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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	eicircuit_resnet18_bn_20260919	.352
51	resnet50_ewconplus_wzc_seed2_2__323	.350
52	efficientnet-b7	.349
53	AT_efficientnet-b2	.348
54	AdvProp_efficientnet-b2	.348
55	mobilenet_v2_1_0_160	.347
56	ReAlnet08	.346
57	resnet50_hvs_wzc	.345
58	resnet50_ewconplus_wzc	.343
59	voneresnet-50-non_stochastic	.337
60	effnetb1_272x240	.337
61	resnet50_robust_l2_eps3	.336
62	resnet50_ewconplus_wzc_seed6_2_323	.334
63	convnext_tiny:in12k_ft_in1k	.332
64	resnet50_robust_l2_eps1	.328
65	AdvProp_efficientnet-b8	.328
66	resnet50_ecoset_full	.327
67	BiT-S-R50x1	.327
68	efficientnet_b0_imagenet_full	.327
69	mobilenet_v2_0_75_224	.327
70	convnext_femto_ols:d1_in1k	.326
71	ReAlnet01_cornet_fov12	.325
72	convnext_large_imagenet_full_seed-0	.322
73	voneresnet-50-robust	.320
74	voneresnet-50	.320
75	resnet50_imagenet_full	.317
76	mobilenet_v2_1_0_192	.313
77	tv_efficientnet-b1	.312
78	vgg_19	.311
79	AdvProp_efficientnet-b6	.309
80	imagenet_l2_3_0	.308
81	yolos_tiny	.307
82	resnet50-barlow	.306
83	convnext_large:fb_in22k_ft_in1k	.305
84	resnet50-vicregl0p9	.301
85	convnext_base_imagenet_full_seed-0	.299
86	convnext_tiny_imagenet_full_seed-0	.295
87	convnext_small_imagenet_full_seed-0	.295
88	resnet50-SIN	.289
89	efficientnet_b0	.289
90	efficientnet_b1_imagenet_full	.289
91	vgg_16	.288
92	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.286
93	resnet152_ecoset_full	.282
94	deepeisnn_ei_imagenet_resnet18	.282
95	AdvProp_efficientnet-b7	.281
96	resnet50-vicregl0p75	.279
97	yudixie_resnet18_distance_reg_0_240719	.278
98	resnet101_ecoset_full	.277
99	resnet50_imagenet_100_seed-0	.277
100	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.277
101	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.275
102	resnet101_imagenet_full	.274
103	custom_model_cv_18_dagger_408	.274
104	densenet-121	.270
105	yudixie_resnet18_distance_translation_0_240719	.270
106	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.270
107	resnet50-vicreg	.269
108	Res2Net50_26w_4s	.267
109	ReAlnet01_cornet_fov16	.266
110	vit_large_patch14_clip_224:laion2b_ft_in1k	.266
111	mobilenet_v2_1_0_224	.265
112	resnet50-moclr8deg	.265
113	AlexNet_SIN	.265
114	cvt_cvt-21-384-in1k_4_LucyV4	.265
115	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.265
116	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.264
117	convnext_large_in22k_supervised	.264
118	yudixie_resnet18_translation_rotation_0_240719	.264
119	convnext_tiny_sup	.263
120	xception	.262
121	resnet-50-robust	.262
122	yudixie_resnet18_distance_rotation_0_240719	.262
123	mobilenet_v2_0_5_224	.262
124	vit_base_patch14_reg4_dinov2-lvd142m	.262
125	BiT-S-R50x3	.261
126	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.260
127	dinov2_vitl14_reg_lc_featread	.260
128	dinov2_vitl14_reg_lc	.260
129	efficientnet_b2_imagenet_full	.257
130	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.256
131	artResNet18_1	.256
132	vit_base_patch14_dinov2-lvd142m	.256
133	pnasnet_large_halfPrecision	.256
134	alexnet_ks_torevert	.255
135	alexnet	.255
136	resnet50-SIN_IN	.255
