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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	resnet50_st_wzc_seed3_2_323	.360
43	BiT-S-R101x1	.360
44	AdvProp_efficientnet-b4	.358
45	resnet50_st_wzc_2	.358
46	resnet50_st_wzc_seed6_2_323	.357
47	ReAlnet07	.355
48	resnet50_st_wzc_seed7_2_323	.354
49	resnet50_ewconplus_wzc_seed5_2__323	.353
50	resnet50_ewconplus_wzc_seed2_2__323	.350
51	efficientnet-b7	.349
52	AT_efficientnet-b2	.348
53	AdvProp_efficientnet-b2	.348
54	mobilenet_v2_1_0_160	.347
55	ReAlnet08	.346
56	resnet50_hvs_wzc	.345
57	resnet50_ewconplus_wzc	.343
58	voneresnet-50-non_stochastic	.337
59	effnetb1_272x240	.337
60	resnet50_robust_l2_eps3	.336
61	resnet50_ewconplus_wzc_seed6_2_323	.334
62	convnext_tiny:in12k_ft_in1k	.332
63	resnet50_robust_l2_eps1	.328
64	AdvProp_efficientnet-b8	.328
65	resnet50_ecoset_full	.327
66	BiT-S-R50x1	.327
67	efficientnet_b0_imagenet_full	.327
68	mobilenet_v2_0_75_224	.327
69	convnext_femto_ols:d1_in1k	.326
70	ReAlnet01_cornet_fov12	.325
71	convnext_large_imagenet_full_seed-0	.322
72	voneresnet-50-robust	.320
73	voneresnet-50	.320
74	resnet50_imagenet_full	.317
75	mobilenet_v2_1_0_192	.313
76	tv_efficientnet-b1	.312
77	vgg_19	.311
78	AdvProp_efficientnet-b6	.309
79	imagenet_l2_3_0	.308
80	yolos_tiny	.307
81	resnet50-barlow	.306
82	convnext_large:fb_in22k_ft_in1k	.305
83	resnet50-vicregl0p9	.301
84	convnext_base_imagenet_full_seed-0	.299
85	convnext_tiny_imagenet_full_seed-0	.295
86	convnext_small_imagenet_full_seed-0	.295
87	resnet50-SIN	.289
88	efficientnet_b0	.289
89	efficientnet_b1_imagenet_full	.289
90	vgg_16	.288
91	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.286
92	resnet152_ecoset_full	.282
93	deepeisnn_ei_imagenet_resnet18	.282
94	AdvProp_efficientnet-b7	.281
95	resnet50-vicregl0p75	.279
96	yudixie_resnet18_distance_reg_0_240719	.278
97	resnet101_ecoset_full	.277
98	resnet50_imagenet_100_seed-0	.277
99	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.277
100	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.275
101	resnet101_imagenet_full	.274
102	custom_model_cv_18_dagger_408	.274
103	densenet-121	.270
104	yudixie_resnet18_distance_translation_0_240719	.270
105	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.270
106	resnet50-vicreg	.269
107	Res2Net50_26w_4s	.267
108	ReAlnet01_cornet_fov16	.266
109	vit_large_patch14_clip_224:laion2b_ft_in1k	.266
110	mobilenet_v2_1_0_224	.265
111	resnet50-moclr8deg	.265
112	AlexNet_SIN	.265
113	cvt_cvt-21-384-in1k_4_LucyV4	.265
114	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.265
115	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.264
116	convnext_large_in22k_supervised	.264
117	yudixie_resnet18_translation_rotation_0_240719	.264
118	convnext_tiny_sup	.263
119	xception	.262
120	resnet-50-robust	.262
121	yudixie_resnet18_distance_rotation_0_240719	.262
122	mobilenet_v2_0_5_224	.262
123	vit_base_patch14_reg4_dinov2-lvd142m	.262
124	BiT-S-R50x3	.261
125	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.260
126	dinov2_vitl14_reg_lc_featread	.260
127	dinov2_vitl14_reg_lc	.260
128	efficientnet_b2_imagenet_full	.257
129	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
