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("Hermann2020cueconflict-shape_match")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitg14_reg_lc	.567
2	convnext_xxlarge_clip	.554
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.550
4	dinov2_vitg14_lc	.529
5	AdvProp_efficientnet-b8	.527
6	dinov2_vitl14_reg_lc	.518
7	eva02_large_in22k	.516
8	imagenet_l2_10_0	.515
9	resnet50-SIN	.506
10	AdvProp_efficientnet-b6	.497
11	AdvProp_efficientnet-b7	.495
12	resnet50_linf_8_robust	.482
13	dinov2_vitl14_lc	.477
14	dinov2_vitl14_lc_res336	.470
15	AlexNet_SIN	.461
16	AlexNet_SIN_fov4	.461
17	AlexNet_SIN_fov12	.461
18	AlexNet_SIN_fov16	.461
19	resnet50_l2_3_robust	.439
20	resnet-50-robust	.432
21	imagenet_l2_3_0	.432
22	resnet50_robust_l2_eps3	.432
23	resnet50_linf_4_robust	.427
24	AT_efficientnet-b4	.415
25	AdvProp_efficientnet-b4	.415
26	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.412
27	alexnet_linf_8_robust	.404
28	voneresnet-50-robust	.393
29	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.380
30	alexnet_l2_3_robust	.372
31	vit_huge_clip336_laion	.369
32	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.359
33	alexnet_robust_correct	.355
34	efficientnet-b7	.353
35	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.347
36	vit_large_clip336_openai	.340
37	vit_large_patch14_clip_224:openai_ft_in1k	.339
38	convnext_xlarge:fb_in22k_ft_in1k	.331
39	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.326
40	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.321
41	deit3_base_patch16_224_fb_in1k	.320
42	vit_large_patch14_clip_224:laion2b_ft_in1k	.314
43	convnext_large:fb_in22k_ft_in1k	.310
44	convnext_large_in22k_supervised	.302
45	resnet50_robust_l2_eps1	.301
46	resnext101_32x48d_wsl	.299
47	vit_large_patch14_clip_336:laion2b_ft_in1k	.299
48	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.297
49	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.293
50	custom_model_cv_18_dagger_408	.287
51	convnext_large_clip_laion2b_finelayers	.279
52	resnext101_32x16d_wsl	.277
53	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.277
54	mobilenet_v2_0.5_96	.274
55	vit_relpos_base_patch16_clsgap_224:sw_in1k	.274
56	ViT_L_32_imagenet1k	.270
57	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.268
58	resnext101_32x32d_wsl	.267
59	deit_large_imagenet_full_seed-0	.265
60	convnext_large_imagenet_full_seed-0	.265
61	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.264
62	convnext_base_fb_in22k_ft_in1k	.261
63	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.260
64	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.258
65	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.257
66	effnetv2m_custom384	.256
67	convnext_small_imagenet_full_seed-0	.255
68	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.251
69	convnext_base_imagenet_full_seed-0	.249
70	vit_base_patch16_clip_224:openai_ft_in1k	.247
71	convnext_base:clip_laiona_augreg_ft_in1k_384	.244
72	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.244
