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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	resnet50-moclr8deg	.534
3	resnet50_robust_l2_eps1	.503
4	vonegrcnn_47e	.498
5	vonegrcnn_62e_nobn	.494
6	vonegrcnn_52e_full	.490
7	resnet_SIN_IN_FT_IN	.489
8	resnet50_tutorial	.488
9	resnet50-VITO-8deg-cc	.483
10	resnet50-vitoimagevidnet8	.483
11	densenet_201_pytorch	.476
12	imagenet_l2_3_0	.476
13	resnet50_robust_l2_eps3	.476
14	resnet18_imagenet21kP	.470
15	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.469
16	antialias-resnet152	.464
17	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.463
18	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.416
19	resnet_50_v2	.408
20	vgg_16	.407
21	resnext101_32x8d_wsl	.407
22	vgg_19	.404
23	efficientnet_b0_imagenet_full	.399
24	efficientnet_b1_imagenet_full	.396
25	efficientnet_b2_imagenet_full	.396
26	resnext101_32x16d_wsl	.387
27	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.381
28	shufflenet_v2_x1_0	.379
29	resnet-152_v2_pytorch	.375
30	alexnet_ks_torevert	.375
31	voneresnet-50-robust	.372
32	custom_model_cv_18_dagger_408	.371
33	voneresnet-50-non_stochastic	.368
34	ReAlnet09	.364
35	ReAlnet09_cornet	.364
36	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.363
37	grcnn	.361
38	resnet18_imagenet_full	.358
39	resnet34_imagenet_full	.358
40	ReAlnet04	.358
41	ReAlnet04_cornet	.358
42	voneresnet-50	.357
43	grcnn_109	.356
44	Res2Net50_26w_4s	.354
45	ReAlnet05	.354
46	ReAlnet05_cornet	.354
47	resnet50-vicregl0p9	.352
48	resnet-50-robust	.352
49	pnasnet_large_pytorch	.351
50	ReAlnet06	.350
51	ReAlnet06_cornet	.350
52	ReAlnet03_cornet	.349
53	ReAlnet03	.349
54	ReAlnet07	.347
55	ReAlnet07_cornet	.347
56	ReAlnet01_cornet	.347
57	ReAlnet01	.347
58	ReAlnet02_cornet	.346
59	ReAlnet02	.346
60	resnet50-vicregl0p75	.345
61	convnext_tiny_sup	.344
62	efficientnet_b0	.342
63	ReAlnet08	.342
64	ReAlnet08_cornet	.342
65	ReAlnet10_ALL	.341
66	ReAlnet10	.338
67	ReAlnet10_cornet	.338
68	resnet18_ecoset_full	.336
69	convnext_large:fb_in22k_ft_in1k	.336
70	ReAlnet08_ALL	.335
71	ReAlnet07_ALL	.333
72	resnet_101_v2	.333
73	ReAlnet03_ALL	.332
74	mobilenet_v2_1_0_224	.330
75	mobilenet_v2_1_4_224	.330
76	mobilenet_v2_1-4_224_pytorch	.330
77	resnet50-SIN_IN	.329
78	ReAlnet05_ALL	.329
79	ReAlnet02_ALL	.328
80	ReAlnet04_ALL	.327
81	ReAlnet01_ALL	.327
82	ReAlnet06_ALL	.326
83	resnet_152_v2	.326
84	focalnet_tiny_lrf_in1k	.326
85	resnext101_32x32d_wsl	.325
86	regnet_y_400mf	.322
87	ReAlnet09_ALL	.320
88	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.320
89	convnext_xlarge:fb_in22k_ft_in1k	.319
90	resnet50_imagenet_full	.318
91	resnet34_ecoset_full	.317
92	resnet101_imagenet_full	.316
93	resnet50-barlow	.313
94	resnet50-vicreg	.311
95	resnet152_imagenet_full	.308
96	resnet_152_v1	.307
97	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.304
98	resnet_101_v1	.297
99	VOneCORnet-S	.296
100	densenet-121	.291
101	inception_v3_pytorch	.291
102	antialiased-r50	.290
103	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.289
104	resnet_50_v1	.288
105	resnet50-sup	.288
106	densenet-201	.286
107	BiT-S-R50x1	.286
108	AlexNet_SIN	.281
109	resnet50_imagenet_100_seed-0	.279
110	resnext101_32x48d_wsl	.278
111	resnet-18_test_m	.273
112	resnet50-SIN_IN_IN	.272
113	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
114	yudixie_resnet50_imagenet1kpret_0_240908	.271
115	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.270
116	resnet50_ecoset_full	.266
117	convnext_tiny:in12k_ft_in1k	.265
118	AdvProp_efficientnet-b2	.265
119	AT_efficientnet-b2	.265
120	deit_large_imagenet_full_seed-0	.263
121	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.260
122	yudixie_resnet18_imagenet1kpret_0_240719	.258
123	convnext_base:clip_laiona_augreg_ft_in1k_384	.257
124	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
125	BiT-S-R101x1	.255
126	resnet50-SIN	.254
127	BiT-S-R50x3	.254
128	BiT-S-R152x2	.254
129	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.253
130	resnet101_ecoset_full	.253
131	densenet-169	.250
132	deit_small_imagenet_100_seed-0	.247
