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result_name: partfield_features/correspondence_demo
continue_ckpt: model/model.ckpt
triplane_channels_low: 128
triplane_channels_high: 512
triplane_resolution: 128
vertex_feature: True
n_point_per_face: 1000
n_sample_each: 10000
is_pc: True
remesh_demo: False
correspondence_demo: True
preprocess_mesh: True
dataset:
type: "Mix"
data_path: data/DenseCorr3D
train_batch_size: 1
val_batch_size: 1
train_num_workers: 8
all_files:
# pairs of example to run correspondence
- animals/071b8_toy_animals_017/simple_mesh.obj
- animals/bdfd0_toy_animals_016/simple_mesh.obj
- animals/2d6b3_toy_animals_009/simple_mesh.obj
- animals/96615_toy_animals_018/simple_mesh.obj
- chairs/063d1_chair_006/simple_mesh.obj
- chairs/bea57_chair_012/simple_mesh.obj
- chairs/fe0fe_chair_004/simple_mesh.obj
- chairs/288dc_chair_011/simple_mesh.obj
# consider decimating animals/../color_mesh.obj yourself for better mesh topology than the provided simple_mesh.obj
# (e.g. <50k vertices for functional map efficiency).
loss:
triplet: 1.0
use_2d_feat: False
pvcnn:
point_encoder_type: 'pvcnn'
z_triplane_channels: 256
z_triplane_resolution: 128 |