1 citations · 1 across the 9 of their papers we have counts for
9 papers
FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition
Enhui Yu, Junhui Li, Ruitong Lu +2
Fine-grained fruit classification is a critical yet challenging task in agricultural computer vision, primarily hindered by a severe shortage of high-quality datasets and the high…
ORMOT: A Dataset and Framework for Omnidirectional Referring Multi-Object Tracking
Zihan Zhou, Sijia Chen, Yanqiu Yu +2
Omnidirectional cameras provide 360° spatial coverage, making them increasingly valuable in applications such as autonomous driving and video surveillance. While Multi-Object Track…
RT-RMOT: A Dataset and Framework for RGB-Thermal Referring Multi-Object Tracking
Yanqiu Yu, Zhifan Jin, Sijia Chen +4
Referring Multi-Object Tracking has attracted increasing attention due to its human-friendly interactive characteristics, yet it exhibits limitations in low-visibility conditions,…
DRMOT: A Dataset and Framework for RGBD Referring Multi-Object Tracking
Sijia Chen, Lijuan Ma, Shaofeng Liang +9
Referring Multi-Object Tracking (RMOT) aims to track specific targets based on language descriptions, playing a vital role in interactive AI systems such as robotics and autonomous…
Disentangling Instance and Scene Contexts for 3D Semantic Scene Completion
Enyu Liu, En Yu, Sijia Chen +1
3D Semantic Scene Completion (SSC) has gained increasing attention due to its pivotal role in 3D perception. Recent advancements have primarily focused on refining voxel-level feat…
ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking
Sijia Chen, Yanqiu Yu, En Yu +1
Referring Multi-Object Tracking (RMOT) aims to track targets specified by language instructions. However, existing RMOT paradigms heavily rely on explicit visual-textual matching a…
OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer
Jinyang Li, En Yu, Sijia Chen +1
Open-vocabulary multiple object tracking aims to generalize trackers to unseen categories during training, enabling their application across a variety of real-world scenarios. Howe…
Cross-View Referring Multi-Object Tracking
Sijia Chen, En Yu, Wenbing Tao
Referring Multi-Object Tracking (RMOT) is an important topic in the current tracking field. Its task form is to guide the tracker to track objects that match the language descripti…
Delving into the Trajectory Long-tail Distribution for Muti-object Tracking
Sijia Chen, En Yu, Jinyang Li +1
Multiple Object Tracking (MOT) is a critical area within computer vision, with a broad spectrum of practical implementations. Current research has primarily focused on the developm…