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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	mehrer2020_alexnet_training_seed_03	.262
85	mobilenet_v2_0.35_128	.261
86	convnext_tiny:in12k_ft_in1k	.259
87	resnet50-SIN_IN	.258
88	mehrer2020_alexnet_training_seed_01	.257
89	mehrer2020_alexnet_training_seed_01_fov12	.257
90	mehrer2020_alexnet_training_seed_01_fov16	.257
91	mehrer2020_alexnet_training_seed_01_fov4	.257
92	mehrer2020_alexnet_training_seed_05	.255
93	resnet-152_v2-tf	.255
94	convnext_base_fb_in1k	.255
95	mobilenet_v2_0.75_96	.254
96	mehrer2020_alexnet_training_seed_02	.252
97	focalnet_tiny_lrf_in1k	.252
98	mobilenet_v2_1_0_128	.251
99	deit_small_imagenet_full_seed-0	.251
100	inception_v1	.249
101	mehrer2020_alexnet_training_seed_04	.249
102	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.247
103	resnet_101_v2	.246
104	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.245
105	regnety_032	.245
106	AdvProp_efficientnet-b0	.243
107	resnet-101_v2-tf	.242
108	cv_18_dagger_408_pretrained	.242
109	voneresnet-50	.242
110	mobilenet_v2_0.5_160	.241
111	mobilenet_v2_0.75_128	.241
112	inception_v3	.241
113	mobilenet_v2_0.35_192	.240
114	ijepa_vith14_linhead	.237
115	mobilenet_v2_0.35_160	.237
116	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.235
117	resnet-50_v2-tf	.235
118	mobilenet_v1_0.25_128	.235
119	seresnext50_32x4d	.231
120	mobilenet_v2_1.0_96	.230
121	mobilenet_v2_0_5_192	.230
122	mobilenet_v2_0_75_160	.230
123	nasnet_large-tf	.228
124	vonegrcnn_47e	.228
125	inception_v3_pytorch	.228
126	inception_v4-tf	.227
127	effnetb1_272x240	.227
128	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.227
129	vonegrcnn_52e_full	.226
130	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.226
131	vonegrcnn_52e_full	.226
132	nasnet_large	.225
133	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.224
134	vonegrcnn_62e_nobn	.223
135	vonegrcnn_47e	.222
136	mobilenet_v2_1.0_192-tf	.221
137	nasnet_mobile	.221
138	mobilenet_v2_0.5_192-tf	.220
139	inception_v2-tf	.220
140	mobilenet_v2_0.75_160-tf	.220
141	inception_v3-tf	.220
142	mobilenet_v2_0_5_224	.220
143	mobilenet_v2_1.0_128-tf	.219
144	pnasnet_large_pytorch	.219
145	mobilenet_v2_1_0_192	.218
146	vonegrcnn_62e_nobn	.217
147	mobilenet_v2_1_0_160	.216
148	cvt_cvt-13-224-in1k_4_LucyV4	.216
149	inception_v1-tf	.215
150	mobilenet_v1_0.5_128	.215
151	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
152	mobilenet_v1_0.25_160	.214
153	mobilenet_v1_0.75_128	.214
154	alexnet_early_checkpoint	.214
155	resnet50_ewconplus_wzc	.214
156	mobilenet_v2_0.75_192-tf	.212
157	densenet-201-keras	.212
158	inception_v4	.212
159	resnet50_st_wzc_seed6_2_323	.212
160	densenet-201	.212
161	densenet_201_pytorch	.212
162	resnet50-VITO-8deg-cc	.211
163	efficientnet_b0	.209
164	convnext_tiny_sup	.209
165	resnet50_st_wzc_2	.209
166	BiT-S-R152x2	.209
167	BiT-S-R50x1	.209
168	cvt_cvt-13-384-in1k_4_LucyV4	.209
169	resnet50_st_wzc_seed3_2_323	.208
170	resnet_152_v1	.207
171	densenet-169	.207
