k	.781
30	deit_small_imagenet_full_seed-0	.778
31	convnext_tiny_sup	.770
32	resnext101_32x32d_wsl	.769
33	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.767
34	fixres_resnext101_32x48d_wsl	.764
35	cvt_cvt-21-224-in1k_4_LucyV4	.761
36	cvt_cvt-21-384-in1k_4_LucyV4	.761
37	resnext101_32x16d_wsl	.753
38	resnext101_32x48d_wsl	.752
39	cvt_cvt-13-224-in1k_4_LucyV4	.750
40	resnext101_32x8d_wsl	.738
41	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.727
42	AdvProp_efficientnet-b7	.723
43	cvt_cvt-13-384-in1k_4_LucyV4	.717
44	convnext_femto_ols:d1_in1k	.713
45	resnet-152_v2_pytorch	.692
46	densenet-201-keras	.691
47	resnet50-vitoimagevidnet8	.691
48	densenet-201	.689
49	densenet_201_pytorch	.689
50	resnet_101_v2	.689
51	tv_efficientnet-b1	.684
52	resnet-101_v2-tf	.680
53	nasnet_large-tf	.678
54	AdvProp_efficientnet-b4	.678
55	AT_efficientnet-b4	.678
56	effnetb1_272x240	.675
57	nasnet_large	.672
58	AdvProp_efficientnet-b6	.670
59	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.666
60	resnet50-VITO-8deg-cc	.666
61	resnet50-SIN_IN	.664
62	BiT-S-R152x4	.661
63	BiT-S-R101x3	.661
64	resnet50-SIN	.661
65	grcnn_109	.661
66	AT_efficientnet-b2	.659
67	AdvProp_efficientnet-b2	.659
68	densenet-169	.658
69	voneresnet-50-robust	.656
70	resnet_101_v1	.656
71	resnet_152_v1	.656
72	BiT-S-R50x3	.655
73	inception_v1-tf	.653
74	densenet-169-keras	.653
75	efficientnet-b7	.653
76	resnet_50_v2	.653
77	Res2Net50_26w_4s	.652
78	resnet50_ewconplus_wzc	.652
79	BiT-S-R101x1	.650
80	inception_v2-tf	.650
81	BiT-S-R50x1	.648
82	AdvProp_efficientnet-b0	.648
83	antialias-resnet152	.648
84	densenet-121-keras	.645
85	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.645
86	pnasnet_large-tf	.644
87	resnet50_robust_l2_eps1	.644
88	densenet-121	.644
89	resnet-152_v2-tf	.641
90	inception_v4-tf	.639
91	pnasnet_large	.639
92	ViT_L_32_imagenet1k	.637
93	resnet_SIN_IN_FT_IN	.636
94	BiT-S-R152x2	.636
95	resnet50-SIN_IN_IN	.636
96	resnet-152_v1-tf	.633
97	antialiased-rnext101_32x8d	.633
98	grcnn	.633
99	resnet_152_v2	.633
100	xception-keras	.630
101	inception_v4	.628
102	resnet-50_v2-tf	.627
103	CLIP-RN50	.627
104	inception_v3_pytorch	.627
105	resnet-34	.625
106	inception_v3	.623
107	resnet101_imagenet_full	.622
108	resnet152_imagenet_full	.622
109	CORnet-S	.620
110	resnet-50-pytorch	.620
111	resnet50-sup	.620
112	resnet50_tutorial	.620
113	resnet_50_v1	.620
114	inception_v3-tf	.616
115	resnet-50_v1-tf	.614
116	antialiased-r50	.614
117	resnet50	.613
118	mobilenet_v2_1_3_224	.613
119	efficientnet_b2_imagenet_full	.609
120	mobilenet_v2_1.4_224-tf	.608
121	resnet-50-robust	.606
122	imagenet_l2_3_0	.606
123	resnet50_robust_l2_eps3	.606
124	resnet50_imagenet_full	.606
125	resnet-101_v1-tf	.605
126	vgg-19-keras	.602
127	vonegrcnn_47e	.598