133	BiT-S-R101x3	.244
134	effnetb1_272x240	.242
135	convnext_femto_ols:d1_in1k	.242
136	cvt_cvt-21-224-in1k_4_LucyV4	.238
137	resnet152_ecoset_full	.238
138	convnext_small_imagenet_full_seed-0	.238
139	deit_base_imagenet_full_seed-0	.238
140	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.237
141	resnet50_eMMCR_Vanilla	.233
142	AdvProp_efficientnet-b4	.228
143	inception_v1	.224
144	convnext_tiny_imagenet_full_seed-0	.220
145	cvt_cvt-21-384-in1k_4_LucyV4	.219
146	cvt_cvt-13-224-in1k_4_LucyV4	.217
147	resnet_50_v1_spiking	.210
148	convnext_base_imagenet_full_seed-0	.209
149	deit_small_imagenet_full_seed-0	.207
150	resnet50_imagenet_10_seed-0	.206
151	vit_relpos_base_patch16_clsgap_224:sw_in1k	.203
152	vit_large_patch14_clip_224:laion2b_ft_in1k	.202
153	vit_large_patch14_clip_336:laion2b_ft_in1k	.200
154	vit_base_patch16_clip_224:openai_ft_in1k	.199
155	cvt_cvt-13-384-in1k_4_LucyV4	.198
156	convnext_small_imagenet_100_seed-0	.191
157	nasnet_mobile	.191
158	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.188
159	AdvProp_efficientnet-b6	.185
160	efficientnet-b7	.176
161	xception	.175
162	artResNet18_1	.173
163	tv_efficientnet-b1	.169
164	convnext_large_imagenet_full_seed-0	.166
165	vit_large_patch14_clip_224:openai_ft_in1k	.157
166	resnet_50_v1_spiking_l4a	.155
167	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.153
168	pnasnet_large	.150
169	AdvProp_efficientnet-b7	.142
170	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.139
171	deit_small_imagenet_10_seed-0	.133
172	AdvProp_efficientnet-b8	.132
173	resnet_50_v1_spiking_l4	.130
174	mobilenet_v2_0_5_192	.129
175	inception_v3	.117
176	mobilenet_v2_0_5_224	.117
177	resnet50_imagenet_1_seed-0	.116
178	mobilenet_v2_0_75_160	.115
179	convnext_small_imagenet_10_seed-0	.114
180	nasnet_large	.113
181	inception_v4	.110
182	resnet50_primary_visual_cortex	.105
183	mobilenet_v2_1_0_128	.105
184	mobilenet_v2_0_75_192	.103
185	mobilenet_v2_0_75_224	.099
186	yudixie_resnet50_category_class_0_240908	.097
187	mobilenet_v2_1_0_160	.089
188	yudixie_resnet18_object_class_0_240719	.089
189	yudixie_resnet50_object_class_0_240908	.088
190	blt_vs	.086
191	mobilenet_v2_1_0_192	.085
192	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.083
193	convnext_small_imagenet_1_seed-0	.083
194	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.080
195	yudixie_resnet18_category_class_0_240719	.071
196	yudixie_resnet18_distance_reg_0_240719	.070
197	mobilenet_v2_1_3_224	.070
198	BiT-S-R152x4	.059
199	yudixie_resnet18_distance_translation_rotation_0_240719	.056
200	yudixie_resnet18_distance_rotation_0_240719	.055
201	alexnet_training_seed_09	.053
202	ViT_L_32_imagenet1k	.052
203	alexnet_training_seed_08	.051
204	alexnet_training_seed_10	.051
205	alexnet_training_seed_05	.051
206	alexnet_training_seed_01	.048
207	alexnet_training_seed_03	.048
208	yudixie_resnet50_distance_rotation_0_240908	.047
209	alexnet_training_seed_02	.047
210	yudixie_resnet18_distance_translation_0_240719	.046
211	alexnet_training_seed_04	.045
212	briaai_rmbg_1_4	.045
213	alexnet_training_seed_07	.045
214	alexnet_training_seed_06	.041
215	yudixie_resnet50_distance_translation_rotation_0_240908	.040
216	yudixie_resnet50_distance_translation_0_240908	.040
217	yudixie_resnet50_distance_reg_0_240908	.035
218	yudixie_resnet18_rotation_reg_0_240719	.032
219	deit_small_imagenet_1_seed-0	.029
220	yudixie_resnet50_random_0_240908	.029
221	mobilevit_small	.029
222	yudixie_resnet18_translation_rotation_0_240719	.028
223	yolos_tiny	.025
224	yudixie_resnet50_translation_rotation_0_240908	.024
225	yudixie_resnet18_random_0_240719	.023
226	hmax	.022
227	yudixie_resnet50_rotation_reg_0_240908	.013
228	resnet_50_v1_spiking_l3	.009
229	yudixie_resnet18_translation_reg_0_240719	.009
230	yudixie_resnet50_translation_reg_0_240908	.003
231	omnivore_swinB	.000
232	omnivore_swinS	.000
233	ConvLSTM
234	PredRNN
235	TAU
236	MIM
237	antialiased-rnext101_32x8d
238	SimVP

Benchmark bibtex

None

Ceiling

0.68.

Note that scores are relative to this ceiling.

Data: Hebart2023

Metric: match