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HENet++: Hybrid Encoding and Multi-task Learning for 3D Perception and End-to-end Autonomous Driving
Zhongyu Xia, Zhiwei Lin, Yongtao Wang +1
Three-dimensional feature extraction and multi-task perception are fundamental components of modern autonomous driving systems. Although large image encoders, high-resolution input…
PTQAT: A Hybrid Parameter-Efficient Quantization Algorithm for 3D Perception Tasks
Xinhao Wang, Zhiwei Lin, Zhongyu Xia +1
Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) represent two mainstream model quantization approaches. However, PTQ often leads to unacceptable performance…
OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection
Zhongyu Xia, Jishuo Li, Zhiwei Lin +3
Open-world perception aims to develop a model adaptable to novel domains and various sensor configurations and can understand uncommon objects and corner cases. However, current re…
HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras
Zhongyu Xia, ZhiWei Lin, Xinhao Wang +5
Three-dimensional perception from multi-view cameras is a crucial component in autonomous driving systems, which involves multiple tasks like 3D object detection and bird's-eye-vie…
RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection
Zhiwei Lin, Zhe Liu, Zhongyu Xia +7
Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce costs in practice, low-cost multi-view cameras for 3D object detection are proposed to r…