128	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.597
129	mobilenet_v2_1.3_224-tf	.597
130	resnet_50_v1_spiking	.597
131	inception_v1	.597
132	efficientnet_b0	.595
133	voneresnet-50-non_stochastic	.595
134	custom_model_cv_18_dagger_408	.595
135	blt_vs	.595
136	efficientnet_b1_imagenet_full	.595
137	ViT_B_32_imagenet1k	.594
138	mobilenet_v2_1_0_192	.594
139	AlexNet_SIN	.594
140	AlexNet_SIN_fov4	.594
141	AlexNet_SIN_fov12	.594
142	AlexNet_SIN_fov16	.594
143	resnet50_l2_3_robust	.592
144	shufflenet_v2_x1_0	.592
145	vonegrcnn_47e	.589
146	resnet50-moclr8deg	.589
147	mobilenet_v2_1.0_224-tf	.588
148	mobilenet_v2_1_0_160	.588
149	mobilenet_v2_1.0_192-tf	.584
150	voneresnet-50	.584
151	vgg_16	.584
152	vonegrcnn_62e_nobn	.583
153	vonegrcnn_62e_nobn	.583
154	vgg-16-keras	.580
155	resnet34_imagenet_full	.580
156	mobilenet_v2_0_75_224	.578
157	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.577
158	ReAlnet09	.577
159	ReAlnet10	.577
160	vonegrcnn_52e_full	.577
161	mobilenet_v2_0.75_192-tf	.575
162	vonegrcnn_52e_full	.573
163	resnet-18	.573
164	vgg_19	.573
165	ReAlnet06	.573
166	resnet50_moco_v2	.572
167	ReAlnet05	.572
168	mobilenet_v2_1.0_160-tf	.569
169	regnet_y_400mf	.567
170	ReAlnet03	.567
171	ReAlnet04	.567
172	nasnet_mobile	.566
173	resnet50_linf_8_robust	.564
174	mobilenet_v2_0_75_192	.564
175	mobilenet_v2_1_0_224	.562
176	ReAlnet01	.562
177	AdvProp_efficientnet-b8	.559
178	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.558
179	alexnet	.558
180	mobilenet_v2_0.75_224-tf	.556
181	efficientnet_b0_imagenet_full	.553
182	ReAlnet07	.553
183	ReAlnet08	.550
184	ReAlnet02	.550
185	resnet18_imagenet_full	.548
186	mobilenet_v1_0.75_224	.545
187	mobilenet_v1_1.0_224	.545
188	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.544
189	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.541
190	resnet50_eMMCR_Vanilla	.539
191	xception	.536
192	squeezenet1_1	.533
193	mobilenet_v1_1.0_192	.530
194	alexnet_random_linf8_perturb	.530
195	mobilenet_v2_0.75_160-tf	.525
196	alexnet_early_checkpoint	.523
197	imagenet_l2_10_0	.523
198	mobilenet_v2_1-4_224_pytorch	.522
199	mobilenet_v2_1_4_224	.522
200	alexnet-baseline	.520
201	alexnet	.520
202	alexnet	.520
203	alexnet	.520
204	alexnet	.520
205	alexnet	.520
206	alexnet	.520
207	alexnet	.520
208	alexnet	.520
209	alexnet_ks_torevert	.520
210	alexnet_fov4	.520
211	alexnet_fov12	.520
212	alexnet_fov16	.520
213	mobilenet_v2_1_0_128	.519
214	mobilenet_v2_0.75_128	.517
215	mobilenet_v2_0_5_192	.517
216	mobilenet_v1_1.0_160	.516
217	mobilenet_v2_0.5_192-tf	.511
218	mobilenet_v2_1.0_128-tf	.511
219	mobilenet_v1_0.75_192	.511
220	mobilenet_v2_0_75_160	.511
221	mobilenet_v2_0_5_224	.506
222	resnet_50_v1_spiking_l4a	.505
223	mobilenet_v2_0.5_224-tf	.503
224	mobilenet_v2_0.5_160	.503
225	mobilenet_v2_1.0_96	.498