73	AdvProp_efficientnet-b2	.241
74	AT_efficientnet-b2	.241
75	deit_base_imagenet_full_seed-0	.240
76	resnext101_32x8d_wsl	.239
77	convnext_tiny_imagenet_full_seed-0	.238
78	fixres_resnext101_32x48d_wsl	.237
79	mobilenet_v2_0.35_128	.237
80	mobilenet_v2_0.5_128	.234
81	blt_vs	.233
82	convnext_small_imagenet_100_seed-0	.228
83	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.226
84	mobilenet_v2_0.75_96	.224
85	voneresnet-50	.224
86	mobilenet_v2_1_0_128	.221
87	resnet50-SIN_IN	.219
88	resnet-152_v2-tf	.217
89	convnext_base_fb_in1k	.217
90	convnext_tiny:in12k_ft_in1k	.217
91	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.216
92	focalnet_tiny_lrf_in1k	.209
93	inception_resnet_v2	.208
94	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.208
95	AdvProp_efficientnet-b0	.207
96	mobilenet_v2_0.5_160	.207
97	inception_v1	.207
98	deit_small_imagenet_full_seed-0	.206
99	resnet_101_v2	.206
100	mobilenet_v1_0.25_128	.206
101	cv_18_dagger_408_pretrained	.205
102	mobilenet_v2_0.75_128	.205
103	mobilenet_v2_0.35_192	.205
104	resnet-101_v2-tf	.203
105	regnety_032	.202
106	mobilenet_v2_0.35_160	.201
107	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.199
108	mobilenet_v2_1.0_96	.199
109	inception_v3	.197
110	alexnet_reduced_aliasing_early_checkpoint	.196
111	mobilenet_v2_0_75_160	.195
112	vonegrcnn_52e_full	.195
113	mobilenet_v2_0_5_192	.193
114	pnasnet_large_pytorch	.193
115	resnet-50_v2-tf	.192
116	vonegrcnn_62e_nobn	.192
117	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.192
118	SWSL_resnet50	.191
119	seresnext50_32x4d	.189
120	inception_v3_pytorch	.188
121	vonegrcnn_62e_nobn	.188
122	mobilenet_v2_0.75_160-tf	.188
123	vonegrcnn_52e_full	.188
124	mobilenet_v2_1.0_128-tf	.185
125	inception_v4-tf	.185
126	nasnet_large-tf	.184
127	vonegrcnn_47e	.184
128	mobilenet_v2_0.5_192-tf	.183
129	mobilenet_v1_0.75_128	.182
130	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.182
131	nasnet_large	.182
132	mobilenet_v2_1.0_192-tf	.182
133	mobilenet_v1_0.5_128	.182
134	vonegrcnn_47e	.182
135	mobilenet_v2_1_0_160	.181
136	effnetb1_272x240	.181
137	inception_v2-tf	.181
138	inception_v3-tf	.180
139	mobilenet_v2_0_5_224	.180
140	nasnet_mobile	.180
141	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.177
142	mobilenet_v2_1_0_192	.176
143	resnet50_random_linf8_perturb	.174
144	resnet50_st_wzc_seed6_2_323	.173
145	mobilenet_v2_0.75_192-tf	.173
146	BiT-S-R152x2	.172
147	inception_v1-tf	.172
148	alexnet_early_checkpoint	.172
149	resnet50_ewconplus_wzc_seed6_2_323	.172
150	resnet50_ewconplus_wzc	.172
151	inception_v4	.172
152	cvt_cvt-13-224-in1k_4_LucyV4	.172
153	BiT-S-R50x1	.170
154	densenet-201-keras	.170
155	densenet-201	.170
156	densenet_201_pytorch	.170
157	resnet50_st_wzc_2	.169
158	alexnet_random_l2_3_perturb	.168
159	resnet50-VITO-8deg-cc	.167
160	efficientnet_b0	.166
161	convnext_tiny_sup	.166
162	mobilenet_v2_1.0_160-tf	.165
163	resnet50_moco_v2	.165
164	mobilenet_v2_0_75_192	.165
165	mobilenet_v1_0.25_192	.164
166	alexnet_random_linf8_perturb	.164
