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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Geirhos2021cueconflict-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	.591
2	convnext_xxlarge_clip	.581
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.577
4	dinov2_vitg14_lc	.558
5	dinov2_vitl14_reg_lc	.547
6	AdvProp_efficientnet-b8	.544
7	eva02_large_in22k	.543
8	imagenet_l2_10_0	.532
9	AdvProp_efficientnet-b6	.525
10	resnet50-SIN	.524
11	AdvProp_efficientnet-b7	.522
12	dinov2_vitl14_lc	.508
13	resnet50_linf_8_robust	.505
14	dinov2_vitl14_lc_res336	.500
15	AlexNet_SIN	.484
16	AlexNet_SIN_fov4	.484
17	AlexNet_SIN_fov12	.484
18	AlexNet_SIN_fov16	.484
19	resnet50_l2_3_robust	.467
20	resnet-50-robust	.459
21	imagenet_l2_3_0	.459
22	resnet50_robust_l2_eps3	.459
23	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.448
24	AdvProp_efficientnet-b4	.444
25	AT_efficientnet-b4	.444
26	alexnet_linf_8_robust	.425
27	voneresnet-50-robust	.418
28	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.415
29	vit_huge_clip336_laion	.405
30	alexnet_l2_3_robust	.399
31	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.395
32	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.386
33	efficientnet-b7	.383
34	vit_large_clip336_openai	.379
35	alexnet_robust_correct	.377
36	vit_large_patch14_clip_224:openai_ft_in1k	.377
37	convnext_xlarge:fb_in22k_ft_in1k	.371
38	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.362
39	vit_large_patch14_clip_224:laion2b_ft_in1k	.355
40	deit3_base_patch16_224_fb_in1k	.355
41	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.355
42	convnext_large:fb_in22k_ft_in1k	.348
43	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.339
44	vit_large_patch14_clip_336:laion2b_ft_in1k	.339
45	convnext_large_in22k_supervised	.338
46	resnext101_32x48d_wsl	.334
47	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.334
48	resnet50_robust_l2_eps1	.332
49	deit3_base_patch16_224_fb_in22k_ft_in1k	.324
50	custom_model_cv_18_dagger_408	.323
51	convnext_large_clip_laion2b_finelayers	.320
52	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.313
53	resnext101_32x16d_wsl	.308
54	vit_relpos_base_patch16_clsgap_224:sw_in1k	.307
55	convnext_base_fb_in22k_ft_in1k	.305
56	ViT_L_32_imagenet1k	.303
57	convnext_large_imagenet_full_seed-0	.303
58	mobilenet_v2_0.5_96	.302
59	deit_large_imagenet_full_seed-0	.302
60	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.300
61	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.300
62	resnext101_32x32d_wsl	.299
63	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.296
64	ViT_B_16_imagenet1k	.295
65	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.295
66	effnetv2m_custom384	.295
67	mobilenet_v2_0.35_96	.294
68	convnext_small_imagenet_full_seed-0	.294
69	convnext_base_imagenet_full_seed-0	.291
70	vit_base_patch16_clip_224:openai_ft_in1k	.289
71	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.282