226	convnext_small_imagenet_100_seed-0	.498
227	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.495
228	alexnet_l2_3_robust	.494
229	mobilenet_v1_1.0_128	.492
230	mobilenet_v2_0.5_128	.491
231	mobilenet_v1_0.75_160	.489
232	mobilenet_v1_0.5_224	.484
233	mobilenet_v2_0.35_224	.483
234	pnasnet_large_pytorch	.481
235	nasnet_mobile-tf	.470
236	alexnet_robust_correct	.470
237	mobilenet_v2_0.75_96	.463
238	mobilenet_v1_0.5_128	.463
239	mobilenet_v1_0.5_192	.461
240	mobilenet_v2_0.35_192	.461
241	squeezenet1_0	.458
242	mobilenet_v1_0.5_160	.458
243	mobilenet_v1_0.75_128	.445
244	mobilenet_v2_0.35_160	.445
245	alexnet_linf_8_robust	.436
246	mobilenet_v1_0.25_160	.430
247	mobilenet_v2_0.5_96	.427
248	mobilenet_v1_0.25_224	.420
249	mobilenet_v2_0.35_96	.417
250	mobilenet_v2_0.35_128	.412
251	0.5x_resnet-18_LC_w_sh_1_iter	.406
252	mobilenet_v1_0.25_128	.398
253	mobilenet_v1_0.25_192	.378
254	deit_small_imagenet_100_seed-0	.372
255	resnet50_imagenet_100_seed-0	.323
256	resnet_50_v1_spiking_l4	.286
257	convnext_small_imagenet_10_seed-0	.109
258	deit_small_imagenet_10_seed-0	.105
259	resnet50_imagenet_10_seed-0	.098
260	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.097
261	deit_small_imagenet_1_seed-0	.086
262	resnet50_imagenet_1_seed-0	.083
263	artResNet18_1	.080
264	resnet50-barlow	.073
265	alexnet_training_seed_06	.069
266	resnet_50_v1_spiking_l3	.067
267	resnet50-meshes-lt-100-original-scratch	.064
268	convnext_small_imagenet_1_seed-0	.064
269	barlow-twins-resnet50	.062
270	resnet50-simclr-vissl	.062
271	resnet-50_untrained	.062
272	alexnet_training_seed_05	.062
273	alexnet_training_seed_02	.062
274	alexnet_training_seed_04	.062
275	alexnet_training_seed_10	.062
276	alexnet_training_seed_08	.062
277	alexnet_training_seed_01	.062
278	alexnet_training_seed_01_fov4	.062
279	alexnet_training_seed_01_fov12	.062
280	alexnet_training_seed_01_fov16	.062
281	alexnet_training_seed_03	.062
282	resnet50-meshes-lt-100-original-pretrained	.061
283	alexnet_training_seed_09	.061
284	alexnet_training_seed_07	.059
285	resnet50-vicregl0p9	.059
286	resnet50-vicregl0p75	.041
287	mobilevit_small	.037
288	ViT-B/32
289	resnet-18-LC_w_sh_100_iter_conv_init_m
290	BiT-M-R50x1
291	resnet-18-LC_w_sh_1_iter_conv_init_m
292	BiT-M-R152x2
293	resnet-18-LC_w_sh_1_iter_m
294	resnet-18-LC_w_sh_10_iter_m
295	BiT-M-R50x3
296	resnet-18-LC_w_sh_100_iter_m
297	resnet-18-LC_w_sh_10_iter_conv_init_m
298	FrankRobWobv0
299	0.5x_resnet-18_LC
300	CORnetZ_CIFAR10
301	resnet18-local_aggregation
302	r3m_resnet18
303	resnet18-deepcluster
304	CORnet-Z
305	vggface
306	resnet18-instance_recognition
307	my-model
308	0.5x_resnet-18_LC_w_sh_10_iter
309	r3m_resnet50
310	resnet-18-LC_m
311	r3m_resnet34
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	resnet18-autoencoder
