1 citations · 1 across the 5 of their papers we have counts for
6 papers
ADU-Depth: Attention-based Distillation with Uncertainty Modeling for Depth Estimation
Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan +4
Monocular depth estimation is challenging due to its inherent ambiguity and ill-posed nature, yet it is quite important to many applications. While recent works achieve limited acc…
PPD: A New Valet Parking Pedestrian Fisheye Dataset for Autonomous Driving
Zizhang Wu, Xinyuan Chen, Fan Song +4
Pedestrian detection under valet parking scenarios is fundamental for autonomous driving. However, the presence of pedestrians can be manifested in a variety of ways and postures u…
Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection
Xianhui Cheng, Shoumeng Qiu, Zhikang Zou +2
Monocular 3D object detection aims to locate objects in different scenes with just a single image. Due to the absence of depth information, several monocular 3D detection technique…
Learning Monocular Depth in Dynamic Environment via Context-aware Temporal Attention
Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan +4
The monocular depth estimation task has recently revealed encouraging prospects, especially for the autonomous driving task. To tackle the ill-posed problem of 3D geometric reasoni…
Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentation
Shoumeng Qiu, Feng Jiang, Haiqiang Zhang +2
3D point cloud semantic segmentation is one of the fundamental tasks for environmental understanding. Although significant progress has been made in recent years, the performance o…
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentation
Feng Jiang, Heng Gao, Shoumeng Qiu +3
LiDAR point cloud segmentation is one of the most fundamental tasks for autonomous driving scene understanding. However, it is difficult for existing models to achieve both high in…