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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	.375
31	alexnet_ks_torevert	.375
32	voneresnet-50-robust	.372
33	custom_model_cv_18_dagger_408	.371
34	voneresnet-50-non_stochastic	.368
35	ReAlnet09	.364
36	ReAlnet09_cornet	.364
37	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.363
38	grcnn	.361
39	resnet18_imagenet_full	.358
40	resnet34_imagenet_full	.358
41	ReAlnet04	.358
42	ReAlnet04_cornet	.358
43	ReAlnet01_cornet_fov12	.357
44	voneresnet-50	.357
45	grcnn_109	.356
46	Res2Net50_26w_4s	.354
47	ReAlnet05	.354
48	ReAlnet05_cornet	.354
49	resnet50-vicregl0p9	.352
50	resnet-50-robust	.352
51	pnasnet_large_pytorch	.351
52	ReAlnet06	.350
53	ReAlnet06_cornet	.350
54	ReAlnet03_cornet	.349
55	ReAlnet03	.349
56	ReAlnet07	.347
57	ReAlnet07_cornet	.347
58	ReAlnet01_cornet	.347
59	ReAlnet01	.347
60	ReAlnet01_cornet_fov16	.346
61	ReAlnet02_cornet	.346
62	ReAlnet02	.346
63	resnet50-vicregl0p75	.345
64	convnext_tiny_sup	.344
65	efficientnet_b0	.342
66	ReAlnet08	.342
67	ReAlnet08_cornet	.342
68	ReAlnet10_ALL	.341
69	ReAlnet10	.338
70	ReAlnet10_cornet	.338
71	alexnet_fov4	.336
72	resnet18_ecoset_full	.336
73	convnext_large:fb_in22k_ft_in1k	.336
74	ReAlnet08_ALL	.335
75	ReAlnet07_ALL	.333
76	resnet_101_v2	.333
77	resnet50_ewconplus_wzc	.332
78	ReAlnet03_ALL	.332
79	mobilenet_v2_1_0_224	.330
80	mobilenet_v2_1_4_224	.330
81	mobilenet_v2_1-4_224_pytorch	.330
82	resnet50-SIN_IN	.329
83	ReAlnet05_ALL	.329
84	ReAlnet02_ALL	.328
85	ReAlnet04_ALL	.327
86	ReAlnet01_ALL	.327
87	ReAlnet06_ALL	.326
88	resnet_152_v2	.326
89	focalnet_tiny_lrf_in1k	.326
90	resnext101_32x32d_wsl	.325
91	regnet_y_400mf	.322
92	ReAlnet09_ALL	.320
93	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.320
94	convnext_xlarge:fb_in22k_ft_in1k	.319
95	alexnet_fov12	.319
96	resnet50_imagenet_full	.318
97	resnet34_ecoset_full	.317
98	resnet101_imagenet_full	.316
99	resnet50-barlow	.313
100	resnet50-vicreg	.311
101	resnet152_imagenet_full	.308
102	resnet_152_v1	.307
103	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.304
104	resnet_101_v1	.297
105	VOneCORnet-S	.296
106	densenet-121	.291
107	inception_v3_pytorch	.291
108	antialiased-r50	.290
109	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.289
110	alexnet_fov16	.289
111	resnet_50_v1	.288
112	resnet50-sup	.288
113	densenet-201	.286
114	BiT-S-R50x1	.286
115	AlexNet_SIN	.281
116	resnet50_imagenet_100_seed-0	.279
117	resnext101_32x48d_wsl	.278
118	resnet-18_test_m	.273
119	resnet50-SIN_IN_IN	.272
120	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.271
121	yudixie_resnet50_imagenet1kpret_0_240908	.271
122	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.270
123	ReAlnet01_cornet_fov4	.268
124	resnet50_ecoset_full	.266
125	convnext_tiny:in12k_ft_in1k	.265
126	AdvProp_efficientnet-b2	.265
127	AT_efficientnet-b2	.265
128	deit_large_imagenet_full_seed-0	.263
129	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.260
130	yudixie_resnet18_imagenet1kpret_0_240719	.258
131	convnext_base:clip_laiona_augreg_ft_in1k_384	.257
132	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
133	BiT-S-R101x1	.255
134	resnet50-SIN	.254
135	BiT-S-R50x3	.254
136	BiT-S-R152x2	.254
137	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.253
138	resnet101_ecoset_full	.253
139	densenet-169	.250
140	deit_small_imagenet_100_seed-0	.247
141	BiT-S-R101x3	.244
142	effnetb1_272x240	.242
143	convnext_femto_ols:d1_in1k	.242
144	cvt_cvt-21-224-in1k_4_LucyV4	.238
145	resnet152_ecoset_full	.238
146	convnext_small_imagenet_full_seed-0	.238
147	deit_base_imagenet_full_seed-0	.238
148	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.237
149	resnet50_eMMCR_Vanilla	.233
150	AlexNet_SIN_fov12	.232
151	AdvProp_efficientnet-b4	.228
152	inception_v1	.224
153	AlexNet_SIN_fov4	.221
154	convnext_tiny_imagenet_full_seed-0	.220
155	cvt_cvt-21-384-in1k_4_LucyV4	.219
156	cvt_cvt-13-224-in1k_4_LucyV4	.217
157	AlexNet_SIN_fov16	.215