172	BiT-S-R101x1	.206
173	mobilenet_v2_0.5_224-tf	.205
174	densenet-169-keras	.205
175	mobilenet_v2_0_75_192	.205
176	resnet50-vitoimagevidnet8	.205
177	resnet_50_v2	.205
178	resnet50_st_wzc_seed7_2_323	.205
179	antialias-resnet152	.204
180	grcnn_109	.204
181	resnet50_moco_v2	.203
182	cvt_cvt-21-224-in1k_4_LucyV4	.202
183	resnet152_imagenet_full	.202
184	eicircuit_resnet18_bn_20260919	.202
185	resnet50_barlowtwins_linhead	.202
186	mobilenet_v2_1.0_160-tf	.202
187	alexnet_random_linf8_perturb	.202
188	mobilenet_v1_0.5_160	.201
189	convnext_femto_ols:d1_in1k	.201
190	antialiased-rnext101_32x8d	.200
191	resnet_152_v2	.200
192	resnet50_hvs_wzc	.200
193	mobilenet_v2_1_0_224	.199
194	resnet_101_v1	.199
195	voneresnet-50-non_stochastic	.198
196	resnet-101_v1-tf	.198
197	resnet34_imagenet_full	.198
198	efficientnet_b0_imagenet_full	.198
199	mobilenet_v2_0.35_224	.197
200	resnet-152_v1-tf	.197
201	BiT-S-R101x3	.196
202	mobilenet_v1_0.25_192	.196
203	pnasnet_large-tf	.195
204	mobilenet_v2_0_75_224	.195
205	pnasnet_large_halfPrecision	.195
206	xception	.195
207	pnasnet_large	.195
208	resnet50_ewconplus_wzc_seed5_2__323	.195
209	resnet-34	.193
210	BiT-S-R152x4	.192
211	resnet50	.192
212	tv_efficientnet-b1	.192
213	xception-keras	.191
214	resnet50_simsiam_linhead	.191
215	resnet-18	.191
216	convnext_base_fb_in1k_gram_aligned_dinov3	.191
217	densenet-121-keras	.190
218	densenet-121	.190
219	alexnet	.189
220	mobilenet_v1_1.0_128	.189
221	alexnet_ks_torevert	.189
222	alexnet_fov4	.189
223	alexnet_fov12	.189
224	resnet101_imagenet_full	.189
225	alexnet_fov16	.189
226	grcnn	.186
227	resnet18_imagenet_full	.185
228	CLIP-RN50	.184
229	resnet50_byol_linhead	.184
230	resnet-50-pytorch	.182
231	resnet50-sup	.182
232	mobilenet_v1_0.75_160	.182
233	shufflenet_v2_x1_0	.182
234	regnet_y_400mf	.182
235	resnet50_imagenet_full	.182
236	resnet50_tutorial	.182
237	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.182
238	resnet_50_v1	.182
239	mobilenet_v1_0.5_192	.181
240	BiT-S-R50x3	.180
241	mobilenet_v2_0.75_224-tf	.180
242	ReAlnet06	.180
243	resnet-50_v1-tf	.178
244	mobilenet_v1_0.25_224	.178
245	antialiased-r50	.178
246	resnet50_vicreg_linhead	.178
247	mobilenet_v2_1.0_224-tf	.177
248	resnet_50_v1_spiking	.177
249	nasnet_mobile-tf	.177
250	CORnet-S	.177
251	Res2Net50_26w_4s	.177
252	ReAlnet02	.176
253	cvt_cvt-21-384-in1k_4_LucyV4	.175
254	efficientnet_b1_imagenet_full	.174
255	resnet_SIN_IN_FT_IN	.173
256	resnet50-SIN_IN_IN	.173
257	vgg-19-keras	.172
258	resnet50-moclr8deg	.172
259	ReAlnet04	.172
260	efficientnet_b2_imagenet_full	.171
261	resnet-152_v2_pytorch	.171
262	ReAlnet03	.171
263	ReAlnet05	.170
264	mobilenet_v1_1.0_160	.170
265	mobilenet_v1_1.0_192	.168
266	resnet50_simclr_linhead_01norm	.168
267	ReAlnet08	.167
268	ReAlnet10	.167
269	mobilenet_v2_1-4_224_pytorch	.166
270	mobilenet_v2_1_4_224	.166
271	mobilenet_v1_0.75_224	.166
272	ReAlnet07	.166
273	mobilenet_v2_1_3_224	.166
274	ReAlnet01	.166
275	squeezenet1_1	.165
276	ReAlnet09	.165
277	mobilenet_v2_1.4_224-tf	.162
