4 papers
HierDAMap: Towards Universal Domain Adaptive BEV Mapping via Hierarchical Perspective Priors
Siyu Li, Yihong Cao, Hao Shi +4
The exploration of Bird's-Eye View (BEV) mapping technology has driven significant innovation in visual perception technology for autonomous driving. BEV mapping models need to be…
EchoTrack: Auditory Referring Multi-Object Tracking for Autonomous Driving
Jiacheng Lin, Jiajun Chen, Kunyu Peng +4
This paper introduces the task of Auditory Referring Multi-Object Tracking (AR-MOT), which dynamically tracks specific objects in a video sequence based on audio expressions and ap…
S-MonoDETR: Supervised Shape&Scale-perceptive Deformable Transformer for Monocular 3D Object Detection
Xuan He, Jin Yuan, Kailun Yang +2
Recently, transformer-based methods have shown exceptional performance in monocular 3D object detection, which can predict 3D attributes from a single 2D image. These methods typic…
SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object Detection
Xuan He, Fan Yang, Kailun Yang +5
Transformer-based methods have demonstrated superior performance for monocular 3D object detection recently, which aims at predicting 3D attributes from a single 2D image. Most exi…