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("Geirhos2021contrast-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.998
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.998
3	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.996
4	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.996
5	vit_large_patch14_clip_224:openai_ft_in1k	.995
6	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.995
7	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.994
8	convnext_large:fb_in22k_ft_in1k	.994
9	convnext_tiny_imagenet_full_seed-0	.993
10	convnext_base_imagenet_full_seed-0	.993
11	convnext_large_imagenet_full_seed-0	.991
12	convnext_xlarge:fb_in22k_ft_in1k	.990
13	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.990
14	convnext_base:clip_laiona_augreg_ft_in1k_384	.990
15	convnext_tiny_sup	.989
16	vit_base_patch16_clip_224:openai_ft_in1k	.989
17	vit_relpos_base_patch16_clsgap_224:sw_in1k	.989
18	focalnet_tiny_lrf_in1k	.988
19	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.988
20	resnext101_32x48d_wsl	.985
21	cvt_cvt-21-224-in1k_4_LucyV4	.985
22	resnet-152_v2_pytorch	.985
23	convnext_small_imagenet_full_seed-0	.985
24	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.984
25	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.984
26	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.984
27	cvt_cvt-21-384-in1k_4_LucyV4	.983
28	fixres_resnext101_32x48d_wsl	.981
29	resnext101_32x32d_wsl	.979
30	tv_efficientnet-b1	.979
31	resnet_101_v2	.978
32	pnasnet_large-tf	.976
33	nasnet_large-tf	.975
34	resnet50_ewconplus_wzc	.974
35	cvt_cvt-13-224-in1k_4_LucyV4	.974
36	resnext101_32x16d_wsl	.973
37	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.973
38	pnasnet_large	.971
39	cvt_cvt-13-384-in1k_4_LucyV4	.968
40	resnet50-vitoimagevidnet8	.968
41	resnext101_32x8d_wsl	.964
42	convnext_tiny:in12k_ft_in1k	.964
43	resnet50-VITO-8deg-cc	.963
44	nasnet_large	.963
45	inception_v4-tf	.958
46	xception	.955
47	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.955
48	resnet_152_v2	.955
49	resnet_50_v2	.951
50	vit_large_patch14_clip_336:laion2b_ft_in1k	.950
51	ViT_L_32_imagenet1k	.949
52	resnet-152_v2-tf	.949
53	effnetv2m_custom384	.949
54	inception_v3-tf	.948
55	resnet-101_v2-tf	.948
56	ViT_B_16_imagenet1k	.948
57	blt_vs	.946
58	inception_v4	.946
59	densenet-169-keras	.945
60	densenet-169	.945
61	resnet-50_v2-tf	.944
62	xception-keras	.941
63	vit_large_patch14_clip_224:laion2b_ft_in1k	.940
64	cv_18_dagger_408_pretrained	.939
65	resnet50-moclr8deg	.936
66	ViT_B_32_imagenet1k	.934
67	densenet-201-keras	.932
68	densenet-201	.932
69	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.924
70	inception_v2-tf	.915
71	mobilenet_v2_1-4_224_pytorch	.915
72	mobilenet_v2_1_4_224	.915
73	efficientnet_b0	.904
74	resnet50_moco_v2	.900
75	BiT-S-R50x1	.899
76	antialiased-rnext101_32x8d	.899
77	BiT-S-R101x3	.891
78	densenet-121-keras	.880
79	antialias-resnet152	.880
80	densenet-121	.880
81	BiT-S-R50x3	.877
82	BiT-S-R152x2	.876
83	BiT-S-R101x1	.873
84	resnet50-SIN_IN	.871
85	vgg-19-keras	.871
86	BiT-S-R152x4	.871
87	convnext_small_imagenet_100_seed-0	.866
88	AT_efficientnet-b2	.864
