16 citations · 45 across the 5 of their papers we have counts for
6 papers · 1 filter
Data Augmentation for Object Detection via Differentiable Neural Rendering
Guanghan Ning, Guang Chen, Chaowei Tan +3
It is challenging to train a robust object detector under the supervised learning setting when the annotated data are scarce. Thus, previous approaches tackling this problem are in…
LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
Guanghan Ning, Heng Huang
In this paper, we propose a novel effective light-weight framework, called LightTrack, for online human pose tracking. The proposed framework is designed to be generic for top-down…
A Top-down Approach to Articulated Human Pose Estimation and Tracking
Guanghan Ning, Ping Liu, Xiaochuan Fan +1
Both the tasks of multi-person human pose estimation and pose tracking in videos are quite challenging. Existing methods can be categorized into two groups: top-down and bottom-up…
Progressive Neural Networks for Image Classification
Zhi Zhang, Guanghan Ning, Yigang Cen +4
The inference structures and computational complexity of existing deep neural networks, once trained, are fixed and remain the same for all test images. However, in practice, it is…
Dual Path Networks for Multi-Person Human Pose Estimation
Guanghan Ning, Zhihai He
The task of multi-person human pose estimation in natural scenes is quite challenging. Existing methods include both top-down and bottom-up approaches. The main advantage of bottom…
Knowledge Projection for Deep Neural Networks
Zhi Zhang, Guanghan Ning, Zhihai He
While deeper and wider neural networks are actively pushing the performance limits of various computer vision and machine learning tasks, they often require large sets of labeled d…