1st Place Solutions for Waymo Open Dataset Challenges – 2D and 3D Tracking

06/28/2020
by   Yu Wang, et al.
10

This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges. An efficient and pragmatic online tracking-by-detection framework named HorizonMOT is proposed for camera-based 2D tracking in the image space and LiDAR-based 3D tracking in the 3D world space. Within the tracking-by-detection paradigm, our trackers leverage our high-performing detectors used in the 2D/3D detection challenges and achieved 45.13 challenges.

READ FULL TEXT

page 1

page 6

page 7

research
08/28/2020

PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges

In this technical report, we present the top-performing LiDAR-only solut...
research
02/02/2016

Simple Online and Realtime Tracking

This paper explores a pragmatic approach to multiple object tracking whe...
research
03/30/2020

RetinaTrack: Online Single Stage Joint Detection and Tracking

Traditionally multi-object tracking and object detection are performed u...
research
11/14/2022

SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes

The SportsMOT competition aims to solve multiple object tracking of athl...
research
07/26/2023

Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis

Splitting of sequential data, such as videos and time series, is an esse...
research
02/06/2017

Challenge of Multi-Camera Tracking

Multi-camera tracking is quite different from single camera tracking, an...
research
03/15/2012

An Online Learning-based Framework for Tracking

We study the tracking problem, namely, estimating the hidden state of an...

Please sign up or login with your details

Forgot password? Click here to reset