89	AdvProp_efficientnet-b2	.864
90	vgg-16-keras	.863
91	deit_large_imagenet_full_seed-0	.863
92	AdvProp_efficientnet-b0	.860
93	inception_v1-tf	.859
94	resnet50-SIN	.856
95	resnet50_eMMCR_Vanilla	.855
96	resnet-152_v1-tf	.853
97	nasnet_mobile	.853
98	effnetb1_272x240	.845
99	resnet-101_v1-tf	.844
100	grcnn_109	.843
101	AdvProp_efficientnet-b6	.840
102	CLIP-RN50	.839
103	resnet_101_v1	.839
104	efficientnet-b7	.830
105	Res2Net50_26w_4s	.829
106	resnet_152_v1	.829
107	resnet_SIN_IN_FT_IN	.823
108	resnet50-SIN_IN_IN	.823
109	deit_base_imagenet_full_seed-0	.819
110	resnet-50-pytorch	.816
111	resnet50-sup	.816
112	resnet50_tutorial	.816
113	resnet_50_v1	.816
114	resnet-50_v1-tf	.811
115	antialiased-r50	.805
116	convnext_femto_ols:d1_in1k	.804
117	AdvProp_efficientnet-b7	.796
118	mobilenet_v2_1.4_224-tf	.796
119	resnet-34	.796
120	AdvProp_efficientnet-b4	.795
121	AT_efficientnet-b4	.795
122	resnet_50_v1_spiking	.795
123	resnet152_imagenet_full	.794
124	grcnn	.790
125	nasnet_mobile-tf	.781
126	deit_small_imagenet_full_seed-0	.777
127	voneresnet-50-non_stochastic	.776
128	regnet_y_400mf	.776
129	resnet50	.771
130	resnet101_imagenet_full	.767
131	inception_v3	.766
132	CORnet-S	.762
133	resnet-18	.745
134	resnet50_imagenet_full	.738
135	mobilenet_v2_1.0_224-tf	.733
136	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.718
137	vgg_16	.713
138	efficientnet_b2_imagenet_full	.709
139	mobilenet_v2_1.3_224-tf	.706
140	ReAlnet04	.706
141	mobilenet_v2_1.0_192-tf	.705
142	vgg_19	.704
143	resnet34_imagenet_full	.703
144	ReAlnet09	.698
145	efficientnet_b1_imagenet_full	.689
146	mobilenet_v2_1_0_192	.688
147	ReAlnet05	.682
148	mobilenet_v1_1.0_224	.681
149	resnet_50_v1_spiking_l4a	.680
150	mobilenet_v1_0.75_224	.676
151	vonegrcnn_62e_nobn	.676
152	ReAlnet06	.674
153	AlexNet_SIN	.669
154	ReAlnet02	.669
155	mobilenet_v2_1_0_224	.667
156	vonegrcnn_62e_nobn	.666
157	mobilenet_v2_1_3_224	.665
158	vonegrcnn_52e_full	.662
159	mobilenet_v2_1.0_160-tf	.661
160	resnet18_imagenet_full	.660
161	vonegrcnn_47e	.660
162	vonegrcnn_52e_full	.660
163	efficientnet_b0_imagenet_full	.654
164	ReAlnet01	.652
165	mobilenet_v2_0.75_192-tf	.651
166	vonegrcnn_47e	.649
167	mobilenet_v2_0.5_224-tf	.647
168	mobilenet_v1_0.5_224	.644
169	mobilenet_v2_0_75_192	.644
170	mobilenet_v1_0.75_192	.642
171	mobilenet_v1_0.75_160	.641
172	shufflenet_v2_x1_0	.641
173	mobilenet_v2_0.75_224-tf	.640
174	mobilenet_v1_1.0_192	.636
175	mobilenet_v2_0.75_160-tf	.636
176	ReAlnet03	.631
177	ReAlnet08	.624
178	voneresnet-50	.621
179	mobilenet_v2_1_0_160	.619
180	mobilenet_v1_1.0_160	.618
181	mobilenet_v2_0.5_192-tf	.615
182	mobilenet_v1_1.0_128	.608
183	AdvProp_efficientnet-b8	.599
184	ReAlnet10	.595
185	mobilenet_v2_0_75_160	.590
186	mobilenet_v1_0.5_160	.588
187	inception_v1	.585
188	ReAlnet07	.584
189	mobilenet_v2_0_5_224	.581
190	mobilenet_v1_0.5_192	.579
191	mobilenet_v2_0_5_192	.579
192	mobilenet_v1_0.75_128	.576
193	mobilenet_v2_0_75_224	.570
194	mobilenet_v2_0.35_224	.569
195	mobilenet_v2_0.5_160	.562
196	mobilenet_v2_0.75_128	.562
197	mobilenet_v2_0.35_192	.556
198	mobilenet_v2_1.0_128-tf	.552
199	mobilenet_v2_1.0_96	.547
200	mobilenet_v2_0.5_128	.544
