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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	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	resnet50_l2_3_robust	.467
10	resnet-50-robust	.459
11	imagenet_l2_3_0	.459
12	resnet50_robust_l2_eps3	.459
13	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.448
14	AdvProp_efficientnet-b4	.444
15	AT_efficientnet-b4	.444
16	alexnet_linf_8_robust	.425
17	voneresnet-50-robust	.418
18	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.415
19	alexnet_l2_3_robust	.399
20	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.395
21	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.386
22	efficientnet-b7	.383
23	alexnet_robust_correct	.377
24	vit_large_patch14_clip_224:openai_ft_in1k	.377
25	convnext_xlarge:fb_in22k_ft_in1k	.371
26	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.362
27	vit_large_patch14_clip_224:laion2b_ft_in1k	.355
28	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.355
29	convnext_large:fb_in22k_ft_in1k	.348
30	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.339
31	vit_large_patch14_clip_336:laion2b_ft_in1k	.339
32	resnext101_32x48d_wsl	.334
33	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.334
34	resnet50_robust_l2_eps1	.332
35	custom_model_cv_18_dagger_408	.323
36	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.313
37	resnext101_32x16d_wsl	.308
38	vit_relpos_base_patch16_clsgap_224:sw_in1k	.307
39	ViT_L_32_imagenet1k	.303
40	convnext_large_imagenet_full_seed-0	.303
41	mobilenet_v2_0.5_96	.302
42	deit_large_imagenet_full_seed-0	.302
43	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.300
44	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.300
45	resnext101_32x32d_wsl	.299
46	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.296
47	ViT_B_16_imagenet1k	.295
48	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.295
49	effnetv2m_custom384	.295
50	mobilenet_v2_0.35_96	.294
51	convnext_small_imagenet_full_seed-0	.294
52	convnext_base_imagenet_full_seed-0	.291
53	vit_base_patch16_clip_224:openai_ft_in1k	.289
54	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.282
55	convnext_base:clip_laiona_augreg_ft_in1k_384	.281
56	deit_base_imagenet_full_seed-0	.280
57	convnext_tiny_imagenet_full_seed-0	.280
58	AT_efficientnet-b2	.277
59	AdvProp_efficientnet-b2	.277
60	ViT_B_32_imagenet1k	.276
61	resnext101_32x8d_wsl	.275
62	fixres_resnext101_32x48d_wsl	.272
63	convnext_small_imagenet_100_seed-0	.267
64	mobilenet_v2_0.5_128	.265
65	blt_vs	.265
66	mobilenet_v2_0.35_128	.261
67	convnext_tiny:in12k_ft_in1k	.259
68	resnet50-SIN_IN	.258
69	resnet-152_v2-tf	.255
70	mobilenet_v2_0.75_96	.254
71	focalnet_tiny_lrf_in1k	.252
72	mobilenet_v2_1_0_128	.251
73	deit_small_imagenet_full_seed-0	.251
74	inception_v1	.249
75	resnet_101_v2	.246
76	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.245
77	AdvProp_efficientnet-b0	.243
78	resnet-101_v2-tf	.242
79	cv_18_dagger_408_pretrained	.242
80	voneresnet-50	.242
81	mobilenet_v2_0.5_160	.241
82	mobilenet_v2_0.75_128	.241
83	inception_v3	.241
