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MVTrack: Ultrafast appearance-free object tracking from compressed video

Researchers have developed MVTrack, a novel system for tracking moving objects that operates directly on compressed video bitstreams, bypassing the need for pixel reconstruction. This approach significantly reduces computational costs and latency compared to traditional RGB-based object detectors. MVTrack combines MVDet for motion vector field detection with MVLink for kinematic association, achieving superior performance on the VIRAT dataset while using substantially fewer parameters and FLOPs than existing methods like YOLO26n. AI

IMPACT This research could enable more efficient and scalable video surveillance and analysis systems by leveraging compressed video data.

RANK_REASON The cluster contains an academic paper detailing a new method for video tracking.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

MVTrack: Ultrafast appearance-free object tracking from compressed video

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The cluster contains an academic paper detailing a new method for video tracking.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · I\~naki Erregue, Kamal Nasrollahi, Sergio Escalera ·

    MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams

    arXiv:2608.10790v1 Announce Type: cross Abstract: Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an ultrafast tracker for moving objects that operates directly on H.264 bitstreams.…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams

    Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an ultrafast tracker for moving objects that operates directly on H.264 bitstreams. MVTrack combines MVDet, a lightweight detector fo…