Skip to main content

Datasets

Standard Dataset

FPNforV-PCC

Citation Author(s):
Que Shicheng
Submitted by:
Shicheng Que
Last updated:
DOI:
10.21227/hb84-q682
83 views
Categories:
Keywords:
No Ratings Yet

Abstract

This dataset is for paper "A feature pyramid network based partition map prediction method for efficient encoding in Video-based Point Cloud Compress", and is what the authors use for training the FPN mentioned in the paper. The CU partitioning data in this dataset comes from V-PCC using VVC to make CU partition and extracting data for a sample based on 64×64 CU. Encoder configuration when extracting data as described in Section III-A of the paper, the point cloud source is the first 32 frames of basketball_player order by owlii, including the partitioning of 5 different QPs. In the dataset, "AttrI_TOri" and "GeomP_TOri" represents the input for luma values, "AttrI_Resi" and "GeomP_Resi" stands for the prediction residual input, "AttrI_Occu" and "GeomP_Occu" denotes the placeholder information input, and "AttrI_y_QP" and "GeomP_y_QP" encompasses both the label value and QP input. The program source code is available on https://github.com/Mesks/FPNforV-PCC/tree/master.

Instructions:

"AttrI_TOri" and "GeomP_TOri" represents the input for luma values, "AttrI_Resi" and "GeomP_Resi" stands for the prediction residual input, "AttrI_Occu" and "GeomP_Occu" denotes the placeholder information input, and "AttrI_y_QP" and "GeomP_y_QP" encompasses both the label value and QP input, in "XXXX_y_QP" the first 480 columns are label vectors' elements and the last column is QP value.

Dataset Files

Files have not been uploaded for this dataset