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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Hebart2023-match")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	bp_resnet50_julios	1.0
2	dinov2_vitl14_reg_lc	.538
3	dinov2_vitl14_lc	.535
4	dinov2_vitg14_lc	.534
5	resnet50-moclr8deg	.534
6	dinov2_vitl14_lc_res336	.528
7	dinov2_vitl14_reg_lc_featread	.525
8	dinov2_vitg14_reg_lc	.519
9	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.504
10	resnet50_robust_l2_eps1	.503
11	vonegrcnn_47e	.498
12	vonegrcnn_62e_nobn	.494
13	vonegrcnn_52e_full	.490
14	resnet_SIN_IN_FT_IN	.489
15	resnet50_tutorial	.488
16	ijepa_vith14_linhead	.483
17	resnet50-vitoimagevidnet8	.483
18	resnet50-VITO-8deg-cc	.483
19	densenet_201_pytorch	.476
20	resnet50_robust_l2_eps3	.476
21	imagenet_l2_3_0	.476
22	resnet50_simsiam_linhead	.473
23	resnet18_imagenet21kP	.470
24	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.469
25	antialias-resnet152	.464
26	vit_base_patch14_reg4_dinov2-lvd142m	.463
27	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.463
28	vit_base_patch14_dinov2-lvd142m	.452
29	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.416
30	resnet_50_v2	.408
31	vgg_16	.407
32	resnext101_32x8d_wsl	.407
33	mehrer2020_alexnet_training_seed_04	.405
34	vgg_19	.404
35	mehrer2020_alexnet_training_seed_07	.402
36	mehrer2020_alexnet_training_seed_10	.401
37	mehrer2020_alexnet_training_seed_09	.400
38	efficientnet_b0_imagenet_full	.399
39	mehrer2020_alexnet_training_seed_06	.399
40	mehrer2020_alexnet_training_seed_02	.399
41	mehrer2020_alexnet_training_seed_08	.398
42	mehrer2020_alexnet_training_seed_01	.398
43	mehrer2020_alexnet_training_seed_03	.396
44	efficientnet_b1_imagenet_full	.396
45	efficientnet_b2_imagenet_full	.396
46	vit_base_patch16_dinov3-lvd1689m	.395
47	mehrer2020_alexnet_training_seed_05	.394
48	convnext_base_fb_in1k_gram_aligned_dinov3	.391
49	resnext101_32x16d_wsl	.387
50	vith14_supervised_linhead	.382
51	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.381
52	shufflenet_v2_x1_0	.379
53	resnet-152_v2_pytorch	.375
54	alexnet_ks_torevert	.375
55	alexnet	.375
56	voneresnet-50-robust	.372
57	custom_model_cv_18_dagger_408	.371
58	voneresnet-50-non_stochastic	.368
59	ReAlnet09_cornet	.364
60	ReAlnet09	.364
61	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.363
62	grcnn	.361
63	deepeisnn_ei_imagenet_resnet18	.361
64	resnet18_imagenet_full	.358
65	resnet34_imagenet_full	.358
66	ReAlnet04_cornet	.358
67	ReAlnet04	.358
68	ReAlnet01_cornet_fov12	.357
69	voneresnet-50	.357
70	grcnn_109	.356
71	resnet50_hvs_wzc	.356
72	Res2Net50_26w_4s	.354
73	ReAlnet05_cornet	.354
74	ReAlnet05	.354
75	mehrer2020_alexnet_training_seed_01_fov4	.353
76	resnet50_ewconplus_wzc_seed2_2__323	.353
77	resnet50-vicregl0p9	.352
78	resnet-50-robust	.352
79	pnasnet_large_pytorch	.351
80	ReAlnet06_cornet	.350
81	ReAlnet06	.350
82	ReAlnet03_cornet	.349
83	ReAlnet03	.349
84	ReAlnet07_cornet	.347
85	ReAlnet07	.347
