SOTAVerified

Multi-Object Tracking and Segmentation

Multiple object tracking and segmentation requires detecting, tracking, and segmenting objects belonging to a set of given classes.

(Image and definition credit: Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation, NeurIPS 2021, Spotlight )

Papers

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Showing 21–28 of 28 papers

TitleStatusHype
Multi-Object Tracking and Segmentation with a Space-Time Memory Network—0
DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception—0
MeNToS: Tracklets Association with a Space-Time Memory Network—0
MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking—0
Weakly Supervised Multi-Object Tracking and Segmentation—0
ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentation—0
Learning Multi-Object Tracking and Segmentation from Automatic Annotations—0
MOTS: Multi-Object Tracking and Segmentation—0
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All datasetsBDD100K valKITTI MOTS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UNINEXT-HmMOTSA35.7—Unverified
2UnicornmMOTSA29.6—Unverified
#ModelMetricClaimedVerifiedStatus
1EagerMOTAssA73.75—Unverified