Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021eidolonII-top1")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50-SIN	X
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	X
3	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	X
4	AdvProp_efficientnet-b6	X
5	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	X
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	X
7	vit_large_patch14_clip_224:openai_ft_in12k_in1k	X
8	cvt_cvt-w24-384-in22k_finetuned-in1k_4	X
9	vit_large_patch14_clip_224:openai_ft_in1k	X
10	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	X
11	convnext_large:fb_in22k_ft_in1k	X
12	AdvProp_efficientnet-b7	X
13	convnext_xlarge:fb_in22k_ft_in1k	X
14	vit_large_patch14_clip_336:laion2b_ft_in1k	X
15	AdvProp_efficientnet-b4	X
16	AT_efficientnet-b4	X
17	vit_large_patch14_clip_224:laion2b_ft_in1k	X
18	vit_base_patch16_clip_224:openai_ft_in12k_in1k	X
19	deit_large_imagenet_full_seed-0	X
20	deit_base_imagenet_full_seed-0	X
21	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	X
22	effnetv2m_custom384	X
23	resnext101_32x48d_wsl	X
24	convnext_large_imagenet_full_seed-0	X
25	vit_relpos_base_patch16_clsgap_224:sw_in1k	X
26	resnext101_32x32d_wsl	X
27	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	X
28	convnext_tiny_sup	X
29	AlexNet_SIN	X
30	swin_small_patch4_window7_224:ms_in22k_ft_in1k	X
31	ViT_L_32_imagenet1k	X
32	AdvProp_efficientnet-b8	X
33	convnext_tiny:in12k_ft_in1k	X
34	focalnet_tiny_lrf_in1k	X
35	resnet50-SIN_IN	X
36	resnet-152_v1-tf	X
37	ViT_B_16_imagenet1k	X
38	resnet-152_v2-tf	X
39	grcnn_109	X
40	convnext_base_imagenet_full_seed-0	X
41	AdvProp_efficientnet-b0	X
42	resnet_101_v1	X
43	resnext101_32x8d_wsl	X
44	resnet-101_v2-tf	X
45	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	X
46	efficientnet-b7	X
47	resnet_SIN_IN_FT_IN	X
48	resnet50-SIN_IN_IN	X
49	vit_base_patch16_clip_224:openai_ft_in1k	X
50	ViT_B_32_imagenet1k	X
51	antialias-resnet152	X
52	resnet_152_v1	X
53	resnext101_32x16d_wsl	X
54	deit_small_imagenet_full_seed-0	X
55	resnet-50-pytorch	X
56	resnet_50_v1	X
57	resnet50_tutorial	X
58	resnet50-sup	X
59	AT_efficientnet-b2	X
60	AdvProp_efficientnet-b2	X
61	convnext_tiny_imagenet_full_seed-0	X
62	resnet-101_v1-tf	X
63	convnext_small_imagenet_full_seed-0	X
64	shufflenet_v2_x1_0	X
65	BiT-S-R152x2	X
66	resnet-50_v2-tf	X
67	voneresnet-50-robust	X
68	densenet-201-keras	X
69	resnet50_robust_l2_eps1	X
70	blt_vs	X
71	densenet_201_pytorch	X
72	densenet-201	X
73	convnext_base:clip_laiona_augreg_ft_in1k_384	X
74	vonegrcnn_47e	X
75	vonegrcnn_62e_nobn	X
76	resnet-152_v2_pytorch	X
77	efficientnet_b0	X
78	vonegrcnn_62e_nobn	X
79	densenet-169-keras	X
80	densenet-169	X
81	inception_v2-tf	X
82	fixres_resnext101_32x48d_wsl	X
83	BiT-S-R101x1	X
84	nasnet_large-tf	X
85	cvt_cvt-13-384-in1k_4_LucyV4	X
86	vonegrcnn_52e_full	X