167	resnet152_imagenet_full	.164
168	grcnn_109	.164
169	cvt_cvt-13-384-in1k_4_LucyV4	.163
170	resnet_152_v1	.163
171	mobilenet_v1_0.5_160	.163
172	antialias-resnet152	.163
173	BiT-S-R101x1	.163
174	resnet50_ewconplus_wzc_seed2_2__323	.163
175	resnet50_st_wzc_seed3_2_323	.162
176	densenet-169	.162
177	resnet50_st_wzc_seed7_2_323	.162
178	cvt_cvt-21-224-in1k_4_LucyV4	.161
179	xception	.161
180	mobilenet_v2_0.5_224-tf	.161
181	voneresnet-50-non_stochastic	.160
182	densenet-169-keras	.160
183	resnet50_hvs_wzc	.160
184	resnet_50_v2	.159
185	resnet_152_v2	.158
186	resnet-101_v1-tf	.158
187	antialiased-rnext101_32x8d	.158
188	BiT-S-R152x4	.157
189	mobilenet_v1_1.0_128	.157
190	BiT-S-R101x3	.157
191	resnet_101_v1	.157
192	resnet-152_v1-tf	.156
193	efficientnet_b0_imagenet_full	.155
194	mobilenet_v2_1_0_224	.155
195	mobilenet_v2_0.35_224	.154
196	resnet34_imagenet_full	.154
197	convnext_femto_ols:d1_in1k	.154
198	convnext_base_fb_in1k_gram_aligned_dinov3	.153
199	pnasnet_large-tf	.152
200	mobilenet_v2_0_75_224	.152
201	resnet-34	.152
202	resnet50-vitoimagevidnet8	.152
203	resnet101_imagenet_full	.152
204	resnet50_ewconplus_wzc_seed5_2__323	.152
205	alexnet_ks_torevert	.151
206	alexnet_fov12	.151
207	alexnet_fov4	.151
208	pnasnet_large_halfPrecision	.151
209	alexnet_fov16	.151
210	pnasnet_large	.151
211	alexnet	.151
212	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.148
213	resnet-18	.147
214	xception-keras	.147
215	mobilenet_v1_0.75_160	.147
216	grcnn	.146
217	BiT-S-R50x3	.145
218	shufflenet_v2_x1_0	.145
219	densenet-121-keras	.144
220	densenet-121	.144
221	resnet_50_v1_spiking	.142
222	resnet18_imagenet_full	.142
223	CLIP-RN50	.142
224	resnet50_tutorial	.141
225	resnet_50_v1	.141
226	resnet50-sup	.141
227	resnet-50-pytorch	.141
228	eBarlow_lmda_02_1000ep	.140
229	regnet_y_400mf	.139
230	resnet50_imagenet_full	.139
231	nasnet_mobile-tf	.138
232	mobilenet_v1_0.25_224	.138
233	resnet50_random_l2_perturb	.138
234	mobilenet_v2_0.75_224-tf	.138
235	resnet-50_v1-tf	.137
236	resnet50-moclr8deg	.137
237	cvt_cvt-21-384-in1k_4_LucyV4	.137
238	Res2Net50_26w_4s	.136
239	mobilenet_v2_1-4_224_pytorch	.136
240	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.136
241	mobilenet_v2_1_4_224	.136
242	resnet-152_v2_pytorch	.135
243	mobilenet_v1_1.0_160	.134
244	ReAlnet06	.134
245	mobilenet_v2_1.0_224-tf	.133
246	antialiased-r50	.133
247	resnet_SIN_IN_FT_IN	.133
248	resnet50-SIN_IN_IN	.133
249	ReAlnet02	.133
250	mobilenet_v1_1.0_192	.130
251	CORnet-S	.130
252	efficientnet_b2_imagenet_full	.130
253	efficientnet_b1_imagenet_full	.129
254	ReAlnet03	.129
255	ReAlnet05	.128
256	vgg-19-keras	.128
257	ReAlnet04	.128
258	squeezenet1_1	.126
259	resnet50_byol	.124
260	ReAlnet08	.124
261	ReAlnet10	.123
262	mobilenet_v1_0.75_192	.123
263	0.5x_resnet-18_LC_w_sh_1_iter	.122
264	mobilenet_v2_1_3_224	.122
265	ReAlnet07	.122
266	deit_small_imagenet_100_seed-0	.122
267	ReAlnet01	.122
268	mobilenet_v2_1.4_224-tf	.119
269	ReAlnet09	.119
270	mobilenet_v1_0.75_224	.117
271	resnet50_simclr	.117
