Pith. sign in

REVIEW

Tencent Video Dataset (TVD): A Video Dataset for Learning-based Visual Data Compression and Analysis

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2105.05961 v1 pith:UZHN7ME2 submitted 2021-05-12 eess.IV

classification eess.IV
keywords videodatasetanalysiscompressiondatadatasetslearning-basedtencent
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Learning-based visual data compression and analysis have attracted great interest from both academia and industry recently. More training as well as testing datasets, especially good quality video datasets are highly desirable for related research and standardization activities. Tencent Video Dataset (TVD) is established to serve various purposes such as training neural network-based coding tools and testing machine vision tasks including object detection and tracking. TVD contains 86 video sequences with a variety of content coverage. Each video sequence consists of 65 frames at 4K (3840x2160) spatial resolution. In this paper, the details of this dataset, as well as its performance when compressed by VVC and HEVC video codecs, are introduced.

Discussion (0). Sign in to comment.

Pith tools