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("Geirhos2021cueconflict-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	.577
2	AdvProp_efficientnet-b8	.544
3	imagenet_l2_10_0	.532
4	AdvProp_efficientnet-b6	.525
5	resnet50-SIN	.524
6	AdvProp_efficientnet-b7	.522
7	resnet50_linf_8_robust	.505
8	AlexNet_SIN	.484
9	AlexNet_SIN_fov4	.484
10	AlexNet_SIN_fov12	.484
11	AlexNet_SIN_fov16	.484
12	resnet50_l2_3_robust	.467
13	resnet-50-robust	.459
14	imagenet_l2_3_0	.459
15	resnet50_robust_l2_eps3	.459
16	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.448
17	AdvProp_efficientnet-b4	.444
18	AT_efficientnet-b4	.444
19	alexnet_linf_8_robust	.425
20	voneresnet-50-robust	.418
21	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.415
22	alexnet_l2_3_robust	.399
23	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.395
24	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.386
25	efficientnet-b7	.383
26	alexnet_robust_correct	.377
27	vit_large_patch14_clip_224:openai_ft_in1k	.377
28	convnext_xlarge:fb_in22k_ft_in1k	.371
29	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.362
30	vit_large_patch14_clip_224:laion2b_ft_in1k	.355
31	deit3_base_patch16_224_fb_in1k	.355
32	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.355
33	convnext_large:fb_in22k_ft_in1k	.348
34	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.339
35	vit_large_patch14_clip_336:laion2b_ft_in1k	.339
36	resnext101_32x48d_wsl	.334
37	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.334
38	resnet50_robust_l2_eps1	.332
39	deit3_base_patch16_224_fb_in22k_ft_in1k	.324
40	custom_model_cv_18_dagger_408	.323
41	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.313
42	resnext101_32x16d_wsl	.308
43	vit_relpos_base_patch16_clsgap_224:sw_in1k	.307
44	convnext_base_fb_in22k_ft_in1k	.305
45	ViT_L_32_imagenet1k	.303
46	convnext_large_imagenet_full_seed-0	.303
47	mobilenet_v2_0.5_96	.302
48	deit_large_imagenet_full_seed-0	.302
49	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.300
50	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.300
51	resnext101_32x32d_wsl	.299
52	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.296
53	ViT_B_16_imagenet1k	.295
54	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.295
55	effnetv2m_custom384	.295
56	mobilenet_v2_0.35_96	.294
57	convnext_small_imagenet_full_seed-0	.294
58	convnext_base_imagenet_full_seed-0	.291
59	vit_base_patch16_clip_224:openai_ft_in1k	.289
60	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.282
61	convnext_base:clip_laiona_augreg_ft_in1k_384	.281
62	deit_base_imagenet_full_seed-0	.280
63	convnext_tiny_imagenet_full_seed-0	.280
64	AT_efficientnet-b2	.277
65	AdvProp_efficientnet-b2	.277
66	ViT_B_32_imagenet1k	.276
67	resnext101_32x8d_wsl	.275
68	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.275
69	fixres_resnext101_32x48d_wsl	.272
70	convnext_small_imagenet_100_seed-0	.267
71	mobilenet_v2_0.5_128	.265
72	blt_vs	.265
73	mobilenet_v2_0.35_128	.261
74	convnext_tiny:in12k_ft_in1k	.259
75	resnet50-SIN_IN	.258
76	resnet-152_v2-tf	.255
77	convnext_base_fb_in1k	.255
78	mobilenet_v2_0.75_96	.254
79	focalnet_tiny_lrf_in1k	.252
80	mobilenet_v2_1_0_128	.251
81	deit_small_imagenet_full_seed-0	.251
82	inception_v1	.249
83	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.247
84	resnet_101_v2	.246
85	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.245
86	AdvProp_efficientnet-b0	.243
87	resnet-101_v2-tf	.242
88	cv_18_dagger_408_pretrained	.242
89	voneresnet-50	.242
90	mobilenet_v2_0.5_160	.241
91	mobilenet_v2_0.75_128	.241
92	inception_v3	.241
93	mobilenet_v2_0.35_192	.240
94	mobilenet_v2_0.35_160	.237
95	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.235
96	resnet-50_v2-tf	.235
97	mobilenet_v1_0.25_128	.235
98	mobilenet_v2_1.0_96	.230