86	ReAlnet01_cornet	.347
87	ReAlnet01	.347
88	resnet50_ewconplus_wzc_seed5_2__323	.346
89	ReAlnet01_cornet_fov16	.346
90	ReAlnet02_cornet	.346
91	ReAlnet02	.346
92	resnet50_ewconplus_wzc_seed6_2_323	.345
93	resnet50-vicregl0p75	.345
94	convnext_tiny_sup	.344
95	efficientnet_b0	.342
96	ReAlnet08_cornet	.342
97	ReAlnet08	.342
98	ReAlnet10_ALL	.341
99	ReAlnet10_cornet	.338
100	ReAlnet10	.338
101	alexnet_fov4	.336
102	resnet18_ecoset_full	.336
103	convnext_large:fb_in22k_ft_in1k	.336
104	ReAlnet08_ALL	.335
105	ReAlnet07_ALL	.333
106	resnet_101_v2	.333
107	resnet50_ewconplus_wzc	.332
108	ReAlnet03_ALL	.332
109	regnety_032	.331
110	mobilenet_v2_1_0_224	.330
111	mobilenet_v2_1_4_224	.330
112	mobilenet_v2_1-4_224_pytorch	.330
113	resnet50-SIN_IN	.329
114	ReAlnet05_ALL	.329
115	ReAlnet02_ALL	.328
116	ReAlnet04_ALL	.327
117	ReAlnet01_ALL	.327
118	ReAlnet06_ALL	.326
119	resnet_152_v2	.326
120	focalnet_tiny_lrf_in1k	.326
121	resnext101_32x32d_wsl	.325
122	eicircuit_resnet18_bn_20260919	.324
123	regnet_y_400mf	.322
124	resnet50_st_wzc_seed7_2_323	.321
125	ReAlnet09_ALL	.320
126	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.320
127	resnet50_st_wzc_2	.319
128	convnext_xlarge:fb_in22k_ft_in1k	.319
129	alexnet_fov12	.319
130	resnet50_imagenet_full	.318
131	resnet34_ecoset_full	.317
132	resnet101_imagenet_full	.316
133	convnext_base_fb_in22k_ft_in1k	.315
134	resnet50-barlow	.313
135	resnet50_st_wzc_seed3_2_323	.312
136	resnet50-vicreg	.311
137	resnet152_imagenet_full	.308
138	resnet_152_v1	.307
139	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.304
140	mehrer2020_alexnet_training_seed_01_fov12	.301
141	resnet_101_v1	.297
142	VOneCORnet-S	.296
143	densenet-121	.291
144	inception_v3_pytorch	.291
145	antialiased-r50	.290
146	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.289
147	alexnet_fov16	.289
148	resnet_50_v1	.288
149	resnet50-sup	.288
150	predictive_coding_pc	.288
151	densenet-201	.286
152	BiT-S-R50x1	.286
153	pr1_stl10_disentangled_alpha04	.284
154	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.281
155	AlexNet_SIN	.281
156	resnet50_imagenet_100_seed-0	.279
157	resnext101_32x48d_wsl	.278
158	resnet-18_test_m	.273
159	resnet50-SIN_IN_IN	.272
160	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
161	yudixie_resnet50_imagenet1kpret_0_240908	.271
162	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.270
163	yudixie_wbh_object_class_scaling_0415_imagenet	.270
164	ReAlnet01_cornet_fov4	.268
165	resnet50_ecoset_full	.266
166	convnext_tiny:in12k_ft_in1k	.265
167	AT_efficientnet-b2	.265
168	AdvProp_efficientnet-b2	.265
169	deit_large_imagenet_full_seed-0	.263
170	vit_huge_clip336_laion	.260
171	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.260
172	yudixie_resnet18_imagenet1kpret_0_240719	.258
173	convnext_base:clip_laiona_augreg_ft_in1k_384	.257
174	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
175	BiT-S-R101x1	.255
176	resnet50-SIN	.254
177	BiT-S-R50x3	.254
178	BiT-S-R152x2	.254
