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