137	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.255
138	yudixie_resnet18_distance_translation_rotation_0_240719	.254
139	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.254
140	convnext_base:clip_laiona_augreg_ft_in1k_384	.253
141	yudixie_resnet50_distance_rotation_0_240908	.253
142	vit_large_patch14_clip_224:openai_ft_in1k	.251
143	vit_base_patch16_dinov3-lvd1689m	.251
144	seresnext50_32x4d	.250
145	convnext_xlarge:fb_in22k_ft_in1k	.250
146	deit3_base_patch16_224_fb_in1k	.250
147	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.250
148	nasnet_mobile	.248
149	vit_base_patch16_clip_224:openai_ft_in1k	.247
150	yudixie_resnet18_translation_reg_0_240719	.247
151	resnet152_imagenet_full	.247
152	cv_18_dagger_408_pretrained	.246
153	convnext_small_imagenet_100_seed-0	.244
154	blt_vs	.244
155	resnet_50_v1_spiking	.243
156	resnet50-sup	.243
157	resnet_50_v1	.243
158	antialiased-r50	.242
159	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.241
160	vit_relpos_base_patch16_clsgap_224:sw_in1k	.240
161	resnet50-SIN_IN_IN	.239
162	cvt_cvt-13-384-in1k_4_LucyV4	.238
163	inception_v3	.237
164	yudixie_wbh_object_class_scaling_0415_imagenet	.236
165	yudixie_resnet18_imagenet1kpret_0_240719	.236
166	deit_base_imagenet_full_seed-0	.236
167	deepeisnn_ei_cifar10_vgg19	.235
168	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.234
169	deit_large_imagenet_full_seed-0	.234
170	cvt_cvt-13-224-in1k_4_LucyV4	.233
171	inception_v1	.232
172	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.230
173	omnivore_swinS	.230
174	resnet50-vitoimagevidnet8	.229
175	resnet50-VITO-8deg-cc	.229
176	resnet_101_v2	.228
177	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.227
178	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.227
179	dinov2_vitl14_lc	.225
180	resnext101_32x32d_wsl	.224
181	resnext101_32x48d_wsl	.223
182	yudixie_resnet50_translation_rotation_0_240908	.223
183	densenet-201	.223
184	deit_small_imagenet_full_seed-0	.222
185	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.220
186	regnety_032	.218
187	vit_huge_clip336_laion	.215
188	yudixie_resnet18_category_class_0_240719	.215
189	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.214
190	gabor_filter_mean_abs_4x4_v2	.213
191	densenet-169	.212
192	dinov2_vitg14_reg_lc	.211
193	resnet_50_v1_spiking_l4a	.210
194	resnet_50_v1_spiking_l4	.210
195	yudixie_resnet50_imagenet1kpret_0_240908	.210
196	resnet50_tutorial	.210
197	mobilenet_v2_1_4_224	.210
198	mobilenet_v2_1-4_224_pytorch	.209
199	dinov2_vitl14_lc_res336	.206
200	omnivore_swinB	.205
201	ReAlnet01_cornet_fov4	.204
202	yudixie_resnet18_object_class_0_240719	.203
203	vit_large_patch14_clip_336:laion2b_ft_in1k	.201
204	convnext_large_clip_laion2b_finelayers	.198
205	pr1_stl10_disentangled_alpha04	.198
206	BiT-S-R101x3	.198
207	focalnet_tiny_lrf_in1k	.193
208	deepeisnn_ei_cifar10_resnet18	.192
209	yudixie_resnet18_rotation_reg_0_240719	.188
210	cvt_cvt-21-224-in1k_4_LucyV4	.188
211	convnext_xxlarge_clip	.188
212	gabor_filter_entropy_4x4	.188
213	vit_large_clip336_openai	.185
214	convnext_base_fb_in1k_gram_aligned_dinov3	.184
215	predictive_coding_pc	.184
216	gabor_filter_entropy_4x4_v2	.182
