7 citations · 11 across the 6 of their papers we have counts for
6 papers
IP-MOT: Instance Prompt Learning for Cross-Domain Multi-Object Tracking
Run Luo, Zikai Song, Longze Chen +3
Multi-Object Tracking (MOT) aims to associate multiple objects across video frames and is a challenging vision task due to inherent complexities in the tracking environment. Most e…
TrackSSM: A General Motion Predictor by State-Space Model
Bin Hu, Run Luo, Zelin Liu +2
Temporal motion modeling has always been a key component in multiple object tracking (MOT) which can ensure smooth trajectory movement and provide accurate positional information t…
Autogenic Language Embedding for Coherent Point Tracking
Zikai Song, Ying Tang, Run Luo +4
Point tracking is a challenging task in computer vision, aiming to establish point-wise correspondence across long video sequences. Recent advancements have primarily focused on te…
DiffusionTrack: Diffusion Model For Multi-Object Tracking
Run Luo, Zikai Song, Lintao Ma +3
Multi-object tracking (MOT) is a challenging vision task that aims to detect individual objects within a single frame and associate them across multiple frames. Recent MOT approach…
Compact Transformer Tracker with Correlative Masked Modeling
Zikai Song, Run Luo, Junqing Yu +2
Transformer framework has been showing superior performances in visual object tracking for its great strength in information aggregation across the template and search image with t…
VariabilityTrack:Multi-Object Tracking with Variable Speed Object Movement
Run Luo, JinLin Wei, Qiao Lin
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in videos. Most methods can be roughly classified as tracking-by-detection and joint-detecti…