Prediction-Tracking-Segmentation

04/05/2019
by   Jianren Wang, et al.
0

We introduce a prediction driven method for visual tracking and segmentation in videos. Instead of solely relying on matching with appearance cues for tracking, we build a predictive model which guides finding more accurate tracking regions efficiently. With the proposed prediction mechanism, we improve the model robustness against distractions and occlusions during tracking. We demonstrate significant improvements over state-of-the-art methods not only on visual tracking tasks (VOT 2016 and VOT 2018) but also on video segmentation datasets (DAVIS 2016 and DAVIS 2017).

READ FULL TEXT

page 1

page 4

page 5

page 6

page 7

page 8

research
04/13/2023

Tracking by 3D Model Estimation of Unknown Objects in Videos

Most model-free visual object tracking methods formulate the tracking ta...
research
10/05/2019

Object Segmentation Tracking from Generic Video Cues

We propose a light-weight variational framework for online tracking of o...
research
10/19/2019

Tracking-Assisted Segmentation of Biological Cells

U-Net and its variants have been demonstrated to work sufficiently well ...
research
10/18/2021

MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation

Recently, there has been tremendous progress in developing each individu...
research
09/01/2016

Attentional Push: Augmenting Salience with Shared Attention Modeling

We present a novel visual attention tracking technique based on Shared A...
research
04/10/2016

Real-Time Facial Segmentation and Performance Capture from RGB Input

We introduce the concept of unconstrained real-time 3D facial performanc...
research
07/05/2021

A topological solution to object segmentation and tracking

The world is composed of objects, the ground, and the sky. Visual percep...

Please sign up or login with your details

Forgot password? Click here to reset