Methods › Computer Vision › Multi-Object Tracking Models › TraDeS

TraDeS

1 paper tagged archive 2025-07-28

Introduced by Jialian Wu et al. in Track to Detect and Segment: An Online Multi-Object Tracker

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

TradeS is an online joint detection and tracking model, coined as TRACK to DEtect and Segment, exploiting tracking clues to assist detection end-to-end. TraDeS infers object tracking offset by a cost volume, which is used to propagate previous object features for improving current object detection and segmentation.

PaperSource

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
3D Multi-Object Tracking1
Instance Segmentation1
Multi-Object Tracking1
Object1
Object Detection1
Object Tracking1
Online Multi-Object Tracking1
Segmentation1
Semantic Segmentation1
Video Instance Segmentation1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with TraDeS: 2021 to 2021, peak 1 1 0 2021: 1 paper 2021
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Multi-Object Tracking Models

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