Peihan Hao — accepted AI-conference papers

2022

INT: Towards Infinite-Frames 3D Detection with an Efficient Framework

Jianyun Xu, Zhenwei Miao, Da Zhang, Hongyu Pan, Kaixuan Liu, Peihan Hao +4

ECCV 2022poster

"It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased comput…

Cited by 22 Source ↗PDF ↗code ↗Scholar ↗

2021

PVGNet: A Bottom-Up One-Stage 3D Object Detector With Integrated Multi-Level Features

Zhenwei Miao, Jikai Chen, Hongyu Pan, Ruiwen Zhang, Kaixuan Liu, Peihan Hao +3

CVPR 2021poster

Quantization-based methods are widely used in LiDAR points 3D object detection for its efficiency in extracting context information. Unlike image where the context information is distributed evenly over the object, most LiDAR points are distributed along the object boundary, which means the boundary…

Cited by 57 PDF ↗Scholar ↗