201	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.541
202	mobilenet_v2_0.75_96	.539
203	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.539
204	squeezenet1_0	.526
205	squeezenet1_1	.520
206	mobilenet_v1_0.25_224	.507
207	mobilenet_v2_0.35_160	.505
208	0.5x_resnet-18_LC_w_sh_1_iter	.502
209	mobilenet_v2_1_0_128	.501
210	mobilenet_v1_0.5_128	.492
211	mobilenet_v1_0.25_192	.448
212	resnet_50_v1_spiking_l4	.439
213	alexnet-baseline	.435
214	alexnet	.435
215	alexnet	.435
216	alexnet	.435
217	alexnet	.435
218	alexnet	.435
219	alexnet	.435
220	alexnet_random_linf8_perturb	.435
221	alexnet	.435
222	alexnet_ks_torevert	.435
223	mobilenet_v1_0.25_160	.430
224	resnet50_robust_l2_eps1	.425
225	mobilenet_v2_0.5_96	.420
226	voneresnet-50-robust	.415
227	mobilenet_v2_0.35_128	.412
228	alexnet	.410
229	alexnet_early_checkpoint	.395
230	deit_small_imagenet_100_seed-0	.394
231	mobilenet_v2_0.35_96	.376
232	custom_model_cv_18_dagger_408	.369
233	mobilenet_v1_0.25_128	.365
234	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.346
235	resnet50_imagenet_100_seed-0	.343
236	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.309
237	resnet-50-robust	.302
238	imagenet_l2_3_0	.302
239	resnet50_robust_l2_eps3	.302
240	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.299
241	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.282
242	resnet50_l2_3_robust	.281
243	imagenet_l2_10_0	.198
244	alexnet_l2_3_robust	.195
245	alexnet_robust_correct	.194
246	resnet50_linf_8_robust	.172
247	alexnet_linf_8_robust	.124
248	resnet50_imagenet_10_seed-0	.100
249	resnet50-vicregl0p9	.100
250	resnet50-barlow	.083
251	convnext_small_imagenet_10_seed-0	.079
252	artResNet18_1	.075
253	resnet50_imagenet_1_seed-0	.072
254	deit_small_imagenet_1_seed-0	.072
255	convnext_small_imagenet_1_seed-0	.070
256	deit_small_imagenet_10_seed-0	.069
257	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.066
258	resnet-50_untrained	.065
259	barlow-twins-resnet50	.064
260	resnet_50_v1_spiking_l3	.064
261	resnet50-meshes-lt-100-original-pretrained	.062
262	resnet50-meshes-lt-100-original-scratch	.062
263	alexnet_training_seed_05	.062
264	alexnet_training_seed_06	.062
265	alexnet_training_seed_02	.062
266	alexnet_training_seed_04	.062
267	alexnet_training_seed_10	.062
268	alexnet_training_seed_07	.062
269	alexnet_training_seed_01	.062
270	alexnet_training_seed_03	.062
271	alexnet_training_seed_09	.062
272	resnet50-vicregl0p75	.060
273	alexnet_training_seed_08	.052
274	resnet50-simclr-vissl	.041
275	ViT-B/32
276	resnet-18-LC_w_sh_100_iter_conv_init_m
277	BiT-M-R50x1
278	resnet-18-LC_w_sh_1_iter_conv_init_m
279	resnet-18-LC_w_sh_1_iter_m
280	BiT-M-R152x2
281	resnet-18-LC_w_sh_10_iter_m
282	BiT-M-R50x3
283	resnet-18-LC_w_sh_100_iter_m
284	resnet-18-LC_w_sh_10_iter_conv_init_m
285	FrankRobWobv0
286	0.5x_resnet-18_LC
287	CORnetZ_CIFAR10
288	resnet18-local_aggregation
289	r3m_resnet18
290	CORnet-Z
291	resnet18-deepcluster
292	vggface
293	my-model
294	resnet18-instance_recognition
295	0.5x_resnet-18_LC_w_sh_10_iter
296	r3m_resnet50
297	r3m_resnet34
298	resnet-18-LC_m
299	r3m_resnet50_nocrop
300	resnet18-supervised
301	resnet-18-LC_1st_conv_m
