Search Results for author:
Found 7 papers, 1 papers with code
Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation
Specifically, inspired by Taylor series, we treat the local structure representation of irregular point clouds as a polynomial fitting problem and propose a novel local structure fitting convolution, called TaylorConv.
GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud Understanding
The core of GPSFormer is the Global Perception Module (GPM) and the Local Structure Fitting Convolution (LSFConv).
Ranked #4 on
3D Point Cloud Classification
on ScanObjectNN
CAP-Context-Aware-Pruning-for-Semantic-Segmentation
In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.
CAP: Context-Aware Pruning for Semantic-Segmentation
In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.
IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report
This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams).
SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection
We propose a method that explores semantic segmentation results as self-attention cues to significantly improve the pedestrian detection performance.
Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model
Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation.