272	resnet50_imagenet_100_seed-0	.116
273	mobilenet_v2_1.3_224-tf	.113
274	resnet_50_v1_spiking_l4a	.111
275	convnext_small_imagenet_10_seed-0	.110
276	vgg-16-keras	.109
277	mobilenet_v1_1.0_224	.107
278	mobilenet_v1_0.5_224	.105
279	resnet_50_v1_spiking_l4	.099
280	squeezenet1_0	.089
281	deit_small_imagenet_10_seed-0	.088
282	alexnet_training_seed_07	.084
283	deit_small_imagenet_1_seed-0	.078
284	alexnet_training_seed_06	.076
285	resnet50-barlow	.076
286	alexnet_training_seed_09	.074
287	convnext_small_imagenet_1_seed-0	.072
288	vgg_19	.071
289	resnet50_imagenet_1_seed-0	.069
290	mobilevit_small	.065
291	my-model	.064
292	resnet_50_v1_spiking_l3	.064
293	vgg_16	.064
294	resnet50-vicregl0p75	.064
295	alexnet_training_seed_05	.062
296	alexnet_training_seed_02	.062
297	alexnet_training_seed_04	.062
298	alexnet_training_seed_08	.062
299	alexnet_training_seed_10	.062
300	alexnet_training_seed_01	.062
301	alexnet_training_seed_01_fov4	.062
302	alexnet_training_seed_01_fov12	.062
303	alexnet_training_seed_01_fov16	.062
304	alexnet_training_seed_03	.062
305	resnet50_imagenet_10_seed-0	.061
306	barlow-twins-resnet50	.060
307	resnet50-simclr-vissl	.059
308	resnet50-vicregl0p9	.048
309	artResNet18_1	.045
310	BiT-M-R50x3
311	BiT-M-R101x3
312	BiT-M-R50x1
313	BiT-M-R152x4
314	BiT-M-R101x1
315	BiT-M-R152x2
316	FrankRobWobv0
317	omnivore_swinT
318	ViT-B/32
319	0.5x_resnet-18
320	0.5x_resnet-18_LC_w_sh_100_iter
321	RN50
322	r3m_resnet18
323	CORnet-Z
324	0.5x_resnet-18_LC
325	vggface
326	r3m_resnet50
327	r3m_resnet34
328	resnet18-supervised
329	resnet18-local_aggregation
330	ViT_B_16_imagenet1k
331	vision_transformer_vit_large_patch16_224
332	CLIP_ViT-B_32
333	SWSL_resnext101_32x8d
334	CLIP_resnet50
335	CLIP_resnet50_float32
336	resnet101
337	resnet50
338	texture_shape_resnet50_trained_on_SIN
339	cornet_s
340	vonealexnet_gaussian_noise_std4_fixed
341	texture_shape_alexnet_trained_on_SIN
342	0.5x_resnet-18_LC_w_sh_10_iter
343	resnet18-contrastive_multiview
344	resnet18-colorization
345	resnet18-simclr
346	resnet18-depth_prediction
347	CORnetZ_CIFAR10
348	resnet18-deepcluster
349	v1-pyr-nodown
350	my-model
351	resnet18-relative_position
352	ViT_B_32_imagenet1k
353	CORnetZ_CIFAR10_bs32_20_04
354	dorinet_cornet_z
355	ViT_L_16_imagenet1k
356	resnet18-autoencoder
357	ViT_L_32
358	ViT_B_32
359	ViT_B_16
360	r3m_resnet34_nocrop
361	dcgan
362	fitvid_trained_on_physion
363	pixels
364	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4
365	yudixie_resnet50_imagenet1kpret_0_240312
366	yudixie_resnet50_category_class_0_240908
367	yudixie_resnet50_distance_reg_0_240908
368	resnet18_imagenet21kP
369	ConvLSTM
370	briaai_rmbg_1_4
371	PredRNN
372	SimVP
373	TAU
374	MIM
375	hmax
376	ReAlnet01_cornet
377	ReAlnet02_cornet
378	yolos_tiny
379	yudixie_resnet18_translation_reg_0_240719
380	compact_resnet50_V4
381	yudixie_resnet18_distance_reg_0_240719
382	yudixie_resnet18_rotation_reg_0_240719
383	yudixie_resnet18_imagenet1kpret_0_240719
384	ReAlnet03_cornet
385	yudixie_resnet50_distance_rotation_0_240908