84	mobilenet_v2_0.35_192	.240
85	mobilenet_v2_0.35_160	.237
86	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.235
87	resnet-50_v2-tf	.235
88	mobilenet_v1_0.25_128	.235
89	mobilenet_v2_1.0_96	.230
90	mobilenet_v2_0_5_192	.230
91	mobilenet_v2_0_75_160	.230
92	nasnet_large-tf	.228
93	vonegrcnn_47e	.228
94	inception_v3_pytorch	.228
95	inception_v4-tf	.227
96	effnetb1_272x240	.227
97	vonegrcnn_52e_full	.226
98	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.226
99	vonegrcnn_52e_full	.226
100	nasnet_large	.225
101	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.224
102	vonegrcnn_62e_nobn	.223
103	vonegrcnn_47e	.222
104	mobilenet_v2_1.0_192-tf	.221
105	nasnet_mobile	.221
106	mobilenet_v2_0.5_192-tf	.220
107	inception_v2-tf	.220
108	mobilenet_v2_0.75_160-tf	.220
109	inception_v3-tf	.220
110	mobilenet_v2_0_5_224	.220
111	mobilenet_v2_1.0_128-tf	.219
112	pnasnet_large_pytorch	.219
113	mobilenet_v2_1_0_192	.218
114	vonegrcnn_62e_nobn	.217
115	mobilenet_v2_1_0_160	.216
116	cvt_cvt-13-224-in1k_4_LucyV4	.216
117	inception_v1-tf	.215
118	mobilenet_v1_0.5_128	.215
119	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
120	mobilenet_v1_0.25_160	.214
121	mobilenet_v1_0.75_128	.214
122	alexnet_early_checkpoint	.214
123	mobilenet_v2_0.75_192-tf	.212
124	densenet-201-keras	.212
125	inception_v4	.212
126	densenet-201	.212
127	densenet_201_pytorch	.212
128	resnet50-VITO-8deg-cc	.211
129	efficientnet_b0	.209
130	convnext_tiny_sup	.209
131	BiT-S-R152x2	.209
132	BiT-S-R50x1	.209
133	cvt_cvt-13-384-in1k_4_LucyV4	.209
134	resnet_152_v1	.207
135	densenet-169	.207
136	BiT-S-R101x1	.206
137	mobilenet_v2_0.5_224-tf	.205
138	densenet-169-keras	.205
139	mobilenet_v2_0_75_192	.205
140	resnet50-vitoimagevidnet8	.205
141	resnet_50_v2	.205
142	antialias-resnet152	.204
143	grcnn_109	.204
144	resnet50_moco_v2	.203
145	cvt_cvt-21-224-in1k_4_LucyV4	.202
146	resnet152_imagenet_full	.202
147	mobilenet_v2_1.0_160-tf	.202
148	alexnet_random_linf8_perturb	.202
149	mobilenet_v1_0.5_160	.201
150	convnext_femto_ols:d1_in1k	.201
151	alexnet	.200
152	antialiased-rnext101_32x8d	.200
153	resnet_152_v2	.200
154	mobilenet_v2_1_0_224	.199
155	resnet_101_v1	.199
156	voneresnet-50-non_stochastic	.198
157	resnet-101_v1-tf	.198
158	resnet34_imagenet_full	.198
159	efficientnet_b0_imagenet_full	.198
160	mobilenet_v2_0.35_224	.197
161	resnet-152_v1-tf	.197
162	BiT-S-R101x3	.196
163	mobilenet_v1_0.25_192	.196
164	pnasnet_large-tf	.195
165	mobilenet_v2_0_75_224	.195
166	xception	.195
167	pnasnet_large	.195
168	resnet-34	.193
169	BiT-S-R152x4	.192
170	resnet50	.192
171	tv_efficientnet-b1	.192
172	xception-keras	.191
173	resnet-18	.191
174	densenet-121-keras	.190
175	densenet-121	.190
176	alexnet-baseline	.189
177	alexnet	.189
178	alexnet	.189
179	alexnet	.189
180	alexnet	.189
181	mobilenet_v1_1.0_128	.189
182	alexnet	.189
183	alexnet	.189
184	alexnet	.189
185	alexnet_ks_torevert	.189
186	resnet101_imagenet_full	.189
187	grcnn	.186
188	resnet18_imagenet_full	.185
189	CLIP-RN50	.184
190	resnet-50-pytorch	.182
191	resnet50-sup	.182
192	mobilenet_v1_0.75_160	.182