99	mobilenet_v2_0_5_192	.230
100	mobilenet_v2_0_75_160	.230
101	nasnet_large-tf	.228
102	vonegrcnn_47e	.228
103	inception_v3_pytorch	.228
104	resnet50_ewconplus_wzc_2_323	.228
105	inception_v4-tf	.227
106	effnetb1_272x240	.227
107	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.227
108	vonegrcnn_52e_full	.226
109	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.226
110	vonegrcnn_52e_full	.226
111	nasnet_large	.225
112	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.224
113	vonegrcnn_62e_nobn	.223
114	resnet50_st_wzc_seed4_2_323	.223
115	vonegrcnn_47e	.222
116	mobilenet_v2_1.0_192-tf	.221
117	nasnet_mobile	.221
118	resnet50_ewconplus_noseed_2_323	.221
119	resnet50_ewconplus_wzc_seed7_2_323	.221
120	mobilenet_v2_0.5_192-tf	.220
121	inception_v2-tf	.220
122	mobilenet_v2_0.75_160-tf	.220
123	inception_v3-tf	.220
124	mobilenet_v2_0_5_224	.220
125	mobilenet_v2_1.0_128-tf	.219
126	pnasnet_large_pytorch	.219
127	mobilenet_v2_1_0_192	.218
128	vonegrcnn_62e_nobn	.217
129	resnet50_ewconplus_wzc_seed4_2_323	.217
130	mobilenet_v2_1_0_160	.216
131	resnet50_st_wzc_noseed_2_323	.216
132	cvt_cvt-13-224-in1k_4_LucyV4	.216
133	inception_v1-tf	.215
134	mobilenet_v1_0.5_128	.215
135	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
136	mobilenet_v1_0.25_160	.214
137	mobilenet_v1_0.75_128	.214
138	alexnet_early_checkpoint	.214
139	resnet50_ewconplus_wzc	.214
140	mobilenet_v2_0.75_192-tf	.212
141	densenet-201-keras	.212
142	inception_v4	.212
143	resnet50_st_wzc_seed6_2_323	.212
144	densenet-201	.212
145	resnet50_st_wzc_seed5_2_323	.212
146	densenet_201_pytorch	.212
147	resnet50_ewconplus_wzc_seed3_2_323	.212
148	resnet50-VITO-8deg-cc	.211
149	efficientnet_b0	.209
150	convnext_tiny_sup	.209
151	resnet50_st_wzc_2	.209
152	BiT-S-R152x2	.209
153	BiT-S-R50x1	.209
154	cvt_cvt-13-384-in1k_4_LucyV4	.209
155	resnet50_st_wzc_seed3_2_323	.208
156	resnet_152_v1	.207
157	densenet-169	.207
158	BiT-S-R101x1	.206
159	resnet50_st_wzc_2_323	.206
160	mobilenet_v2_0.5_224-tf	.205
161	densenet-169-keras	.205
162	mobilenet_v2_0_75_192	.205
163	resnet50-vitoimagevidnet8	.205
164	resnet_50_v2	.205
165	resnet50_st_wzc_seed7_2_323	.205
166	antialias-resnet152	.204
167	grcnn_109	.204
168	resnet50_moco_v2	.203
169	cvt_cvt-21-224-in1k_4_LucyV4	.202
170	resnet152_imagenet_full	.202
171	mobilenet_v2_1.0_160-tf	.202
172	alexnet_random_linf8_perturb	.202
173	mobilenet_v1_0.5_160	.201
174	convnext_femto_ols:d1_in1k	.201
175	antialiased-rnext101_32x8d	.200
176	resnet_152_v2	.200
177	mobilenet_v2_1_0_224	.199
178	resnet_101_v1	.199
179	voneresnet-50-non_stochastic	.198
180	resnet-101_v1-tf	.198
181	resnet34_imagenet_full	.198
182	efficientnet_b0_imagenet_full	.198
183	mobilenet_v2_0.35_224	.197
184	resnet-152_v1-tf	.197
185	BiT-S-R101x3	.196
186	mobilenet_v1_0.25_192	.196
187	pnasnet_large-tf	.195
188	mobilenet_v2_0_75_224	.195
189	pnasnet_large_halfPrecision	.195
190	xception	.195
191	pnasnet_large	.195
192	resnet50_ewconplus_wzc_seed5_2__323	.195
193	resnet-34	.193
194	BiT-S-R152x4	.192
195	resnet50	.192
196	tv_efficientnet-b1	.192
197	xception-keras	.191
198	resnet-18	.191
199	convnext_base_fb_in1k_gram_aligned_dinov3	.191
200	densenet-121-keras	.190
201	densenet-121	.190
202	alexnet	.189
203	mobilenet_v1_1.0_128	.189
204	alexnet_ks_torevert	.189
205	alexnet_fov4	.189
206	alexnet_fov12	.189
207	resnet101_imagenet_full	.189
208	alexnet_fov16	.189
209	grcnn	.186
210	resnet18_imagenet_full	.185
211	CLIP-RN50	.184
212	resnet-50-pytorch	.182
213	resnet50-sup	.182
214	mobilenet_v1_0.75_160	.182
215	shufflenet_v2_x1_0	.182
216	regnet_y_400mf	.182
217	resnet50_imagenet_full	.182
218	resnet50_tutorial	.182
219	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.182
220	resnet_50_v1	.182
221	mobilenet_v1_0.5_192	.181
222	BiT-S-R50x3	.180
