Search Results for author:
Found 6 papers, 2 papers with code
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.
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.
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).
Self-Growing Spatial Graph Network for Context-Aware Pedestrian Trajectory Prediction
To fill this gap, we propose Social Trajectory Recommender-Gated Graph Recurrent Neighborhood Network, (STR-GGRNN), which uses data-driven adaptive online neighborhood recommendation based on the contextual scene features and pedestrian visual cues.
Multi-fold Correlation Attention Network for Predicting Traffic Speeds with Heterogeneous Frequency
We propose a Heterogeneous Spatial Correlation (HSC) model to capture the spatial correlation based on a specific measurement, where the traffic data of varying road segments can be heterogeneous (i. e. obtained with different sampling frequency).