386	yudixie_resnet50_distance_translation_0_240908
387	yudixie_resnet50_rotation_reg_0_240908
388	compact_resnet50_IT
389	vit_base_patch16_dinov3-lvd1689m
390	resnet18_ecoset_full
391	VOneCORnet-S
392	resnet34_ecoset_full
393	ReAlnet04_cornet
394	resnet50_ecoset_full
395	ReAlnet01_cornet_fov4
396	resnet101_ecoset_full
397	resnet152_ecoset_full
398	compact_vgg19_V4
399	yudixie_resnet18_distance_translation_0_240719
400	omnivore_swinB
401	yudixie_resnet18_translation_rotation_0_240719
402	ReAlnet05_cornet
403	resnet-18_test_m
404	yudixie_resnet18_distance_rotation_0_240719
405	ReAlnet01_cornet_fov12
406	yudixie_resnet18_category_class_0_240719
407	yudixie_resnet18_random_0_240719
408	yudixie_resnet50_translation_reg_0_240908
409	yudixie_resnet18_cat_obj_class_all_latents_0_240719
410	yudixie_resnet18_distance_translation_rotation_0_240719
411	ReAlnet06_cornet
412	compact_vgg19_IT
413	yudixie_resnet18_object_class_0_240719
414	ReAlnet01_cornet_fov16
415	compact_resnet50_robust_V4
416	ReAlnet07_cornet
417	ReAlnet01_ALL
418	yudixie_resnet50_translation_rotation_0_240908
419	ReAlnet08_cornet
420	ReAlnet02_ALL
421	resnet50-vicreg
422	ReAlnet04_ALL
423	compact_cornets_V4
424	ReAlnet09_cornet
425	ReAlnet03_ALL
426	compact_cornets_IT
427	omnivore_swinS
428	ReAlnet05_ALL
429	ReAlnet10_cornet
430	ReAlnet06_ALL
431	yudixie_resnet50_imagenet1kpret_0_240908
432	yudixie_resnet50_random_0_240908
433	compact_resnet50_robust_IT
434	ReAlnet07_ALL
435	yudixie_resnet50_distance_translation_rotation_0_240908
436	yudixie_resnet50_cat_obj_class_all_latents_0_240908
437	yudixie_resnet50_object_class_0_240908
438	ReAlnet08_ALL
439	ReAlnet09_ALL
440	resnet50_primary_visual_cortex
441	ReAlnet10_ALL
442	vit_base_patch14_reg4_dinov2-lvd142m
443	vit_base_patch14_dinov2-lvd142m
444	resnet18_fair
445	pr1_stl10_disentangled_alpha04
446	predictive_coding_pc
447	yudixie_wbh_object_class_scaling_0415_run_0
448	yudixie_wbh_object_class_scaling_0415_run_3
449	yudixie_wbh_object_class_scaling_0415_imagenet
450	yudixie_wbh_object_class_scaling_0415_run_2
451	yudixie_wbh_object_class_scaling_0415_run_1
452	deepeisnn_ei_cifar10_vgg19
453	deepeisnn_ei_cifar10_resnet18
454	deepeisnn_ei_imagenet_resnet18
455	dinov2_vitl14_reg_lc_featread
456	gabor_filter_entropy_4x4
457	gabor_filter_mean_abs_4x4_v2
458	gabor_filter_entropy_4x4_v2
459	gabor_filter_entropy_4x4_v2_forcedCosine

Benchmark bibtex

@article{hermann2020origins,
              title={The origins and prevalence of texture bias in convolutional neural networks},
              author={Hermann, Katherine and Chen, Ting and Kornblith, Simon},
              journal={Advances in Neural Information Processing Systems},
              volume={33},
              pages={19000--19015},
              year={2020},
              url={https://proceedings.neurips.cc/paper/2020/hash/db5f9f42a7157abe65bb145000b5871a-Abstract.html}
        }

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: Hermann2020cueconflict

Metric: shape_match