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Online and Real-Time Mask-Guided Multi-Object Tracking and Segmentation

https://doi.org/10.2139/ssrn.4098769
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5/5 checkable references clean · checked 2026-07-30

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

22 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 5 checked references that resolve
resolves10.1007/978-3-030-58621-8_7
Towards Real-Time Multi-Object Tracking
resolves10.1109/ICIP.2017.8296962
Simple online and realtime tracking with a deep association metric
resolves10.1109/LRA.2020.2969183
Track to Reconstruct and Reconstruct to Track
resolves10.1002/nav.3800020109
The Hungarian method for the assignment problem
resolves10.1007/s11263-020-01375-2
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking
The 22 references without a DOI — listed, not checked
no DOI — not checkedCentermask: Real-time anchor-free instance segmentation
no DOI — not checkedOn the fairness of detection and re-identification in multiple object tracking
no DOI — not checkedMots: Multi-object tracking and segmentation
no DOI — not checkedref6
no DOI — not checkedLearning a neural solver for multiple object tracking
no DOI — not checkedSpatial-temporal relation networks for multi-object tracking
no DOI — not checkedGlobal data association for multi-object tracking using network flows
no DOI — not checkedLifted disjoint paths with application in multiple object tracking
no DOI — not checkedPremvos: Proposal-generation, refinement and merging for video object segmentation
no DOI — not checkedTrack, then decide: Category-agnostic vision-based multi-object tracking
no DOI — not checkedInstance segmentation and tracking with cosine embeddings and recurrent hourglass networks
no DOI — not checkedref14
no DOI — not checkedVip-deeplab: Learning visual perception with depth-aware video panoptic segmentation
no DOI — not checkedSegment as points for efficient online multi-object tracking and segmentation
no DOI — not checkedref18
no DOI — not checkedref19
no DOI — not checkedref20
no DOI — not checkedAn energy and gpucomputation efficient backbone network for real-time object detection
no DOI — not checkedref22
no DOI — not checkedref23
no DOI — not checkedMulti-task learning using uncertainty to weigh losses for scene geometry and semantics
no DOI — not checkedref25
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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