217	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.181
218	yudixie_resnet50_distance_translation_0_240908	.180
219	dinov2_vitg14_lc	.175
220	yudixie_resnet50_rotation_reg_0_240908	.173
221	gabor_filter_entropy_4x4_v2_forcedCosine	.166
222	resnet_50_v2	.165
223	BiT-S-R152x2	.163
224	alexnet_fov4	.161
225	yudixie_resnet50_category_class_0_240908	.157
226	deit_small_imagenet_100_seed-0	.157
227	eva02_large_in22k	.153
228	yudixie_wbh_object_class_scaling_0415_run_1	.148
229	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.146
230	resnext101_32x8d_wsl	.145
231	resnet18_fair	.140
232	yudixie_resnet50_object_class_0_240908	.139
233	briaai_rmbg_1_4	.139
234	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.139
235	yudixie_resnet50_distance_translation_rotation_0_240908	.135
236	yudixie_resnet50_translation_reg_0_240908	.129
237	alexnet_fov16	.127
238	ViT_L_32_imagenet1k	.125
239	alexnet_fov12	.125
240	AlexNet_SIN_fov16	.120
241	resnet50_imagenet_10_seed-0	.118
242	convnext_small_imagenet_10_seed-0	.117
243	AlexNet_SIN_fov12	.113
244	yudixie_wbh_object_class_scaling_0415_run_2	.109
245	resnet_50_v1_spiking_l3	.108
246	convnext_base_fb_in22k_ft_in1k	.106
247	resnet50_primary_visual_cortex	.103
248	resnet-152_v2_pytorch	.097
249	deit_small_imagenet_10_seed-0	.095
250	compact_resnet50_robust_IT	.090
251	compact_resnet50_IT	.086
252	yudixie_resnet50_distance_reg_0_240908	.083
253	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.079
254	deit3_base_patch16_224_fb_in22k_ft_in1k	.079
255	convnext_base_fb_in1k	.079
256	deit_small_imagenet_1_seed-0	.068
257	alexnet_training_seed_01_fov16	.064
258	yudixie_wbh_object_class_scaling_0415_run_0	.062
259	alexnet_training_seed_02	.060
260	alexnet_training_seed_01_fov12	.060
261	compact_cornets_IT	.060
262	compact_vgg19_V4	.060
263	resnet50_imagenet_1_seed-0	.059
264	alexnet_training_seed_04	.059
265	compact_vgg19_IT	.058
266	alexnet_training_seed_03	.056
267	compact_resnet50_robust_V4	.056
268	convnext_small_imagenet_1_seed-0	.055
269	yudixie_wbh_object_class_scaling_0415_run_3	.053
270	alexnet_training_seed_09	.048
271	alexnet_training_seed_01	.048
272	alexnet_training_seed_05	.046
273	alexnet_training_seed_10	.042
274	alexnet_training_seed_07	.039
275	alexnet_training_seed_06	.039
276	alexnet_training_seed_08	.033
277	yudixie_resnet50_random_0_240908	.029
278	yudixie_resnet18_random_0_240719	.027
279	AlexNet_SIN_fov4	.019
280	compact_resnet50_V4	.005
281	hmax	.000
282	compact_cornets_V4	.000
283	alexnet_training_seed_01_fov4	.000
284	pnasnet_large
285	BiT-S-R152x4
286	resnet_SIN_IN_FT_IN
287	vonegrcnn_52e_full
288	vonegrcnn_47e
289	pnasnet_large_pytorch
290	densenet_201_pytorch
291	inception_v3_pytorch
292	MIM
293	resnet50_eMMCR_Vanilla
294	TAU
295	PredRNN
296	SimVP
297	ConvLSTM
298	bp_resnet50_julios
299	regnet_y_400mf
300	antialiased-rnext101_32x8d
301	antialias-resnet152
302	resnet_152_v1
303	resnet_101_v1
304	resnet_152_v2
305	nasnet_large
306	inception_v4
307	grcnn_109
308	vonegrcnn_62e_nobn
309	grcnn
310	resnext101_32x16d_wsl

Benchmark bibtex

None

Ceiling

1.00.

Note that scores are relative to this ceiling.

Data: Bracci2019.anteriorVTC

Metric: rdm