Predictive Self-Conditioning for Accurate and Calibrated LiDAR 3D Object Detection
Published in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV, CORE A), 2027
This paper introduces Predictive Self-Conditioning (PSC), a within-frame feature-level feedback mechanism that converts Pass-1 proposals into confidence-weighted Gaussian heatmaps and injects them as a BEV feature residual before Pass-2, significantly boosting accuracy and calibration for LiDAR 3D object detection.
Recommended citation: Sami Sadat, Md. Irtiza Hossain, Shreya Adrita Banik, Md Zia Uddin, Md. Golam Rabiul Alam. (2027). "Predictive Self-Conditioning for Accurate and Calibrated LiDAR 3D Object Detection." IEEE/CVF Winter Conference on Applications of Computer Vision (WACV, CORE A). Accepted.
