Spatio-Temporal Action Detection with Cascade Proposal and Location Anticipation
In this work, we address the problem of spatio-temporal action detection in temporally untrimmed videos. It is an important and challenging task as finding accurate human actions in both temporal and spatial space is important for analyzing large-scale video data. To tackle this problem, we propose a cascade proposal and location anticipation (CPLA) model for frame-level action detection. There are several salient points of our model: (1) a cascade region proposal network (casRPN) is adopted for action proposal generation and shows better localization accuracy compared with single region proposal network (RPN); (2) action spatio-temporal consistencies are exploited via a location anticipation network (LAN) and thus frame-level action detection is not conducted independently. Frame-level detections are then linked by solving an linking score maximization problem, and temporally trimmed into spatio-temporal action tubes. We demonstrate the effectiveness of our model on the challenging UCF101 and LIRIS-HARL datasets, both achieving state-of-the-art performance.
Code (0)
등록된 구현이 없습니다.
Tasks
Action DetectionRegion ProposalSimilar Papers 제목 키워드 기반
A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos
Existing approaches for spatio-temporal action detection in videos are limited by the spatial extent and temporal duration of the actions. In this paper, we present a modular system for spatio-temporal action detection i…
Action ClassificationAction DetectionClusteringobject-detection+1STEP: Spatio-Temporal Progressive Learning for Video Action Detection
In this paper, we propose Spatio-TEmporal Progressive (STEP) action detector---a progressive learning framework for spatio-temporal action detection in videos. Starting from a handful of coarse-scale proposal cuboids, ou…
Action DetectionAction RecognitionVideo Action DetectionFast Action Proposals for Human Action Detection and Search
In this paper we target at generating generic action proposals in unconstrained videos. Each action proposal corresponds to a temporal series of spatial bounding boxes, i.e., a spatio-temporal video tube, which has a goo…
Action DetectionVideo SegmentationVideo Semantic SegmentationCBR-Net: Cascade Boundary Refinement Network for Action Detection: Submission to ActivityNet Challenge 2020 (Task 1)
In this report, we present our solution for the task of temporal action localization (detection) (task 1) in ActivityNet Challenge 2020. The purpose of this task is to temporally localize intervals where actions of inter…
Action DetectionAction LocalizationTemporal Action LocalizationLearning to track for spatio-temporal action localization
We propose an effective approach for spatio-temporal action localization in realistic videos. The approach first detects proposals at the frame-level and scores them with a combination of static and motion CNN features. …
Action LocalizationSpatio-Temporal Action LocalizationTemporal Action LocalizationTemporal Localization