Scene-centric Joint Parsing of Cross-view Videos

09/16/2017
by   Hang Qi, et al.
0

Cross-view video understanding is an important yet under-explored area in computer vision. In this paper, we introduce a joint parsing framework that integrates view-centric proposals into scene-centric parse graphs that represent a coherent scene-centric understanding of cross-view scenes. Our key observations are that overlapping fields of views embed rich appearance and geometry correlations and that knowledge fragments corresponding to individual vision tasks are governed by consistency constraints available in commonsense knowledge. The proposed joint parsing framework represents such correlations and constraints explicitly and generates semantic scene-centric parse graphs. Quantitative experiments show that scene-centric predictions in the parse graph outperform view-centric predictions.

READ FULL TEXT
research
11/13/2021

Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views

Learning object-centric representations of multi-object scenes is a prom...
research
03/25/2018

Scene Graph Parsing as Dependency Parsing

In this paper, we study the problem of parsing structured knowledge grap...
research
06/09/2019

Cross-view Semantic Segmentation for Sensing Surroundings

Sensing surroundings is ubiquitous and effortless to humans: It takes a ...
research
03/06/2023

UniHCP: A Unified Model for Human-Centric Perceptions

Human-centric perceptions (e.g., pose estimation, human parsing, pedestr...
research
09/01/2021

Memory Based Video Scene Parsing

Video scene parsing is a long-standing challenging task in computer visi...
research
01/11/2023

Allo-centric Occupancy Grid Prediction for Urban Traffic Scene Using Video Prediction Networks

Prediction of dynamic environment is crucial to safe navigation of an au...
research
01/12/2023

Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study

Most approaches to cross-modal retrieval (CMR) focus either on object-ce...

Please sign up or login with your details

Forgot password? Click here to reset