179	vonealexnet	.253
180	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.253
181	resnet101_ecoset_full	.253
182	mehrer2020_alexnet_training_seed_01_fov16	.252
183	densenet-169	.250
184	deit_small_imagenet_100_seed-0	.247
185	BiT-S-R101x3	.244
186	effnetb1_272x240	.242
187	convnext_femto_ols:d1_in1k	.242
188	convnext_base_fb_in1k	.241
189	cvt_cvt-21-224-in1k_4_LucyV4	.238
190	resnet152_ecoset_full	.238
191	convnext_small_imagenet_full_seed-0	.238
192	deit_base_imagenet_full_seed-0	.238
193	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.237
194	resnet50_eMMCR_Vanilla	.233
195	AlexNet_SIN_fov12	.232
196	AdvProp_efficientnet-b4	.228
197	deit3_base_patch16_224_fb_in1k	.227
198	inception_v1	.224
199	resnet50_cpc_linhead	.222
200	AlexNet_SIN_fov4	.221
201	convnext_tiny_imagenet_full_seed-0	.220
202	cvt_cvt-21-384-in1k_4_LucyV4	.219
203	eva02_large_in22k	.218
204	cvt_cvt-13-224-in1k_4_LucyV4	.217
205	AlexNet_SIN_fov16	.215
206	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.213
207	resnet_50_v1_spiking	.210
208	convnext_base_imagenet_full_seed-0	.209
209	deit_small_imagenet_full_seed-0	.207
210	resnet50_imagenet_10_seed-0	.206
211	vit_relpos_base_patch16_clsgap_224:sw_in1k	.203
212	vit_large_patch14_clip_224:laion2b_ft_in1k	.202
213	vit_large_patch14_clip_336:laion2b_ft_in1k	.200
214	vit_base_patch16_clip_224:openai_ft_in1k	.199
215	cvt_cvt-13-384-in1k_4_LucyV4	.198
216	convnext_small_imagenet_100_seed-0	.191
217	nasnet_mobile	.191
218	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.188
219	AdvProp_efficientnet-b6	.185
220	efficientnet-b7	.176
221	xception	.175
222	artResNet18_1	.173
223	tv_efficientnet-b1	.169
224	convnext_large_imagenet_full_seed-0	.166
225	vit_large_patch14_clip_224:openai_ft_in1k	.157
226	vith14_untrained_linhead	.156
227	resnet_50_v1_spiking_l4a	.155
228	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.153
229	pnasnet_large_halfPrecision	.151
230	pnasnet_large	.150
231	deepeisnn_ei_cifar10_resnet18	.144
232	AdvProp_efficientnet-b7	.142
233	convnext_large_clip_laion2b_finelayers	.141
234	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.139
235	persistence_memory	.139
236	persistence_mem	.138
237	deit_small_imagenet_10_seed-0	.133
238	AdvProp_efficientnet-b8	.132
239	resnet50_untrained_linhead	.131
240	resnet_50_v1_spiking_l4	.130
241	resnet18_fair	.129
242	mobilenet_v2_0_5_192	.129
243	seresnext50_32x4d	.121
244	inception_v3	.117
245	mobilenet_v2_0_5_224	.117
246	resnet50_imagenet_1_seed-0	.116
247	resnet50_supervised_linhead	.115
248	mobilenet_v2_0_75_160	.115
249	convnext_small_imagenet_10_seed-0	.114
250	convnext_large_in22k_supervised	.114
251	nasnet_large	.113
252	deepeisnn_ei_cifar10_vgg19	.113
253	inception_v4	.110
254	resnet50_primary_visual_cortex	.105
255	mobilenet_v2_1_0_128	.105
256	mobilenet_v2_0_75_192	.103
257	mobilenet_v2_0_75_224	.099
258	yudixie_resnet50_category_class_0_240908	.097
259	mobilenet_v2_1_0_160	.089