158	resnet_50_v1_spiking	.210
159	convnext_base_imagenet_full_seed-0	.209
160	deit_small_imagenet_full_seed-0	.207
161	resnet50_imagenet_10_seed-0	.206
162	vit_relpos_base_patch16_clsgap_224:sw_in1k	.203
163	vit_large_patch14_clip_224:laion2b_ft_in1k	.202
164	vit_large_patch14_clip_336:laion2b_ft_in1k	.200
165	vit_base_patch16_clip_224:openai_ft_in1k	.199
166	cvt_cvt-13-384-in1k_4_LucyV4	.198
167	convnext_small_imagenet_100_seed-0	.191
168	nasnet_mobile	.191
169	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.188
170	AdvProp_efficientnet-b6	.185
171	efficientnet-b7	.176
172	xception	.175
173	artResNet18_1	.173
174	tv_efficientnet-b1	.169
175	convnext_large_imagenet_full_seed-0	.166
176	vit_large_patch14_clip_224:openai_ft_in1k	.157
177	resnet_50_v1_spiking_l4a	.155
178	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.153
179	pnasnet_large	.150
180	AdvProp_efficientnet-b7	.142
181	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.139
182	deit_small_imagenet_10_seed-0	.133
183	AdvProp_efficientnet-b8	.132
184	resnet_50_v1_spiking_l4	.130
185	mobilenet_v2_0_5_192	.129
186	inception_v3	.117
187	mobilenet_v2_0_5_224	.117
188	resnet50_imagenet_1_seed-0	.116
189	mobilenet_v2_0_75_160	.115
190	convnext_small_imagenet_10_seed-0	.114
191	nasnet_large	.113
192	inception_v4	.110
193	resnet50_primary_visual_cortex	.105
194	mobilenet_v2_1_0_128	.105
195	mobilenet_v2_0_75_192	.103
196	mobilenet_v2_0_75_224	.099
197	yudixie_resnet50_category_class_0_240908	.097
198	mobilenet_v2_1_0_160	.089
199	yudixie_resnet18_object_class_0_240719	.089
200	yudixie_resnet50_object_class_0_240908	.088
201	blt_vs	.086
202	mobilenet_v2_1_0_192	.085
203	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.083
204	convnext_small_imagenet_1_seed-0	.083
205	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.080
206	cv_18_dagger_408_pretrained	.077
207	compact_resnet50_IT	.072
208	yudixie_resnet18_category_class_0_240719	.071
209	yudixie_resnet18_distance_reg_0_240719	.070
210	mobilenet_v2_1_3_224	.070
211	BiT-S-R152x4	.059
212	yudixie_resnet18_distance_translation_rotation_0_240719	.056
213	yudixie_resnet18_distance_rotation_0_240719	.055
214	alexnet_training_seed_09	.053
215	compact_vgg19_IT	.053
216	ViT_L_32_imagenet1k	.052
217	alexnet_training_seed_08	.051
218	alexnet_training_seed_10	.051
219	alexnet_training_seed_05	.051
220	compact_resnet50_robust_IT	.049
221	alexnet_training_seed_01	.048
222	alexnet_training_seed_01_fov12	.048
223	alexnet_training_seed_03	.048
224	yudixie_resnet50_distance_rotation_0_240908	.047
225	alexnet_training_seed_02	.047
226	alexnet_training_seed_01_fov16	.046
227	yudixie_resnet18_distance_translation_0_240719	.046
228	alexnet_training_seed_04	.045
229	briaai_rmbg_1_4	.045
230	alexnet_training_seed_07	.045
231	alexnet_training_seed_01_fov4	.044
232	compact_cornets_V4	.042
233	alexnet_training_seed_06	.041
234	compact_cornets_IT	.041
235	yudixie_resnet50_distance_translation_rotation_0_240908	.040
236	yudixie_resnet50_distance_translation_0_240908	.040
237	yudixie_resnet50_distance_reg_0_240908	.035
238	yudixie_resnet18_rotation_reg_0_240719	.032
239	compact_resnet50_V4	.031
240	deit_small_imagenet_1_seed-0	.029
241	yudixie_resnet50_random_0_240908	.029
242	mobilevit_small	.029
243	yudixie_resnet18_translation_rotation_0_240719	.028
244	yolos_tiny	.025
245	yudixie_resnet50_translation_rotation_0_240908	.024
246	yudixie_resnet18_random_0_240719	.023
247	hmax	.022
248	compact_resnet50_robust_V4	.019
249	yudixie_resnet50_rotation_reg_0_240908	.013
250	resnet_50_v1_spiking_l3	.009
251	yudixie_resnet18_translation_reg_0_240719	.009
252	compact_vgg19_V4	.003
253	yudixie_resnet50_translation_reg_0_240908	.003
254	omnivore_swinB	.000
255	omnivore_swinS	.000
256	ConvLSTM
257	PredRNN
258	TAU
259	MIM
260	antialiased-rnext101_32x8d
261	SimVP

Benchmark bibtex

None

Ceiling

0.68.

Note that scores are relative to this ceiling.

Data: Hebart2023

Metric: match