87	cvt_cvt-13-224-in1k_4_LucyV4	X
88	voneresnet-50	X
89	antialiased-r50	X
90	vonegrcnn_47e	X
91	inception_v4-tf	X
92	BiT-S-R101x3	X
93	grcnn	X
94	resnet50-vitoimagevidnet8	X
95	resnet152_imagenet_full	X
96	antialiased-rnext101_32x8d	X
97	effnetb1_272x240	X
98	cv_18_dagger_408_pretrained	X
99	imagenet_l2_3_0	X
100	resnet50_robust_l2_eps3	X
101	inception_v3-tf	X
102	CORnet-S	X
103	resnet-50-robust	X
104	resnet-18	X
105	resnet-50_v1-tf	X
106	cvt_cvt-21-384-in1k_4_LucyV4	X
107	vonegrcnn_52e_full	X
108	Res2Net50_26w_4s	X
109	efficientnet_b2_imagenet_full	X
110	xception-keras	X
111	resnet50-moclr8deg	X
112	cvt_cvt-21-224-in1k_4_LucyV4	X
113	inception_v1-tf	X
114	inception_v3_pytorch	X
115	mobilenet_v2_0.75_160-tf	X
116	inception_v4	X
117	resnet50	X
118	pnasnet_large-tf	X
119	mobilenet_v2_0.5_128	X
120	mobilenet_v2_1.4_224-tf	X
121	resnet_101_v2	X
122	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	X
123	resnet101_imagenet_full	X
124	mobilenet_v2_1.3_224-tf	X
125	mobilenet_v2_1.0_96	X
126	nasnet_large	X
127	mobilenet_v2_1.0_224-tf	X
128	resnet50_moco_v2	X
129	mobilenet_v2_1.0_160-tf	X
130	imagenet_l2_10_0	X
131	BiT-S-R50x3	X
132	resnet-34	X
133	BiT-S-R50x1	X
134	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	X
135	regnet_y_400mf	X
136	resnet50-VITO-8deg-cc	X
137	mobilenet_v2_1.0_128-tf	X
138	resnet50_l2_3_robust	X
139	mobilenet_v2_1.0_192-tf	X
140	resnet_50_v2	X
141	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	X
142	voneresnet-50-non_stochastic	X
143	convnext_femto_ols:d1_in1k	X
144	resnet_152_v2	X
145	densenet-121	X
146	densenet-121-keras	X
147	pnasnet_large	X
148	resnet34_imagenet_full	X
149	mobilenet_v1_0.75_128	X
150	mobilenet_v2_0.5_192-tf	X
151	BiT-S-R152x4	X
152	mobilenet_v2_0.75_192-tf	X
153	mobilenet_v2_0.75_96	X
154	resnet50_imagenet_full	X
155	mobilenet_v1_0.75_160	X
156	mobilenet_v2_0.35_128	X
157	mobilenet_v1_1.0_128	X
158	inception_v3	X
159	vgg-19-keras	X
160	efficientnet_b1_imagenet_full	X
161	mobilenet_v1_1.0_224	X
162	mobilenet_v1_0.75_192	X
163	nasnet_mobile	X
164	mobilenet_v2_0.75_128	X
165	mobilenet_v1_0.5_160	X
166	mobilenet_v2_1_0_160	X
167	vgg-16-keras	X
168	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	X
169	mobilenet_v2_0.35_160	X
170	mobilenet_v2_0.5_96	X
171	mobilenet_v2_0.75_224-tf	X
172	xception	X
173	mobilenet_v1_0.5_128	X
174	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	X
175	mobilenet_v1_1.0_160	X
176	mobilenet_v2_0_75_160	X
177	mobilenet_v2_1_3_224	X
178	mobilenet_v2_1_0_224	X
179	mobilenet_v2_0.35_192	X
180	mobilenet_v1_0.5_192	X
181	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	X
182	mobilenet_v2_0.5_160	X
183	efficientnet_b0_imagenet_full	X
184	mobilenet_v2_0.5_224-tf	X
185	inception_v1	X
186	ReAlnet06	X
187	resnet50_linf_8_robust	X
188	ReAlnet08	X
189	mobilenet_v2_0.35_96	X
190	mobilenet_v1_0.5_224	X
191	ReAlnet10	X
