Pith. sign in

REVIEW

Action recognition in real-world videos

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

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 2004.10774 v1 pith:NDH7K4UQ submitted 2020-04-22 cs.CV eess.IV

Waqas Sultani , Qazi Ammar Arshad , Chen Chen This is my paper · ORCID
classification cs.CVeess.IV
keywords actiondetectionhumanlocalizationrecognitionreferredvideoactivity
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

The goal of human action recognition is to temporally or spatially localize the human action of interest in video sequences. Temporal localization (i.e. indicating the start and end frames of the action in a video) is referred to as frame-level detection. Spatial localization, which is more challenging, means to identify the pixels within each action frame that correspond to the action. This setting is usually referred to as pixel-level detection. In this chapter, we are using action, activity, event interchangeably.

Discussion (0). Continue with ORCID to comment.

Pith tools