302	resnet-18-LC_conv_init_m
303	resnet18-contrastive_multiview
304	0.5x_resnet-18
305	RN50
306	0.5x_resnet-18_LC_w_sh_100_iter
307	RN50
308	resnet18-colorization
309	resnet18-relative_position
310	resnet18-autoencoder
311	resnet18-simclr
312	ViT_L_32
313	ViT_B_32
314	resnet18-depth_prediction
315	ViT_B_16
316	r3m_resnet34_nocrop
317	resnet18-contrastive_predictive
318	resnet-18-LC_untrained
319	resnet-18_untrained
320	resnet-50x2_untrained
321	dcgan
322	unet_entire
323	CORnetZ_CIFAR10_bs32_20_04
324	v1-pyr-nodown
325	pixels
326	dorinet_cornet_z
327	omnivore_swinT
328	resnet50
329	openclip
330	vonealexnet_gaussian_noise_std4_fixed
331	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
332	resnet18_ecoset_full
333	yudixie_resnet50_distance_reg_0_240908
334	resnet18_imagenet21kP
335	ConvLSTM
336	PredRNN
337	SimVP
338	yolos_tiny
339	TAU
340	hmax
341	briaai_rmbg_1_4
342	densenet_201_pytorch
343	pnasnet_large_pytorch
344	inception_v3_pytorch
345	compact_resnet50_V4
346	ReAlnet01_cornet
347	yudixie_resnet18_rotation_reg_0_240719
348	ReAlnet02_cornet
349	yudixie_resnet50_rotation_reg_0_240908
350	yudixie_resnet50_translation_reg_0_240908
351	yudixie_resnet50_distance_translation_0_240908
352	compact_resnet50_IT
353	yudixie_resnet50_distance_rotation_0_240908
354	ReAlnet04_cornet
355	ReAlnet03_cornet
356	resnet50_ecoset_full
357	yudixie_resnet50_translation_rotation_0_240908
358	resnet152_ecoset_full
359	compact_vgg19_V4
360	yudixie_resnet18_translation_rotation_0_240719
361	yudixie_resnet18_distance_rotation_0_240719
362	resnet-18_test_m
363	yudixie_resnet18_category_class_0_240719
364	ReAlnet05_cornet
365	yudixie_resnet18_random_0_240719
366	yudixie_resnet18_cat_obj_class_all_latents_0_240719
367	compact_vgg19_IT
368	SeLaVi-AVE
369	yudixie_resnet18_distance_translation_rotation_0_240719
370	yudixie_resnet18_object_class_0_240719
371	ReAlnet06_cornet
372	yudixie_resnet18_imagenet1kpret_0_240719
373	yudixie_resnet18_translation_reg_0_240719
374	yudixie_resnet18_distance_reg_0_240719
375	compact_resnet50_robust_V4
376	r3d_18
377	ReAlnet01_ALL
378	ReAlnet07_cornet
379	ReAlnet02_ALL
380	mc3_18
381	s3d
382	VOneCORnet-S
383	omnivore_swinB
384	resnet50-vicreg
385	ReAlnet08_cornet
386	mvit_v1_b
387	ReAlnet03_ALL
388	compact_cornets_V4
389	ReAlnet04_ALL
390	omnivore_swinS
391	ReAlnet05_ALL
392	compact_cornets_IT
393	SeLaVi-VGG-Sound
394	SeLaVi-Kinetics-Sound
395	ReAlnet10_cornet
396	ReAlnet06_ALL
397	yudixie_resnet50_imagenet1kpret_0_240908
398	compact_resnet50_robust_IT
399	mvit_v2_s
400	r2plus1d_18
401	ReAlnet07_ALL
402	yudixie_resnet50_distance_translation_rotation_0_240908
403	yudixie_resnet50_random_0_240908
404	SeLaVi-Kinetics400
405	resnet101_ecoset_full
406	ReAlnet08_ALL
407	resnet34_ecoset_full
408	yudixie_resnet50_cat_obj_class_all_latents_0_240908
409	yudixie_resnet50_object_class_0_240908
410	ReAlnet09_ALL
411	yudixie_resnet18_distance_translation_0_240719
412	yudixie_resnet50_imagenet1kpret_0_240312
413	resnet50_primary_visual_cortex
414	ReAlnet10_ALL
415	ReAlnet09_cornet
416	yudixie_resnet50_category_class_0_240908

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: Geirhos2021contrast

Metric: top1