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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Bracci2019.anteriorVTC-rdm")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet34_imagenet_full	.411
2	mobilenet_v2_1_0_128	.402
3	ReAlnet04_cornet	.395
4	ReAlnet05_cornet	.392
5	ReAlnet01_cornet	.391
6	ReAlnet06_cornet	.391
7	ReAlnet03_cornet	.390
8	ReAlnet07_cornet	.389
9	resnet34_ecoset_full	.389
10	ReAlnet05	.388
11	ReAlnet03	.387
12	ReAlnet06_ALL	.387
13	ReAlnet03_ALL	.387
14	shufflenet_v2_x1_0	.385
15	ReAlnet10_cornet	.384
16	ReAlnet09_cornet	.383
17	ReAlnet01	.383
18	resnet18_imagenet21kP	.382
19	ReAlnet02_ALL	.382
20	ReAlnet04	.382
21	ReAlnet05_ALL	.382
22	resnet18_ecoset_full	.381
23	ReAlnet01_ALL	.380
24	ReAlnet04_ALL	.380
25	ReAlnet08_cornet	.378
26	mobilenet_v2_0_5_192	.378
27	ReAlnet10_ALL	.377
28	ReAlnet09	.377
29	ReAlnet02	.373
30	ReAlnet08_ALL	.373
31	ReAlnet06	.373
32	ReAlnet09_ALL	.373
33	ReAlnet07_ALL	.373
34	ReAlnet02_cornet	.371
35	VOneCORnet-S	.371
36	mobilenet_v2_0_75_160	.370
37	mobilenet_v2_1_3_224	.368
38	ReAlnet10	.368
39	resnet18_imagenet_full	.367
40	resnet-18_test_m	.366
41	mobilenet_v2_0_75_192	.365
42	BiT-S-R101x1	.360
43	AdvProp_efficientnet-b4	.358
44	ReAlnet07	.355
45	efficientnet-b7	.349
46	AdvProp_efficientnet-b2	.348
47	AT_efficientnet-b2	.348
48	mobilenet_v2_1_0_160	.347
49	ReAlnet08	.346
50	voneresnet-50-non_stochastic	.337
51	effnetb1_272x240	.337
52	resnet50_robust_l2_eps3	.336
53	convnext_tiny:in12k_ft_in1k	.332
54	resnet50_robust_l2_eps1	.328
55	AdvProp_efficientnet-b8	.328
56	resnet50_ecoset_full	.327
57	BiT-S-R50x1	.327
58	efficientnet_b0_imagenet_full	.327
59	mobilenet_v2_0_75_224	.327
60	convnext_femto_ols:d1_in1k	.326
61	convnext_large_imagenet_full_seed-0	.322
62	voneresnet-50-robust	.320
63	voneresnet-50	.320
64	resnet50_imagenet_full	.317
65	mobilenet_v2_1_0_192	.313
66	tv_efficientnet-b1	.312
67	vgg_19	.311
68	AdvProp_efficientnet-b6	.309
69	imagenet_l2_3_0	.308
70	yolos_tiny	.307
71	resnet50-barlow	.306
72	convnext_large:fb_in22k_ft_in1k	.305
73	resnet50-vicregl0p9	.301
74	convnext_base_imagenet_full_seed-0	.299
75	convnext_tiny_imagenet_full_seed-0	.295
76	convnext_small_imagenet_full_seed-0	.295
77	resnet50-SIN	.289
78	efficientnet_b0	.289
79	efficientnet_b1_imagenet_full	.289
80	vgg_16	.288
81	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.286
82	resnet152_ecoset_full	.282
83	AdvProp_efficientnet-b7	.281
84	resnet50-vicregl0p75	.279
85	yudixie_resnet18_distance_reg_0_240719	.278
86	resnet101_ecoset_full	.277
87	resnet50_imagenet_100_seed-0	.277
88	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.277
89	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.275
90	resnet101_imagenet_full	.274
91	custom_model_cv_18_dagger_408	.274
92	densenet-121	.270
93	yudixie_resnet18_distance_translation_0_240719	.270
94	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.270
95	resnet50-vicreg	.269
96	Res2Net50_26w_4s	.267
97	vit_large_patch14_clip_224:laion2b_ft_in1k	.266
98	mobilenet_v2_1_0_224	.265
99	resnet50-moclr8deg	.265
100	AlexNet_SIN	.265
101	cvt_cvt-21-384-in1k_4_LucyV4	.265
102	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.265
103	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.264
104	yudixie_resnet18_translation_rotation_0_240719	.264
105	convnext_tiny_sup	.263
106	xception	.262
107	resnet-50-robust	.262
108	yudixie_resnet18_distance_rotation_0_240719	.262
109	mobilenet_v2_0_5_224	.262
110	BiT-S-R50x3	.261
111	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.260
112	efficientnet_b2_imagenet_full	.257
113	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
114	artResNet18_1	.256
115	alexnet_ks_torevert	.255
116	resnet50-SIN_IN	.255
117	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.255
118	yudixie_resnet18_distance_translation_rotation_0_240719	.254
119	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.254
120	convnext_base:clip_laiona_augreg_ft_in1k_384	.253
121	yudixie_resnet50_distance_rotation_0_240908	.253
122	vit_large_patch14_clip_224:openai_ft_in1k	.251