130	artResNet18_1	.256
131	vit_base_patch14_dinov2-lvd142m	.256
132	pnasnet_large_halfPrecision	.256
133	alexnet_ks_torevert	.255
134	alexnet	.255
135	resnet50-SIN_IN	.255
136	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.255
137	yudixie_resnet18_distance_translation_rotation_0_240719	.254
138	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.254
139	convnext_base:clip_laiona_augreg_ft_in1k_384	.253
140	yudixie_resnet50_distance_rotation_0_240908	.253
141	vit_large_patch14_clip_224:openai_ft_in1k	.251
142	vit_base_patch16_dinov3-lvd1689m	.251
143	convnext_xlarge:fb_in22k_ft_in1k	.250
144	deit3_base_patch16_224_fb_in1k	.250
145	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.250
146	nasnet_mobile	.248
147	vit_base_patch16_clip_224:openai_ft_in1k	.247
148	yudixie_resnet18_translation_reg_0_240719	.247
149	resnet152_imagenet_full	.247
150	cv_18_dagger_408_pretrained	.246
151	convnext_small_imagenet_100_seed-0	.244
152	blt_vs	.244
153	resnet_50_v1_spiking	.243
154	resnet50-sup	.243
155	resnet_50_v1	.243
156	antialiased-r50	.242
157	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.241
158	vit_relpos_base_patch16_clsgap_224:sw_in1k	.240
159	resnet50-SIN_IN_IN	.239
160	cvt_cvt-13-384-in1k_4_LucyV4	.238
161	inception_v3	.237
162	yudixie_wbh_object_class_scaling_0415_imagenet	.236
163	yudixie_resnet18_imagenet1kpret_0_240719	.236
164	deit_base_imagenet_full_seed-0	.236
165	deepeisnn_ei_cifar10_vgg19	.235
166	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.234
167	deit_large_imagenet_full_seed-0	.234
168	cvt_cvt-13-224-in1k_4_LucyV4	.233
169	inception_v1	.232
170	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.230
171	omnivore_swinS	.230
172	resnet50-vitoimagevidnet8	.229
173	resnet50-VITO-8deg-cc	.229
174	resnet_101_v2	.228
175	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.227
176	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.227
177	dinov2_vitl14_lc	.225
178	resnext101_32x32d_wsl	.224
179	resnext101_32x48d_wsl	.223
180	yudixie_resnet50_translation_rotation_0_240908	.223
181	densenet-201	.223
182	deit_small_imagenet_full_seed-0	.222
183	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.220
184	vit_huge_clip336_laion	.215
185	yudixie_resnet18_category_class_0_240719	.215
186	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
187	densenet-169	.212
188	dinov2_vitg14_reg_lc	.211
189	resnet_50_v1_spiking_l4a	.210
190	resnet_50_v1_spiking_l4	.210
191	yudixie_resnet50_imagenet1kpret_0_240908	.210
192	resnet50_tutorial	.210
193	mobilenet_v2_1_4_224	.210
194	mobilenet_v2_1-4_224_pytorch	.209
195	dinov2_vitl14_lc_res336	.206
196	omnivore_swinB	.205
197	ReAlnet01_cornet_fov4	.204
198	yudixie_resnet18_object_class_0_240719	.203
199	vit_large_patch14_clip_336:laion2b_ft_in1k	.201
200	convnext_large_clip_laion2b_finelayers	.198
201	pr1_stl10_disentangled_alpha04	.198
202	BiT-S-R101x3	.198
203	focalnet_tiny_lrf_in1k	.193
204	deepeisnn_ei_cifar10_resnet18	.192
205	yudixie_resnet18_rotation_reg_0_240719	.188
206	cvt_cvt-21-224-in1k_4_LucyV4	.188
207	convnext_xxlarge_clip	.188
208	vit_large_clip336_openai	.185
209	convnext_base_fb_in1k_gram_aligned_dinov3	.184
