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A Simple and Efficient Multi-task Network for 3D Object Detection and
  Road Understanding

A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding

6 March 2021
Di Feng
Yiyang Zhou
Chenfeng Xu
Masayoshi Tomizuka
Wei Zhan
    3DPC
ArXivPDFHTML

Papers citing "A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding"

5 / 5 papers shown
Title
LiSD: An Efficient Multi-Task Learning Framework for LiDAR Segmentation
  and Detection
LiSD: An Efficient Multi-Task Learning Framework for LiDAR Segmentation and Detection
Jiahua Xu
Si Zuo
Chenfeng Wei
Wei Zhou
40
3
0
11 Jun 2024
Instance-aware 3D Semantic Segmentation powered by Shape Generators and
  Classifiers
Instance-aware 3D Semantic Segmentation powered by Shape Generators and Classifiers
Bo Sun
Qixing Huang
Xiangru Huang
3DV
3DPC
35
0
0
21 Nov 2023
LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR
  Perception
LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perception
Zixiang Zhou
Dongqiangzi Ye
Weijia Chen
Yufei Xie
Yu Wang
Panqu Wang
H. Foroosh
33
10
0
21 Mar 2023
Convolutional Recurrent Network for Road Boundary Extraction
Convolutional Recurrent Network for Road Boundary Extraction
Justin Liang
N. Homayounfar
Wei-Chiu Ma
Shenlong Wang
R. Urtasun
119
73
0
21 Dec 2020
SNE-RoadSeg: Incorporating Surface Normal Information into Semantic
  Segmentation for Accurate Freespace Detection
SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection
Rui Fan
Haoyu Wang
Peide Cai
Ming-Yu Liu
61
147
0
26 Aug 2020
1