8 citations · 27 across the 10 of their papers we have counts for
10 papers
Dilated Continuous Random Field for Semantic Segmentation
Xi Mo, Xiangyu Chen, Cuncong Zhong +3
Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation. In this paper, we…
Towards More Effective PRM-based Crowd Counting via A Multi-resolution Fusion and Attention Network
Usman Sajid, Guanghui Wang
The paper focuses on improving the recent plug-and-play patch rescaling module (PRM) based approaches for crowd counting. In order to make full use of the PRM potential and obtain…
Audio-Visual Transformer Based Crowd Counting
Usman Sajid, Xiangyu Chen, Hasan Sajid +2
Crowd estimation is a very challenging problem. The most recent study tries to exploit auditory information to aid the visual models, however, the performance is limited due to the…
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…
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…
Multi-Resolution Fusion and Multi-scale Input Priors Based Crowd Counting
Usman Sajid, Wenchi Ma, Guanghui Wang
Crowd counting in still images is a challenging problem in practice due to huge crowd-density variations, large perspective changes, severe occlusion, and variable lighting conditi…
Classification of Noncoding RNA Elements Using Deep Convolutional Neural Networks
Brian McClannahan, Krushi Patel, Usman Sajid +2
The paper proposes to employ deep convolutional neural networks (CNNs) to classify noncoding RNA (ncRNA) sequences. To this end, we first propose an efficient approach to convert t…
ZoomCount: A Zooming Mechanism for Crowd Counting in Static Images
Usman Sajid, Hasan Sajid, Hongcheng Wang +1
This paper proposes a novel approach for crowd counting in low to high density scenarios in static images. Current approaches cannot handle huge crowd diversity well and thus perfo…
Plug-and-Play Rescaling Based Crowd Counting in Static Images
Usman Sajid, Guanghui Wang
Crowd counting is a challenging problem especially in the presence of huge crowd diversity across images and complex cluttered crowd-like background regions, where most previous ap…
Object Detection with Convolutional Neural Networks
Kaidong Li, Wenchi Ma, Usman Sajid +2
In this chapter, we present a brief overview of the recent development in object detection using convolutional neural networks (CNN). Several classical CNN-based detectors are pres…