210	predictive_coding_pc	.184
211	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.181
212	yudixie_resnet50_distance_translation_0_240908	.180
213	dinov2_vitg14_lc	.175
214	yudixie_resnet50_rotation_reg_0_240908	.173
215	resnet_50_v2	.165
216	BiT-S-R152x2	.163
217	alexnet_fov4	.161
218	yudixie_resnet50_category_class_0_240908	.157
219	deit_small_imagenet_100_seed-0	.157
220	eva02_large_in22k	.153
221	yudixie_wbh_object_class_scaling_0415_run_1	.148
222	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.146
223	resnext101_32x8d_wsl	.145
224	resnet18_fair	.140
225	yudixie_resnet50_object_class_0_240908	.139
226	briaai_rmbg_1_4	.139
227	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.139
228	yudixie_resnet50_distance_translation_rotation_0_240908	.135
229	yudixie_resnet50_translation_reg_0_240908	.129
230	alexnet_fov16	.127
231	ViT_L_32_imagenet1k	.125
232	alexnet_fov12	.125
233	AlexNet_SIN_fov16	.120
234	resnet50_imagenet_10_seed-0	.118
235	convnext_small_imagenet_10_seed-0	.117
236	AlexNet_SIN_fov12	.113
237	yudixie_wbh_object_class_scaling_0415_run_2	.109
238	resnet_50_v1_spiking_l3	.108
239	convnext_base_fb_in22k_ft_in1k	.106
240	resnet50_primary_visual_cortex	.103
241	resnet-152_v2_pytorch	.097
242	deit_small_imagenet_10_seed-0	.095
243	compact_resnet50_robust_IT	.090
244	compact_resnet50_IT	.086
245	yudixie_resnet50_distance_reg_0_240908	.083
246	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.079
247	deit3_base_patch16_224_fb_in22k_ft_in1k	.079
248	convnext_base_fb_in1k	.079
249	deit_small_imagenet_1_seed-0	.068
250	alexnet_training_seed_01_fov16	.064
251	yudixie_wbh_object_class_scaling_0415_run_0	.062
252	alexnet_training_seed_02	.060
253	alexnet_training_seed_01_fov12	.060
254	compact_cornets_IT	.060
255	compact_vgg19_V4	.060
256	aughost_fair_resnet18	.059
257	resnet50_imagenet_1_seed-0	.059
258	alexnet_training_seed_04	.059
259	compact_vgg19_IT	.058
260	alexnet_training_seed_03	.056
261	compact_resnet50_robust_V4	.056
262	convnext_small_imagenet_1_seed-0	.055
263	yudixie_wbh_object_class_scaling_0415_run_3	.053
264	alexnet_training_seed_09	.048
265	alexnet_training_seed_01	.048
266	alexnet_training_seed_05	.046
267	alexnet_training_seed_10	.042
268	alexnet_training_seed_07	.039
269	alexnet_training_seed_06	.039
270	alexnet_training_seed_08	.033
271	yudixie_resnet50_random_0_240908	.029
272	yudixie_resnet18_random_0_240719	.027
273	AlexNet_SIN_fov4	.019
274	compact_resnet50_V4	.005
275	hmax	.000
276	compact_cornets_V4	.000
277	alexnet_training_seed_01_fov4	.000
278	pnasnet_large
279	BiT-S-R152x4
280	resnet_SIN_IN_FT_IN
281	vonegrcnn_52e_full
282	vonegrcnn_47e
283	pnasnet_large_pytorch
284	densenet_201_pytorch
285	inception_v3_pytorch
286	MIM
287	resnet50_eMMCR_Vanilla
288	TAU
289	PredRNN
290	SimVP
291	ConvLSTM
292	bp_resnet50_julios
293	regnet_y_400mf
294	antialiased-rnext101_32x8d
295	antialias-resnet152
296	resnet_152_v1
297	resnet_101_v1
298	resnet_152_v2
299	nasnet_large
300	inception_v4
301	grcnn_109
302	vonegrcnn_62e_nobn
303	grcnn
304	resnext101_32x16d_wsl

Benchmark bibtex

None

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: Bracci2019.anteriorVTC

Metric: rdm