Hugging Face Trending Papers
MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking
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arXiv Computer Vision
3d ago
MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking
arXiv:2608.24365v1 Announce Type: new Abstract: Transformer-based object trackers are renowned for their strong performance, yet dense token processing often leads to prohibitive computational cost,...
Hugging Face Trending Papers
Aug 11
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.
arXiv AI
Aug 12
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.
arXiv Computer Vision
5d ago
Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking
Tetris is a video object tracking system that uses tile-level sampling to efficiently extract high‑fidelity tracks. It partitions videos into tile‑based polyominoes, classifies relevant tiles, prunes redundant ones with an ILP under a user‑defined accuracy constraint, and packs the remaining polyominoes to minimize detector calls. On seven stationary‑video datasets, Tetris maintains less than a 5% loss in tracking accuracy while achieving up to 17.4× higher throughput than prior systems and up to 68.8× higher than a full‑frame reference pipeline.
arXiv Computer Vision
4d ago
Adaptive Tokenisation Via Temporal Redundancy Masking And Latent Inpainting
arXiv:2606.06158v2 Announce Type: replace Abstract: Adaptive video tokenisation seeks to dynamically allocate token budgets based on the underlying visual complexity of a sequence. Current continuous...
arXiv Computer Vision
4d ago
RS$^3$-Prune: Read-Sparse, Store-Sparse Token Pruning for Video Object Segmentation
arXiv:2608.22526v1 Announce Type: new Abstract: We introduce RS$^3$-Prune, a training-free token-pruning recipe that instantiates as a small set of inference time hooks atop existing video object seg...