8 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…
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…
ORMOT: A Dataset and Framework for Omnidirectional Referring Multi-Object Tracking
Sijia Chen, Zihan Zhou, Yanqiu Yu +2
Multi-Object Tracking (MOT) is a fundamental task in computer vision, aiming to track targets across video frames. Existing MOT methods perform well in general visual scenes, but f…
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, Yanqiu Yu +3
Referring Multi-Object Tracking (RMOT) aims to track specific targets based on language descriptions and is vital for interactive AI systems such as robotics and autonomous driving…
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…