123	convnext_xlarge:fb_in22k_ft_in1k	.250
124	nasnet_mobile	.248
125	vit_base_patch16_clip_224:openai_ft_in1k	.247
126	yudixie_resnet18_translation_reg_0_240719	.247
127	resnet152_imagenet_full	.247
128	convnext_small_imagenet_100_seed-0	.244
129	blt_vs	.244
130	resnet_50_v1_spiking	.243
131	resnet_50_v1	.243
132	resnet50-sup	.243
133	antialiased-r50	.242
134	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.241
135	vit_relpos_base_patch16_clsgap_224:sw_in1k	.240
136	resnet50-SIN_IN_IN	.239
137	cvt_cvt-13-384-in1k_4_LucyV4	.238
138	inception_v3	.237
139	yudixie_resnet18_imagenet1kpret_0_240719	.236
140	deit_base_imagenet_full_seed-0	.236
141	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.234
142	deit_large_imagenet_full_seed-0	.234
143	cvt_cvt-13-224-in1k_4_LucyV4	.233
144	inception_v1	.232
145	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.230
146	omnivore_swinS	.230
147	resnet50-VITO-8deg-cc	.229
148	resnet50-vitoimagevidnet8	.229
149	resnet_101_v2	.228
150	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.227
151	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.227
152	resnext101_32x32d_wsl	.224
153	resnext101_32x48d_wsl	.223
154	yudixie_resnet50_translation_rotation_0_240908	.223
155	densenet-201	.223
156	deit_small_imagenet_full_seed-0	.222
157	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.220
158	yudixie_resnet18_category_class_0_240719	.215
159	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
160	densenet-169	.212
161	resnet_50_v1_spiking_l4	.210
162	yudixie_resnet50_imagenet1kpret_0_240908	.210
163	resnet_50_v1_spiking_l4a	.210
164	resnet50_tutorial	.210
165	mobilenet_v2_1_4_224	.210
166	mobilenet_v2_1-4_224_pytorch	.209
167	omnivore_swinB	.205
168	yudixie_resnet18_object_class_0_240719	.203
169	vit_large_patch14_clip_336:laion2b_ft_in1k	.201
170	BiT-S-R101x3	.198
171	focalnet_tiny_lrf_in1k	.193
172	yudixie_resnet18_rotation_reg_0_240719	.188
173	cvt_cvt-21-224-in1k_4_LucyV4	.188
174	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.181
175	yudixie_resnet50_distance_translation_0_240908	.180
176	yudixie_resnet50_rotation_reg_0_240908	.173
177	resnet_50_v2	.165
178	BiT-S-R152x2	.163
179	yudixie_resnet50_category_class_0_240908	.157
180	deit_small_imagenet_100_seed-0	.157
181	resnext101_32x8d_wsl	.145
182	yudixie_resnet50_object_class_0_240908	.139
183	briaai_rmbg_1_4	.139
184	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.139
185	yudixie_resnet50_distance_translation_rotation_0_240908	.135
186	yudixie_resnet50_translation_reg_0_240908	.129
187	ViT_L_32_imagenet1k	.125
188	resnet50_imagenet_10_seed-0	.118
189	convnext_small_imagenet_10_seed-0	.117
190	resnet_50_v1_spiking_l3	.108
191	resnet50_primary_visual_cortex	.103
192	resnet-152_v2_pytorch	.097
193	deit_small_imagenet_10_seed-0	.095
194	yudixie_resnet50_distance_reg_0_240908	.083
195	deit_small_imagenet_1_seed-0	.068
196	alexnet_training_seed_02	.060
197	resnet50_imagenet_1_seed-0	.059
198	alexnet_training_seed_04	.059
199	alexnet_training_seed_03	.056
200	convnext_small_imagenet_1_seed-0	.055
201	alexnet_training_seed_09	.048
202	alexnet_training_seed_01	.048
203	alexnet_training_seed_05	.046
204	alexnet_training_seed_10	.042
205	alexnet_training_seed_07	.039
206	alexnet_training_seed_06	.039
207	alexnet_training_seed_08	.033
208	yudixie_resnet50_random_0_240908	.029
209	yudixie_resnet18_random_0_240719	.027
210	hmax	-0.007
211	resnet_152_v1
212	resnext101_32x16d_wsl
213	antialias-resnet152
214	antialiased-rnext101_32x8d
215	regnet_y_400mf
216	bp_resnet50_julios
217	ConvLSTM
218	SimVP
219	PredRNN
220	TAU
221	resnet50_eMMCR_Vanilla
222	MIM
223	inception_v3_pytorch
224	densenet_201_pytorch
225	pnasnet_large_pytorch
226	inception_v4
227	nasnet_large
228	pnasnet_large
229	grcnn
230	vonegrcnn_62e_nobn
231	grcnn_109
232	vonegrcnn_47e
233	vonegrcnn_52e_full
234	resnet_SIN_IN_FT_IN
235	BiT-S-R152x4
236	resnet_152_v2
237	resnet_101_v1

Benchmark bibtex

None

Ceiling

Not available

Data: Bracci2019.anteriorVTC

Metric: rdm