324	resnet18-simclr
325	ViT_L_32
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	v1-pyr-nodown
338	pixels
339	dorinet_cornet_z
340	omnivore_swinT
341	resnet50
342	openclip
343	vonealexnet_gaussian_noise_std4_fixed
344	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
345	yudixie_resnet50_object_class_0_240908
346	yudixie_resnet50_imagenet1kpret_0_240312
347	yudixie_resnet50_category_class_0_240908
348	resnet18_imagenet21kP
349	yudixie_resnet50_distance_reg_0_240908
350	ConvLSTM
351	PredRNN
352	SimVP
353	briaai_rmbg_1_4
354	TAU
355	yolos_tiny
356	MIM
357	hmax
358	ReAlnet01_cornet
359	yudixie_resnet18_distance_translation_0_240719
360	compact_resnet50_V4
361	ReAlnet03_cornet
362	yudixie_resnet18_translation_reg_0_240719
363	yudixie_resnet18_rotation_reg_0_240719
364	yudixie_resnet18_imagenet1kpret_0_240719
365	ReAlnet02_cornet
366	yudixie_resnet50_distance_translation_0_240908
367	yudixie_resnet50_rotation_reg_0_240908
368	yudixie_resnet50_distance_rotation_0_240908
369	resnet18_ecoset_full
370	VOneCORnet-S
371	resnet34_ecoset_full
372	ReAlnet01_cornet_fov4
373	resnet50_ecoset_full
374	compact_resnet50_IT
375	resnet101_ecoset_full
376	ReAlnet01_cornet_fov12
377	compact_vgg19_V4
378	resnet152_ecoset_full
379	ReAlnet04_cornet
380	yudixie_resnet18_translation_rotation_0_240719
381	yudixie_resnet18_distance_rotation_0_240719
382	resnet-18_test_m
383	yudixie_resnet18_category_class_0_240719
384	yudixie_resnet18_random_0_240719
385	yudixie_resnet18_cat_obj_class_all_latents_0_240719
386	yudixie_resnet50_translation_reg_0_240908
387	compact_resnet50_robust_V4
388	ReAlnet05_cornet
389	yudixie_resnet18_distance_translation_rotation_0_240719
390	compact_vgg19_IT
391	yudixie_resnet18_object_class_0_240719
392	ReAlnet06_cornet
393	SeLaVi-AVE
394	r3d_18
395	ReAlnet04_ALL
396	yudixie_resnet50_translation_rotation_0_240908
397	yudixie_resnet18_distance_reg_0_240719
398	ReAlnet07_cornet
399	mc3_18
400	ReAlnet02_ALL
401	s3d
402	omnivore_swinB
403	ReAlnet01_cornet_fov16
404	ReAlnet08_cornet
405	mvit_v1_b
406	resnet50-vicreg
407	ReAlnet01_ALL
408	compact_cornets_V4
409	ReAlnet03_ALL
410	ReAlnet09_cornet
411	compact_cornets_IT
412	ReAlnet05_ALL
413	omnivore_swinS
414	SeLaVi-Kinetics400
415	SeLaVi-VGG-Sound
416	ReAlnet06_ALL
417	SeLaVi-Kinetics-Sound
418	compact_resnet50_robust_IT
419	ReAlnet10_cornet
420	r2plus1d_18
421	yudixie_resnet50_random_0_240908
422	ReAlnet07_ALL
423	yudixie_resnet50_distance_translation_rotation_0_240908
424	mvit_v2_s
425	ReAlnet08_ALL
426	yudixie_resnet50_imagenet1kpret_0_240908
427	ReAlnet09_ALL
428	yudixie_resnet50_cat_obj_class_all_latents_0_240908
429	ReAlnet10_ALL
430	resnet50_primary_visual_cortex

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: Geirhos2021phasescrambling

Metric: top1