72	convnext_base:clip_laiona_augreg_ft_in1k_384	.281
73	deit_base_imagenet_full_seed-0	.280
74	convnext_tiny_imagenet_full_seed-0	.280
75	AT_efficientnet-b2	.277
76	AdvProp_efficientnet-b2	.277
77	ViT_B_32_imagenet1k	.276
78	resnext101_32x8d_wsl	.275
79	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.275
80	fixres_resnext101_32x48d_wsl	.272
81	convnext_small_imagenet_100_seed-0	.267
82	mobilenet_v2_0.5_128	.265
83	blt_vs	.265
84	mobilenet_v2_0.35_128	.261
85	convnext_tiny:in12k_ft_in1k	.259
86	resnet50-SIN_IN	.258
87	resnet-152_v2-tf	.255
88	convnext_base_fb_in1k	.255
89	mobilenet_v2_0.75_96	.254
90	focalnet_tiny_lrf_in1k	.252
91	mobilenet_v2_1_0_128	.251
92	deit_small_imagenet_full_seed-0	.251
93	inception_v1	.249
94	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.247
95	resnet_101_v2	.246
96	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.245
97	AdvProp_efficientnet-b0	.243
98	resnet-101_v2-tf	.242
99	cv_18_dagger_408_pretrained	.242
100	voneresnet-50	.242
101	mobilenet_v2_0.5_160	.241
102	mobilenet_v2_0.75_128	.241
103	inception_v3	.241
104	mobilenet_v2_0.35_192	.240
105	mobilenet_v2_0.35_160	.237
106	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.235
107	resnet-50_v2-tf	.235
108	mobilenet_v1_0.25_128	.235
109	mobilenet_v2_1.0_96	.230
110	mobilenet_v2_0_5_192	.230
111	mobilenet_v2_0_75_160	.230
112	nasnet_large-tf	.228
113	vonegrcnn_47e	.228
114	inception_v3_pytorch	.228
115	inception_v4-tf	.227
116	effnetb1_272x240	.227
117	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.227
118	vonegrcnn_52e_full	.226
119	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.226
120	vonegrcnn_52e_full	.226
121	nasnet_large	.225
122	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.224
123	vonegrcnn_62e_nobn	.223
124	vonegrcnn_47e	.222
125	mobilenet_v2_1.0_192-tf	.221
126	nasnet_mobile	.221
127	mobilenet_v2_0.5_192-tf	.220
128	inception_v2-tf	.220
129	mobilenet_v2_0.75_160-tf	.220
130	inception_v3-tf	.220
131	mobilenet_v2_0_5_224	.220
132	mobilenet_v2_1.0_128-tf	.219
133	pnasnet_large_pytorch	.219
134	mobilenet_v2_1_0_192	.218
135	vonegrcnn_62e_nobn	.217
136	mobilenet_v2_1_0_160	.216
137	cvt_cvt-13-224-in1k_4_LucyV4	.216
138	inception_v1-tf	.215
139	mobilenet_v1_0.5_128	.215
140	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
141	mobilenet_v1_0.25_160	.214
142	mobilenet_v1_0.75_128	.214
143	alexnet_early_checkpoint	.214
144	resnet50_ewconplus_wzc	.214
145	mobilenet_v2_0.75_192-tf	.212
146	densenet-201-keras	.212
147	inception_v4	.212
148	resnet50_st_wzc_seed6_2_323	.212
149	densenet-201	.212
150	densenet_201_pytorch	.212
151	resnet50-VITO-8deg-cc	.211
152	efficientnet_b0	.209
153	convnext_tiny_sup	.209
154	resnet50_st_wzc_2	.209
155	BiT-S-R152x2	.209
156	BiT-S-R50x1	.209
157	cvt_cvt-13-384-in1k_4_LucyV4	.209
158	resnet50_st_wzc_seed3_2_323	.208
159	resnet_152_v1	.207
160	densenet-169	.207