278	mobilenet_v1_0.75_192	.162
279	0.5x_resnet-18_LC_w_sh_1_iter	.159
280	resnet50_eMMCR_Vanilla	.158
281	vgg-16-keras	.157
282	mobilenet_v2_1.3_224-tf	.156
283	deit_small_imagenet_100_seed-0	.156
284	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.155
285	resnet_50_v1_spiking_l4a	.154
286	mobilenet_v1_1.0_224	.148
287	resnet50_imagenet_100_seed-0	.148
288	vgg_19	.144
289	mobilenet_v1_0.5_224	.143
290	resnet_50_v1_spiking_l4	.137
291	squeezenet1_0	.135
292	vgg_16	.116
293	convnext_small_imagenet_10_seed-0	.114
294	deit_small_imagenet_10_seed-0	.088
295	alexnet_training_seed_07	.084
296	deit_small_imagenet_1_seed-0	.077
297	alexnet_training_seed_06	.076
298	convnext_small_imagenet_1_seed-0	.076
299	alexnet_training_seed_09	.074
300	resnet50_imagenet_10_seed-0	.074
301	resnet50_imagenet_1_seed-0	.073
302	resnet50-vicregl0p9	.070
303	resnet50-vicregl0p75	.064
304	resnet50-barlow	.063
305	alexnet_training_seed_05	.062
306	alexnet_training_seed_02	.062
307	alexnet_training_seed_04	.062
308	alexnet_training_seed_08	.062
309	alexnet_training_seed_10	.062
310	alexnet_training_seed_01	.062
311	alexnet_training_seed_01_fov4	.062
312	alexnet_training_seed_01_fov12	.062
313	alexnet_training_seed_01_fov16	.062
314	alexnet_training_seed_03	.062
315	barlow-twins-resnet50	.060
316	resnet-50_untrained	.060
317	resnet50-simclr-vissl	.059
318	resnet_50_v1_spiking_l3	.055
319	artResNet18_1	.053
320	ViT-B/32
321	resnet-18-LC_w_sh_100_iter_conv_init_m
322	BiT-M-R50x1
323	resnet-18-LC_w_sh_1_iter_conv_init_m
324	BiT-M-R152x2
325	resnet-18-LC_w_sh_1_iter_m
326	resnet-18-LC_w_sh_10_iter_m
327	BiT-M-R50x3
328	resnet-18-LC_w_sh_100_iter_m
329	resnet-18-LC_w_sh_10_iter_conv_init_m
330	FrankRobWobv0
331	0.5x_resnet-18_LC
332	CORnetZ_CIFAR10
333	resnet18-local_aggregation
334	r3m_resnet18
335	resnet18-deepcluster
336	CORnet-Z
337	vggface
338	my-model
339	resnet18-instance_recognition
340	0.5x_resnet-18_LC_w_sh_10_iter
341	r3m_resnet50
342	r3m_resnet34
343	resnet-18-LC_m
344	resnet18-supervised
345	r3m_resnet50_nocrop
346	resnet-18-LC_1st_conv_m
347	resnet-18-LC_conv_init_m
348	resnet18-contrastive_multiview
349	0.5x_resnet-18
350	RN50
351	0.5x_resnet-18_LC_w_sh_100_iter
352	RN50
353	resnet18-colorization
354	resnet18-relative_position
355	resnet18-autoencoder
356	resnet18-simclr
357	ViT_L_32
358	ViT_B_32
359	resnet18-depth_prediction
360	ViT_B_16
361	r3m_resnet34_nocrop
362	resnet18-contrastive_predictive
363	resnet-18-LC_untrained
364	resnet-18_untrained
365	resnet-50x2_untrained
366	dcgan
367	unet_entire
368	CORnetZ_CIFAR10_bs32_20_04
369	v1-pyr-nodown
370	pixels
371	dorinet_cornet_z
372	omnivore_swinT
373	openclip
374	vonealexnet_gaussian_noise_std4_fixed
375	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
376	yudixie_resnet50_imagenet1kpret_0_240312
377	yudixie_resnet50_category_class_0_240908
378	yudixie_resnet50_distance_reg_0_240908
379	resnet18_imagenet21kP
380	ConvLSTM
381	PredRNN
382	SimVP
383	briaai_rmbg_1_4
384	TAU
385	MIM
386	ReAlnet01_cornet