260	yudixie_resnet18_object_class_0_240719	.089
261	yudixie_resnet50_object_class_0_240908	.088
262	blt_vs	.086
263	mobilenet_v2_1_0_192	.085
264	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.083
265	convnext_small_imagenet_1_seed-0	.083
266	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.080
267	cv_18_dagger_408_pretrained	.077
268	compact_resnet50_IT	.072
269	yudixie_resnet18_category_class_0_240719	.071
270	yudixie_resnet18_distance_reg_0_240719	.070
271	mobilenet_v2_1_3_224	.070
272	BiT-S-R152x4	.059
273	yudixie_resnet18_distance_translation_rotation_0_240719	.056
274	yudixie_resnet18_distance_rotation_0_240719	.055
275	alexnet_training_seed_09	.053
276	compact_vgg19_IT	.053
277	ViT_L_32_imagenet1k	.052
278	alexnet_training_seed_08	.051
279	alexnet_training_seed_10	.051
280	alexnet_training_seed_05	.051
281	compact_resnet50_robust_IT	.049
282	alexnet_training_seed_01	.048
283	alexnet_training_seed_01_fov12	.048
284	alexnet_training_seed_03	.048
285	yudixie_resnet50_distance_rotation_0_240908	.047
286	alexnet_training_seed_02	.047
287	alexnet_training_seed_01_fov16	.046
288	yudixie_resnet18_distance_translation_0_240719	.046
289	alexnet_training_seed_04	.045
290	resnet50_byol_linhead	.045
291	briaai_rmbg_1_4	.045
292	alexnet_training_seed_07	.045
293	alexnet_training_seed_01_fov4	.044
294	compact_cornets_V4	.042
295	gabor_filter_mean_abs_4x4_v2	.041
296	alexnet_training_seed_06	.041
297	compact_cornets_IT	.041
298	yudixie_resnet50_distance_translation_rotation_0_240908	.040
299	yudixie_resnet50_distance_translation_0_240908	.040
300	resnet50_ijepacnn_linhead	.039
301	yudixie_resnet50_distance_reg_0_240908	.035
302	resnet50_barlowtwins_linhead	.034
303	yudixie_resnet18_rotation_reg_0_240719	.032
304	compact_resnet50_V4	.031
305	resnet50_vicreg_linhead	.030
306	deit_small_imagenet_1_seed-0	.029
307	yudixie_resnet50_random_0_240908	.029
308	mobilevit_small	.029
309	yudixie_resnet18_translation_rotation_0_240719	.028
310	resnet50_simclr_linhead_01norm	.028
311	yolos_tiny	.025
312	yudixie_resnet50_translation_rotation_0_240908	.024
313	yudixie_resnet18_random_0_240719	.023
314	hmax	.022
315	yudixie_wbh_object_class_scaling_0415_run_3	.022
316	compact_resnet50_robust_V4	.019
317	yudixie_wbh_object_class_scaling_0415_run_0	.017
318	yudixie_wbh_object_class_scaling_0415_run_2	.015
319	yudixie_resnet50_rotation_reg_0_240908	.013
320	resnet_50_v1_spiking_l3	.009
321	yudixie_resnet18_translation_reg_0_240719	.009
322	compact_vgg19_V4	.003
323	yudixie_resnet50_translation_reg_0_240908	.003
324	gabor_filter_entropy_4x4	.000
325	omnivore_swinB	.000
326	gabor_filter_entropy_4x4_v2_forcedCosine	.000
327	gabor_filter_entropy_4x4_v2	.000
328	omnivore_swinS	.000
329	convnext_xxlarge_clip
330	vit_large_clip336_openai
331	SimVP
332	antialiased-rnext101_32x8d
333	MIM
334	TAU
335	PredRNN
336	ConvLSTM

Benchmark bibtex

None

Ceiling

0.68.

Note that scores are relative to this ceiling.

Data: Hebart2023

Metric: match