161	BiT-S-R101x1	.206
162	mobilenet_v2_0.5_224-tf	.205
163	densenet-169-keras	.205
164	mobilenet_v2_0_75_192	.205
165	resnet50-vitoimagevidnet8	.205
166	resnet_50_v2	.205
167	resnet50_st_wzc_seed7_2_323	.205
168	antialias-resnet152	.204
169	grcnn_109	.204
170	resnet50_moco_v2	.203
171	cvt_cvt-21-224-in1k_4_LucyV4	.202
172	resnet152_imagenet_full	.202
173	mobilenet_v2_1.0_160-tf	.202
174	alexnet_random_linf8_perturb	.202
175	mobilenet_v1_0.5_160	.201
176	convnext_femto_ols:d1_in1k	.201
177	antialiased-rnext101_32x8d	.200
178	resnet_152_v2	.200
179	resnet50_hvs_wzc	.200
180	mobilenet_v2_1_0_224	.199
181	resnet_101_v1	.199
182	voneresnet-50-non_stochastic	.198
183	resnet-101_v1-tf	.198
184	resnet34_imagenet_full	.198
185	efficientnet_b0_imagenet_full	.198
186	mobilenet_v2_0.35_224	.197
187	resnet-152_v1-tf	.197
188	BiT-S-R101x3	.196
189	mobilenet_v1_0.25_192	.196
190	pnasnet_large-tf	.195
191	mobilenet_v2_0_75_224	.195
192	pnasnet_large_halfPrecision	.195
193	xception	.195
194	pnasnet_large	.195
195	resnet50_ewconplus_wzc_seed5_2__323	.195
196	resnet-34	.193
197	BiT-S-R152x4	.192
198	resnet50	.192
199	tv_efficientnet-b1	.192
200	xception-keras	.191
201	resnet-18	.191
202	convnext_base_fb_in1k_gram_aligned_dinov3	.191
203	densenet-121-keras	.190
204	densenet-121	.190
205	alexnet	.189
206	mobilenet_v1_1.0_128	.189
207	alexnet_ks_torevert	.189
208	alexnet_fov4	.189
209	alexnet_fov12	.189
210	resnet101_imagenet_full	.189
211	alexnet_fov16	.189
212	grcnn	.186
213	resnet18_imagenet_full	.185
214	CLIP-RN50	.184
215	resnet-50-pytorch	.182
216	resnet50-sup	.182
217	mobilenet_v1_0.75_160	.182
218	shufflenet_v2_x1_0	.182
219	regnet_y_400mf	.182
220	resnet50_imagenet_full	.182
221	resnet50_tutorial	.182
222	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.182
223	resnet_50_v1	.182
224	mobilenet_v1_0.5_192	.181
225	BiT-S-R50x3	.180
226	mobilenet_v2_0.75_224-tf	.180
227	ReAlnet06	.180
228	resnet-50_v1-tf	.178
229	mobilenet_v1_0.25_224	.178
230	antialiased-r50	.178
231	mobilenet_v2_1.0_224-tf	.177
232	resnet_50_v1_spiking	.177
233	nasnet_mobile-tf	.177
234	CORnet-S	.177
235	Res2Net50_26w_4s	.177
236	ReAlnet02	.176
237	cvt_cvt-21-384-in1k_4_LucyV4	.175
238	efficientnet_b1_imagenet_full	.174
239	resnet_SIN_IN_FT_IN	.173
240	resnet50-SIN_IN_IN	.173
241	vgg-19-keras	.172
242	resnet50-moclr8deg	.172
243	ReAlnet04	.172
244	efficientnet_b2_imagenet_full	.171
245	resnet-152_v2_pytorch	.171
246	ReAlnet03	.171
247	ReAlnet05	.170
248	mobilenet_v1_1.0_160	.170
249	mobilenet_v1_1.0_192	.168
250	ReAlnet08	.167
251	ReAlnet10	.167
252	mobilenet_v2_1-4_224_pytorch	.166
253	mobilenet_v2_1_4_224	.166
254	mobilenet_v1_0.75_224	.166
255	ReAlnet07	.166
256	mobilenet_v2_1_3_224	.166
257	ReAlnet01	.166
258	squeezenet1_1	.165
259	ReAlnet09	.165
260	mobilenet_v2_1.4_224-tf	.162
261	mobilenet_v1_0.75_192	.162
262	0.5x_resnet-18_LC_w_sh_1_iter	.159
263	resnet50_eMMCR_Vanilla	.158