193	shufflenet_v2_x1_0	.182
194	regnet_y_400mf	.182
195	resnet50_imagenet_full	.182
196	resnet50_tutorial	.182
197	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.182
198	resnet_50_v1	.182
199	mobilenet_v1_0.5_192	.181
200	BiT-S-R50x3	.180
201	mobilenet_v2_0.75_224-tf	.180
202	ReAlnet06	.180
203	resnet-50_v1-tf	.178
204	mobilenet_v1_0.25_224	.178
205	antialiased-r50	.178
206	mobilenet_v2_1.0_224-tf	.177
207	resnet_50_v1_spiking	.177
208	nasnet_mobile-tf	.177
209	CORnet-S	.177
210	Res2Net50_26w_4s	.177
211	ReAlnet02	.176
212	cvt_cvt-21-384-in1k_4_LucyV4	.175
213	efficientnet_b1_imagenet_full	.174
214	resnet_SIN_IN_FT_IN	.173
215	resnet50-SIN_IN_IN	.173
216	vgg-19-keras	.172
217	resnet50-moclr8deg	.172
218	ReAlnet04	.172
219	efficientnet_b2_imagenet_full	.171
220	resnet-152_v2_pytorch	.171
221	ReAlnet03	.171
222	ReAlnet05	.170
223	mobilenet_v1_1.0_160	.170
224	mobilenet_v1_1.0_192	.168
225	ReAlnet08	.167
226	ReAlnet10	.167
227	mobilenet_v2_1-4_224_pytorch	.166
228	mobilenet_v2_1_4_224	.166
229	mobilenet_v1_0.75_224	.166
230	ReAlnet07	.166
231	mobilenet_v2_1_3_224	.166
232	ReAlnet01	.166
233	squeezenet1_1	.165
234	ReAlnet09	.165
235	mobilenet_v2_1.4_224-tf	.162
236	mobilenet_v1_0.75_192	.162
237	0.5x_resnet-18_LC_w_sh_1_iter	.159
238	resnet50_eMMCR_Vanilla	.158
239	vgg-16-keras	.157
240	mobilenet_v2_1.3_224-tf	.156
241	deit_small_imagenet_100_seed-0	.156
242	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.155
243	resnet_50_v1_spiking_l4a	.154
244	mobilenet_v1_1.0_224	.148
245	resnet50_imagenet_100_seed-0	.148
246	vgg_19	.144
247	mobilenet_v1_0.5_224	.143
248	resnet_50_v1_spiking_l4	.137
249	squeezenet1_0	.135
250	vgg_16	.116
251	convnext_small_imagenet_10_seed-0	.114
252	deit_small_imagenet_10_seed-0	.088
253	alexnet_training_seed_07	.084
254	deit_small_imagenet_1_seed-0	.077
255	alexnet_training_seed_06	.076
256	convnext_small_imagenet_1_seed-0	.076
257	alexnet_training_seed_09	.074
258	resnet50_imagenet_10_seed-0	.074
259	resnet50_imagenet_1_seed-0	.073
260	resnet50-vicregl0p9	.070
261	resnet50-meshes-lt-100-original-pretrained	.065
262	resnet50-vicregl0p75	.064
263	resnet50-barlow	.063
264	resnet50-meshes-lt-100-original-scratch	.062
265	alexnet_training_seed_05	.062
266	alexnet_training_seed_02	.062
267	alexnet_training_seed_04	.062
268	alexnet_training_seed_08	.062
269	alexnet_training_seed_10	.062
270	alexnet_training_seed_01	.062
271	alexnet_training_seed_03	.062
272	barlow-twins-resnet50	.060
273	resnet-50_untrained	.060
274	resnet50-simclr-vissl	.059
275	resnet_50_v1_spiking_l3	.055
276	artResNet18_1	.053
277	ViT-B/32
278	resnet-18-LC_w_sh_100_iter_conv_init_m
279	BiT-M-R50x1
280	resnet-18-LC_w_sh_1_iter_conv_init_m
281	BiT-M-R152x2
282	resnet-18-LC_w_sh_1_iter_m
283	resnet-18-LC_w_sh_10_iter_m
284	BiT-M-R50x3
285	resnet-18-LC_w_sh_100_iter_m
286	resnet-18-LC_w_sh_10_iter_conv_init_m
287	FrankRobWobv0
288	0.5x_resnet-18_LC
289	CORnetZ_CIFAR10
290	resnet18-local_aggregation
291	r3m_resnet18
292	resnet18-deepcluster
293	CORnet-Z
294	vggface
295	my-model
296	resnet18-instance_recognition
