3 citations · 5 across the 13 of their papers we have counts for
15 papers
RiskFly: Frustum-Aligned Spatio-Temporal Risk Fields for One-Stage Agile Flight in Dynamic Clutter
Luxia Ai, Haopeng Chen, Yuchao Mei +2
Agile flight in unknown, cluttered, and dynamic environments requires a planner that knows where and when danger will appear, not only that a trajectory is dangerous. One-stage lea…
Learning Beyond Full Imitation: Task-Preserving Knowledge Distillation
Qianfeng Yuan, Wenbing Tao
Knowledge distillation transfers knowledge by encouraging a student to match a teacher's predicted class probabilities. These probabilities express not only confidence in the corre…
Anticipatory Risk-Guided Reinforcement Learning for Safe Flight Through Dynamic Clutter
Yuchao Mei, Guohao Zhang, Luxia Ai +2
Safe quadrotor navigation in cluttered and dynamic environments depends not only on instantaneous geometric perception, but more critically on anticipating collision risks induced…
PET-DINO: Unifying Visual Cues into Grounding DINO with Prompt-Enriched Training
Weifu Fu, Jinyang Li, Bin-Bin Gao +6
Open-Set Object Detection (OSOD) enables recognition of novel categories beyond fixed classes but faces challenges in aligning text representations with complex visual concepts and…
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…
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…
Perception-R1: Pioneering Perception Policy with Reinforcement Learning
En Yu, Kangheng Lin, Liang Zhao +11
Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement learning (RL) in MLLM post-training for perception policy learning. While promising, ou…
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…
Unhackable Temporal Rewarding for Scalable Video MLLMs
En Yu, Kangheng Lin, Liang Zhao +8
In the pursuit of superior video-processing MLLMs, we have encountered a perplexing paradox: the "anti-scaling law", where more data and larger models lead to worse performance. Th…
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…
Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy
Yu-Xin Zhang, Jie Gui, Baosheng Yu +4
Point cloud registration involves determining a rigid transformation to align a source point cloud with a target point cloud. This alignment is fundamental in applications such as…
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…
Merlin:Empowering Multimodal LLMs with Foresight Minds
En Yu, Liang Zhao, Yana Wei +8
Humans possess the remarkable ability to foresee the future to a certain extent based on present observations, a skill we term as foresight minds. However, this capability remains…