192	ReAlnet07	X
193	mobilenet_v1_0.75_224	X
194	mobilenet_v1_1.0_192	X
195	ReAlnet05	X
196	mobilenet_v2_0_5_192	X
197	mobilenet_v1_0.25_224	X
198	ReAlnet01	X
199	ReAlnet_incorrect	X
200	mobilenet_v2_1_0_192	X
201	0.5x_resnet-18_LC_w_sh_1_iter	X
202	mobilenet_v2_0_75_192	X
203	ReAlnet03	X
204	mobilenet_v2_1_0_128	X
205	mobilenet_v2_1_4_224	X
206	mobilenet_v2_1-4_224_pytorch	X
207	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	X
208	ReAlnet04	X
209	alexnet_robust_correct	X
210	custom_model_cv_18_dagger_408	X
211	resnet18_imagenet_full	X
212	alexnet	X
213	alexnet	X
214	alexnet	X
215	alexnet_ks_torevert	X
216	alexnet	X
217	alexnet	X
218	alexnet	X
219	alexnet	X
220	alexnet-baseline	X
221	convnext_small_imagenet_100_seed-0	X
222	CLIP-RN50	X
223	vgg_16	X
224	ReAlnet09	X
225	ReAlnet02	X
226	alexnet_l2_3_robust	X
227	mobilenet_v2_0_5_224	X
228	nasnet_mobile-tf	X
229	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	X
230	mobilenet_v1_0.25_192	X
231	pnasnet_large_pytorch	X
232	mobilenet_v2_0_75_224	X
233	squeezenet1_1	X
234	alexnet_random_linf8_perturb	X
235	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	X
236	vgg_19	X
237	alexnet	X
238	alexnet_linf_8_robust	X
239	alexnet_early_checkpoint	X
240	mobilenet_v2_0.35_224	X
241	mobilenet_v1_0.25_128	X
242	mobilenet_v1_0.25_160	X
243	squeezenet1_0	X
244	deit_small_imagenet_100_seed-0	X
245	resnet50_imagenet_100_seed-0	X
246	resnet50_imagenet_10_seed-0	X
247	deit_small_imagenet_10_seed-0	X
248	convnext_small_imagenet_10_seed-0	X
249	deit_small_imagenet_1_seed-0	X
250	resnet50-simclr-vissl	X
251	resnet50-vicregl0p9	X
252	artResNet18_1	X
253	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	X
254	resnet50_imagenet_1_seed-0	X
255	alexnet_training_seed_08	X
256	resnet50-barlow	X
257	alexnet_training_seed_06	X
258	alexnet_training_seed_09	X
259	alexnet_training_seed_02	X
260	alexnet_training_seed_05	X
261	alexnet_training_seed_10	X
262	resnet50-meshes-lt-100-original-scratch	X
263	resnet-50_untrained	X
264	alexnet_training_seed_01	X
265	alexnet_training_seed_03	X
266	alexnet_training_seed_04	X
267	convnext_small_imagenet_1_seed-0	X
268	resnet50-meshes-lt-100-original-pretrained	X
269	resnet50-vicregl0p75	X
270	barlow-twins-resnet50	X
271	alexnet_training_seed_07	X
272	mobilevit_small	X
273	omnivore_swinS	X
274	ReAlnet10_cornet	X
275	yudixie_resnet50_distance_translation_rotation_0_240908	X
276	yudixie_resnet50_imagenet1kpret_0_240908	X
277	yudixie_resnet50_random_0_240908	X
278	0.5x_resnet-18_LC_w_sh_10_iter	X
279	r3m_resnet18	X
280	my-model	X
281	yudixie_resnet50_cat_obj_class_all_latents_0_240908	X
282	yudixie_resnet50_object_class_0_240908	X
283	resnet18-instance_recognition	X
284	vggface	X
285	CORnet-Z	X
286	resnet50	X
287	resnet18-deepcluster	X
288	openclip	X
289	omnivore_swinT	X
290	dorinet_cornet_z	X
