86 citations · 182 across the 9 of their papers we have counts for
10 papers
Parallel Scale-wise Attention Network for Effective Scene Text Recognition
Usman Sajid, Michael Chow, Jin Zhang +2
The paper proposes a new text recognition network for scene-text images. Many state-of-the-art methods employ the attention mechanism either in the text encoder or decoder for the…
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images
Lei He, Jiwen Lu, Guanghui Wang +2
Depth estimation and semantic segmentation play essential roles in scene understanding. The state-of-the-art methods employ multi-task learning to simultaneously learn models for t…
Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter
Tianxiao Zhang, Xiaohan Zhang, Yiju Yang +2
This paper focuses on the problem of online golf ball detection and tracking from image sequences. An efficient real-time approach is proposed by exploiting convolutional neural ne…
Stereo Frustums: A Siamese Pipeline for 3D Object Detection
Xi Mo, Usman Sajid, Guanghui Wang
The paper proposes a light-weighted stereo frustums matching module for 3D objection detection. The proposed framework takes advantage of a high-performance 2D detector and a point…
Deep Feature Augmentation for Occluded Image Classification
Feng Cen, Xiaoyu Zhao, Wuzhuang Li +1
Due to the difficulty in acquiring massive task-specific occluded images, the classification of occluded images with deep convolutional neural networks (CNNs) remains highly challe…
Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling
Wenchi Ma, Miao Yu, Kaidong Li +1
Layer-wise learning, as an alternative to global back-propagation, is easy to interpret, analyze, and it is memory efficient. Recent studies demonstrate that layer-wise learning ca…