DORT: Modeling Dynamic Objects in Recurrent for Multi-Camera 3D Object Detection and Tracking

Understand

Recent multi-camera 3D object detectors usually leverage temporal information to construct multi-view stereo that alleviates the ill-posed depth estimation.

• However, they typically assume all the objects are static and directly aggregate features across frames.
• This work begins with a theoretical and empirical analysis to reveal that ignoring the motion of moving objects can result in serious localization bias.
• Therefore, we propose to model Dynamic Objects in RecurrenT (DORT) to tackle this problem.