223	mobilenet_v2_0.75_224-tf	.180
224	ReAlnet06	.180
225	resnet-50_v1-tf	.178
226	mobilenet_v1_0.25_224	.178
227	antialiased-r50	.178
228	mobilenet_v2_1.0_224-tf	.177
229	resnet_50_v1_spiking	.177
230	nasnet_mobile-tf	.177
231	CORnet-S	.177
232	Res2Net50_26w_4s	.177
233	ReAlnet02	.176
234	cvt_cvt-21-384-in1k_4_LucyV4	.175
235	efficientnet_b1_imagenet_full	.174
236	resnet_SIN_IN_FT_IN	.173
237	resnet50-SIN_IN_IN	.173
238	vgg-19-keras	.172
239	resnet50-moclr8deg	.172
240	ReAlnet04	.172
241	efficientnet_b2_imagenet_full	.171
242	resnet-152_v2_pytorch	.171
243	ReAlnet03	.171
244	ReAlnet05	.170
245	mobilenet_v1_1.0_160	.170
246	mobilenet_v1_1.0_192	.168
247	ReAlnet08	.167
248	ReAlnet10	.167
249	mobilenet_v2_1-4_224_pytorch	.166
250	mobilenet_v2_1_4_224	.166
251	mobilenet_v1_0.75_224	.166
252	ReAlnet07	.166
253	mobilenet_v2_1_3_224	.166
254	ReAlnet01	.166
255	squeezenet1_1	.165
256	ReAlnet09	.165
257	mobilenet_v2_1.4_224-tf	.162
258	mobilenet_v1_0.75_192	.162
259	0.5x_resnet-18_LC_w_sh_1_iter	.159
260	resnet50_eMMCR_Vanilla	.158
261	vgg-16-keras	.157
262	mobilenet_v2_1.3_224-tf	.156
263	deit_small_imagenet_100_seed-0	.156
264	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.155
265	resnet_50_v1_spiking_l4a	.154
266	mobilenet_v1_1.0_224	.148
267	resnet50_imagenet_100_seed-0	.148
268	vgg_19	.144
269	mobilenet_v1_0.5_224	.143
270	resnet_50_v1_spiking_l4	.137
271	squeezenet1_0	.135
272	vgg_16	.116
273	convnext_small_imagenet_10_seed-0	.114
274	deit_small_imagenet_10_seed-0	.088
275	alexnet_training_seed_07	.084
276	deit_small_imagenet_1_seed-0	.077
277	alexnet_training_seed_06	.076
278	convnext_small_imagenet_1_seed-0	.076
279	alexnet_training_seed_09	.074
280	resnet50_imagenet_10_seed-0	.074
281	resnet50_imagenet_1_seed-0	.073
282	resnet50-vicregl0p9	.070
283	resnet50-meshes-lt-100-original-pretrained	.065
284	resnet50-vicregl0p75	.064
285	resnet50-barlow	.063
286	resnet50-meshes-lt-100-original-scratch	.062
287	alexnet_training_seed_05	.062
288	alexnet_training_seed_02	.062
289	alexnet_training_seed_04	.062
290	alexnet_training_seed_08	.062
291	alexnet_training_seed_10	.062
292	alexnet_training_seed_01	.062
293	alexnet_training_seed_01_fov4	.062
294	alexnet_training_seed_01_fov12	.062
295	alexnet_training_seed_01_fov16	.062
296	alexnet_training_seed_03	.062
297	barlow-twins-resnet50	.060
298	resnet-50_untrained	.060
299	resnet50-simclr-vissl	.059
300	resnet_50_v1_spiking_l3	.055
301	artResNet18_1	.053
302	ViT-B/32
303	resnet-18-LC_w_sh_100_iter_conv_init_m
304	BiT-M-R50x1
305	resnet-18-LC_w_sh_1_iter_conv_init_m
306	BiT-M-R152x2
307	resnet-18-LC_w_sh_1_iter_m
308	resnet-18-LC_w_sh_10_iter_m
309	BiT-M-R50x3
310	resnet-18-LC_w_sh_100_iter_m
311	resnet-18-LC_w_sh_10_iter_conv_init_m
312	FrankRobWobv0
313	0.5x_resnet-18_LC
314	CORnetZ_CIFAR10
315	resnet18-local_aggregation
316	r3m_resnet18
317	resnet18-deepcluster
318	CORnet-Z
319	vggface
320	my-model
321	resnet18-instance_recognition
322	0.5x_resnet-18_LC_w_sh_10_iter
323	r3m_resnet50
324	r3m_resnet34
325	resnet-18-LC_m
326	resnet18-supervised
327	r3m_resnet50_nocrop
328	resnet-18-LC_1st_conv_m
329	resnet-18-LC_conv_init_m
330	resnet18-contrastive_multiview
331	0.5x_resnet-18
332	RN50
333	0.5x_resnet-18_LC_w_sh_100_iter
334	RN50
335	resnet18-colorization
336	resnet18-relative_position
337	resnet18-autoencoder
338	resnet18-simclr
339	ViT_L_32
340	ViT_B_32
341	resnet18-depth_prediction
342	ViT_B_16
343	r3m_resnet34_nocrop
344	resnet18-contrastive_predictive
345	resnet-18-LC_untrained
346	resnet-18_untrained
347	resnet-50x2_untrained
348	dcgan
349	unet_entire
350	CORnetZ_CIFAR10_bs32_20_04
351	v1-pyr-nodown
352	pixels
353	dorinet_cornet_z
354	omnivore_swinT
355	resnet50
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

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