264	vgg-16-keras	.157
265	mobilenet_v2_1.3_224-tf	.156
266	deit_small_imagenet_100_seed-0	.156
267	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.155
268	resnet_50_v1_spiking_l4a	.154
269	mobilenet_v1_1.0_224	.148
270	resnet50_imagenet_100_seed-0	.148
271	vgg_19	.144
272	mobilenet_v1_0.5_224	.143
273	resnet_50_v1_spiking_l4	.137
274	squeezenet1_0	.135
275	vgg_16	.116
276	convnext_small_imagenet_10_seed-0	.114
277	deit_small_imagenet_10_seed-0	.088
278	alexnet_training_seed_07	.084
279	deit_small_imagenet_1_seed-0	.077
280	alexnet_training_seed_06	.076
281	convnext_small_imagenet_1_seed-0	.076
282	alexnet_training_seed_09	.074
283	resnet50_imagenet_10_seed-0	.074
284	resnet50_imagenet_1_seed-0	.073
285	resnet50-vicregl0p9	.070
286	resnet50-vicregl0p75	.064
287	resnet50-barlow	.063
288	alexnet_training_seed_05	.062
289	alexnet_training_seed_02	.062
290	alexnet_training_seed_04	.062
291	alexnet_training_seed_08	.062
292	alexnet_training_seed_10	.062
293	alexnet_training_seed_01	.062
294	alexnet_training_seed_01_fov4	.062
295	alexnet_training_seed_01_fov12	.062
296	alexnet_training_seed_01_fov16	.062
297	alexnet_training_seed_03	.062
298	barlow-twins-resnet50	.060
299	resnet-50_untrained	.060
300	resnet50-simclr-vissl	.059
301	resnet_50_v1_spiking_l3	.055
302	artResNet18_1	.053
303	ViT-B/32
304	resnet-18-LC_w_sh_100_iter_conv_init_m
305	BiT-M-R50x1
306	resnet-18-LC_w_sh_1_iter_conv_init_m
307	BiT-M-R152x2
308	resnet-18-LC_w_sh_1_iter_m
309	resnet-18-LC_w_sh_10_iter_m
310	BiT-M-R50x3
311	resnet-18-LC_w_sh_100_iter_m
312	resnet-18-LC_w_sh_10_iter_conv_init_m
313	FrankRobWobv0
314	0.5x_resnet-18_LC
315	CORnetZ_CIFAR10
316	resnet18-local_aggregation
317	r3m_resnet18
318	resnet18-deepcluster
319	CORnet-Z
320	vggface
321	my-model
322	resnet18-instance_recognition
323	0.5x_resnet-18_LC_w_sh_10_iter
324	r3m_resnet50
325	r3m_resnet34
326	resnet-18-LC_m
327	resnet18-supervised
328	r3m_resnet50_nocrop
329	resnet-18-LC_1st_conv_m
330	resnet-18-LC_conv_init_m
331	resnet18-contrastive_multiview
332	0.5x_resnet-18
333	RN50
334	0.5x_resnet-18_LC_w_sh_100_iter
335	RN50
336	resnet18-colorization
337	resnet18-relative_position
338	resnet18-autoencoder
339	resnet18-simclr
340	ViT_L_32
341	ViT_B_32
342	resnet18-depth_prediction
343	ViT_B_16
344	r3m_resnet34_nocrop
345	resnet18-contrastive_predictive
346	resnet-18-LC_untrained
347	resnet-18_untrained
348	resnet-50x2_untrained
349	dcgan
350	unet_entire
351	CORnetZ_CIFAR10_bs32_20_04
352	v1-pyr-nodown
353	pixels
354	dorinet_cornet_z
355	omnivore_swinT
356	openclip
357	vonealexnet_gaussian_noise_std4_fixed
358	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
359	yudixie_resnet50_imagenet1kpret_0_240312
360	yudixie_resnet50_category_class_0_240908
361	yudixie_resnet50_distance_reg_0_240908
362	resnet18_imagenet21kP
363	ConvLSTM
364	PredRNN
365	SimVP
366	briaai_rmbg_1_4
367	TAU
368	MIM
369	ReAlnet01_cornet