291	pixels	X
292	vonealexnet_gaussian_noise_std4_fixed	X
293	CORnetZ_CIFAR10	X
294	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	X
295	v1-pyr-nodown	X
296	0.5x_resnet-18_LC	X
297	CORnetZ_CIFAR10_bs32_20_04	X
298	unet_entire	X
299	FrankRobWobv0	X
300	dcgan	X
301	resnet-50x2_untrained	X
302	resnet-18_untrained	X
303	yudixie_resnet50_imagenet1kpret_0_240312	X
304	resnet-18-LC_w_sh_10_iter_conv_init_m	X
305	resnet-18-LC_untrained	X
306	resnet18-contrastive_predictive	X
307	resnet-18-LC_w_sh_100_iter_m	X
308	BiT-M-R50x3	X
309	r3m_resnet34_nocrop	X
310	resnet18-local_aggregation	X
311	resnet-18-LC_w_sh_10_iter_m	X
312	ViT_B_16	X
313	yudixie_resnet50_category_class_0_240908	X
314	resnet18-depth_prediction	X
315	ViT_B_32	X
316	ViT_L_32	X
317	resnet18-simclr	X
318	resnet-18-LC_w_sh_1_iter_m	X
319	yudixie_resnet50_distance_reg_0_240908	X
320	resnet18-autoencoder	X
321	resnet18-relative_position	X
322	resnet18_imagenet21kP	X
323	ConvLSTM	X
324	PredRNN	X
325	SimVP	X
326	TAU	X
327	MIM	X
328	hmax	X
329	resnet18-colorization	X
330	ReAlnet01_cornet	X
331	BiT-M-R152x2	X
332	RN50	X
333	resnet-18-LC_w_sh_1_iter_conv_init_m	X
334	0.5x_resnet-18_LC_w_sh_100_iter	X
335	yudixie_resnet18_distance_translation_0_240719	X
336	RN50	X
337	0.5x_resnet-18	X
338	yudixie_resnet18_translation_reg_0_240719	X
339	BiT-M-R50x1	X
340	yudixie_resnet18_distance_reg_0_240719	X
341	yudixie_resnet18_rotation_reg_0_240719	X
342	ReAlnet03_cornet	X
343	yudixie_resnet18_imagenet1kpret_0_240719	X
344	resnet18-contrastive_multiview	X
345	yudixie_resnet50_rotation_reg_0_240908	X
346	yudixie_resnet50_distance_rotation_0_240908	X
347	resnet-18-LC_conv_init_m	X
348	resnet-18-LC_w_sh_100_iter_conv_init_m	X
349	yudixie_resnet50_distance_translation_0_240908	X
350	resnet-18-LC_1st_conv_m	X
351	r3m_resnet50_nocrop	X
352	resnet18_ecoset_full	X
353	ReAlnet02_cornet	X
354	ReAlnet04_cornet	X
355	resnet34_ecoset_full	X
356	resnet50_ecoset_full	X
357	resnet101_ecoset_full	X
358	resnet152_ecoset_full	X
359	yudixie_resnet18_translation_rotation_0_240719	X
360	yudixie_resnet18_distance_rotation_0_240719	X
361	resnet-18_test_m	X
362	ReAlnet05_cornet	X
363	yudixie_resnet18_category_class_0_240719	X
364	yudixie_resnet50_translation_reg_0_240908	X
365	resnet18-supervised	X
366	yudixie_resnet18_random_0_240719	X
367	resnet-18-LC_m	X
368	yudixie_resnet18_cat_obj_class_all_latents_0_240719	X
369	yudixie_resnet18_distance_translation_rotation_0_240719	X
370	yudixie_resnet18_object_class_0_240719	X
371	ReAlnet06_cornet	X
372	r3m_resnet34	X
373	yudixie_resnet50_translation_rotation_0_240908	X
374	ReAlnet07_cornet	X
375	ReAlnet08_cornet	X
376	omnivore_swinB	X
377	resnet50-vicreg	X
378	VOneCORnet-S	X
379	ReAlnet09_cornet	X
380	ViT-B/32	X
381	r3m_resnet50	X

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: Geirhos2021eidolonII

Metric: top1