297	0.5x_resnet-18_LC_w_sh_10_iter
298	r3m_resnet50
299	r3m_resnet34
300	resnet-18-LC_m
301	resnet18-supervised
302	r3m_resnet50_nocrop
303	resnet-18-LC_1st_conv_m
304	resnet-18-LC_conv_init_m
305	resnet18-contrastive_multiview
306	0.5x_resnet-18
307	RN50
308	0.5x_resnet-18_LC_w_sh_100_iter
309	RN50
310	resnet18-colorization
311	resnet18-relative_position
312	resnet18-autoencoder
313	resnet18-simclr
314	ViT_L_32
315	ViT_B_32
316	resnet18-depth_prediction
317	ViT_B_16
318	r3m_resnet34_nocrop
319	resnet18-contrastive_predictive
320	resnet-18-LC_untrained
321	resnet-18_untrained
322	resnet-50x2_untrained
323	dcgan
324	unet_entire
325	CORnetZ_CIFAR10_bs32_20_04
326	v1-pyr-nodown
327	pixels
328	dorinet_cornet_z
329	omnivore_swinT
330	resnet50
331	openclip
332	vonealexnet_gaussian_noise_std4_fixed
333	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
334	yudixie_resnet50_imagenet1kpret_0_240312
335	yudixie_resnet50_category_class_0_240908
336	yudixie_resnet50_distance_reg_0_240908
337	resnet18_imagenet21kP
338	ConvLSTM
339	PredRNN
340	SimVP
341	briaai_rmbg_1_4
342	TAU
343	MIM
344	ReAlnet01_cornet
345	yudixie_resnet18_distance_translation_0_240719
346	mobilevit_small
347	yudixie_resnet18_translation_reg_0_240719
348	yolos_tiny
349	yudixie_resnet18_distance_reg_0_240719
350	yudixie_resnet18_rotation_reg_0_240719
351	ReAlnet03_cornet
352	yudixie_resnet50_distance_translation_0_240908
353	yudixie_resnet50_distance_rotation_0_240908
354	resnet18_ecoset_full
355	resnet34_ecoset_full
356	ReAlnet04_cornet
357	resnet50_ecoset_full
358	yudixie_resnet50_rotation_reg_0_240908
359	resnet101_ecoset_full
360	resnet152_ecoset_full
361	yudixie_resnet18_translation_rotation_0_240719
362	yudixie_resnet50_translation_reg_0_240908
363	yudixie_resnet18_distance_rotation_0_240719
364	resnet-18_test_m
365	yudixie_resnet18_category_class_0_240719
366	yudixie_resnet18_random_0_240719
367	yudixie_resnet18_cat_obj_class_all_latents_0_240719
368	SeLaVi-AVE
369	yudixie_resnet18_object_class_0_240719
370	yudixie_resnet18_imagenet1kpret_0_240719
371	hmax
372	ReAlnet06_cornet
373	r3d_18
374	yudixie_resnet50_translation_rotation_0_240908
375	ReAlnet07_cornet
376	ReAlnet01_ALL
377	mc3_18
378	ReAlnet02_ALL
379	s3d
380	ReAlnet08_cornet
381	VOneCORnet-S
382	resnet50-vicreg
383	mvit_v1_b
384	omnivore_swinB
385	ReAlnet03_ALL
386	ReAlnet09_cornet
387	ReAlnet04_ALL
388	omnivore_swinS
389	SeLaVi-Kinetics400
390	ReAlnet05_ALL
391	SeLaVi-VGG-Sound
392	ReAlnet06_ALL
393	SeLaVi-Kinetics-Sound
394	ReAlnet10_cornet
395	mvit_v2_s
396	yudixie_resnet50_distance_translation_rotation_0_240908
397	ReAlnet07_ALL
398	r2plus1d_18
399	yudixie_resnet50_random_0_240908
400	yudixie_resnet50_imagenet1kpret_0_240908
401	ReAlnet08_ALL
402	yudixie_resnet50_cat_obj_class_all_latents_0_240908
403	yudixie_resnet50_object_class_0_240908
404	ReAlnet09_ALL
405	yudixie_resnet18_distance_translation_rotation_0_240719
406	resnet50_primary_visual_cortex
407	ReAlnet02_cornet
408	ReAlnet10_ALL
409	ReAlnet05_cornet

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