370	yudixie_resnet18_distance_translation_0_240719
371	compact_resnet50_V4
372	mobilevit_small
373	yudixie_resnet18_translation_reg_0_240719
374	yolos_tiny
375	yudixie_resnet18_distance_reg_0_240719
376	yudixie_resnet18_rotation_reg_0_240719
377	ReAlnet03_cornet
378	eBarlow_lmda_02_1000ep
379	vit_base_patch16_dinov3-lvd1689m
380	yudixie_resnet50_distance_translation_0_240908
381	yudixie_resnet50_distance_rotation_0_240908
382	compact_resnet50_IT
383	ReAlnet01_cornet_fov4
384	resnet18_ecoset_full
385	ReAlnet01_cornet_fov12
386	resnet34_ecoset_full
387	ReAlnet04_cornet
388	resnet50_ecoset_full
389	vit_base_patch14_reg4_dinov2-lvd142m
390	yudixie_resnet50_rotation_reg_0_240908
391	resnet101_ecoset_full
392	resnet152_ecoset_full
393	compact_vgg19_V4
394	yudixie_resnet18_translation_rotation_0_240719
395	yudixie_resnet50_translation_reg_0_240908
396	yudixie_resnet18_distance_rotation_0_240719
397	aughost_fair_resnet18
398	resnet-18_test_m
399	yudixie_resnet18_category_class_0_240719
400	yudixie_resnet18_random_0_240719
401	yudixie_resnet18_cat_obj_class_all_latents_0_240719
402	compact_vgg19_IT
403	SeLaVi-AVE
404	yudixie_resnet18_object_class_0_240719
405	compact_resnet50_robust_V4
406	yudixie_resnet18_imagenet1kpret_0_240719
407	hmax
408	ReAlnet06_cornet
409	r3d_18
410	yudixie_resnet50_translation_rotation_0_240908
411	ReAlnet07_cornet
412	ReAlnet01_ALL
413	mc3_18
414	ReAlnet02_ALL
415	s3d
416	ReAlnet08_cornet
417	resnet50_ewconplus_wzc_seed2_2__323
418	VOneCORnet-S
419	resnet50-vicreg
420	mvit_v1_b
421	omnivore_swinB
422	compact_cornets_V4
423	ReAlnet03_ALL
424	ReAlnet01_cornet_fov16
425	ReAlnet09_cornet
426	compact_cornets_IT
427	ReAlnet04_ALL
428	omnivore_swinS
429	SeLaVi-Kinetics400
430	ReAlnet05_ALL
431	SeLaVi-VGG-Sound
432	ReAlnet06_ALL
433	SeLaVi-Kinetics-Sound
434	ReAlnet10_cornet
435	compact_resnet50_robust_IT
436	mvit_v2_s
437	yudixie_resnet50_distance_translation_rotation_0_240908
438	ReAlnet07_ALL
439	r2plus1d_18
440	yudixie_resnet50_random_0_240908
441	yudixie_resnet50_imagenet1kpret_0_240908
442	ReAlnet08_ALL
443	yudixie_resnet50_cat_obj_class_all_latents_0_240908
444	yudixie_resnet50_object_class_0_240908
445	ReAlnet09_ALL
446	yudixie_resnet18_distance_translation_rotation_0_240719
447	resnet50_primary_visual_cortex
448	ReAlnet02_cornet
449	ReAlnet10_ALL
450	ReAlnet05_cornet
451	vit_base_patch14_dinov2-lvd142m
452	resnet18_fair
453	pr1_stl10_disentangled_alpha04
454	predictive_coding_pc
455	yudixie_wbh_object_class_scaling_0415_run_0
456	yudixie_wbh_object_class_scaling_0415_run_3
457	yudixie_wbh_object_class_scaling_0415_imagenet
458	yudixie_wbh_object_class_scaling_0415_run_2
459	yudixie_wbh_object_class_scaling_0415_run_1
460	deepeisnn_ei_cifar10_vgg19
461	deepeisnn_ei_cifar10_resnet18
462	deepeisnn_ei_imagenet_resnet18
463	dinov2_vitl14_reg_lc_featread

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: Geirhos2021cueconflict

Metric: top1