387	yudixie_resnet18_distance_translation_0_240719
388	compact_resnet50_V4
389	mobilevit_small
390	yudixie_resnet18_translation_reg_0_240719
391	yolos_tiny
392	yudixie_resnet18_distance_reg_0_240719
393	yudixie_resnet18_rotation_reg_0_240719
394	ReAlnet03_cornet
395	eBarlow_lmda_02_1000ep
396	vit_base_patch16_dinov3-lvd1689m
397	yudixie_resnet50_distance_translation_0_240908
398	yudixie_resnet50_distance_rotation_0_240908
399	compact_resnet50_IT
400	ReAlnet01_cornet_fov4
401	ReAlnet01_cornet_fov12
402	resnet34_ecoset_full
403	ReAlnet04_cornet
404	resnet50_ecoset_full
405	vit_base_patch14_reg4_dinov2-lvd142m
406	yudixie_resnet50_rotation_reg_0_240908
407	resnet101_ecoset_full
408	resnet152_ecoset_full
409	compact_vgg19_V4
410	yudixie_resnet18_translation_rotation_0_240719
411	yudixie_resnet50_translation_reg_0_240908
412	yudixie_resnet18_distance_rotation_0_240719
413	resnet-18_test_m
414	yudixie_resnet18_category_class_0_240719
415	yudixie_resnet18_random_0_240719
416	yudixie_resnet18_cat_obj_class_all_latents_0_240719
417	compact_vgg19_IT
418	SeLaVi-AVE
419	yudixie_resnet18_object_class_0_240719
420	compact_resnet50_robust_V4
421	yudixie_resnet18_imagenet1kpret_0_240719
422	hmax
423	ReAlnet06_cornet
424	r3d_18
425	yudixie_resnet50_translation_rotation_0_240908
426	ReAlnet07_cornet
427	ReAlnet01_ALL
428	mc3_18
429	ReAlnet02_ALL
430	s3d
431	ReAlnet08_cornet
432	resnet50_ewconplus_wzc_seed2_2__323
433	resnet50-vicreg
434	mvit_v1_b
435	omnivore_swinB
436	compact_cornets_V4
437	ReAlnet03_ALL
438	ReAlnet01_cornet_fov16
439	compact_cornets_IT
440	ReAlnet04_ALL
441	omnivore_swinS
442	SeLaVi-Kinetics400
443	ReAlnet05_ALL
444	SeLaVi-VGG-Sound
445	ReAlnet06_ALL
446	SeLaVi-Kinetics-Sound
447	ReAlnet10_cornet
448	compact_resnet50_robust_IT
449	mvit_v2_s
450	yudixie_resnet50_distance_translation_rotation_0_240908
451	ReAlnet07_ALL
452	r2plus1d_18
453	yudixie_resnet50_random_0_240908
454	yudixie_resnet50_imagenet1kpret_0_240908
455	ReAlnet08_ALL
456	yudixie_resnet50_cat_obj_class_all_latents_0_240908
457	yudixie_resnet50_object_class_0_240908
458	ReAlnet09_ALL
459	yudixie_resnet18_distance_translation_rotation_0_240719
460	resnet50_primary_visual_cortex
461	ReAlnet02_cornet
462	ReAlnet10_ALL
463	ReAlnet05_cornet
464	vit_base_patch14_dinov2-lvd142m
465	ReAlnet09_cornet
466	VOneCORnet-S
467	resnet18_ecoset_full
468	resnet18_fair
469	pr1_stl10_disentangled_alpha04
470	predictive_coding_pc
471	yudixie_wbh_object_class_scaling_0415_run_0
472	yudixie_wbh_object_class_scaling_0415_run_3
473	yudixie_wbh_object_class_scaling_0415_imagenet
474	yudixie_wbh_object_class_scaling_0415_run_2
475	yudixie_wbh_object_class_scaling_0415_run_1
476	deepeisnn_ei_cifar10_vgg19
477	deepeisnn_ei_cifar10_resnet18
478	deepeisnn_ei_imagenet_resnet18
479	dinov2_vitl14_reg_lc_featread
480	gabor_filter_entropy_4x4
481	gabor_filter_entropy_4x4_v2
482	gabor_filter_entropy_4x4_v2_forcedCosine
483	gabor_filter_mean_abs_4x4_v2

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