58 citations · 85 across the 6 of their papers we have counts for
6 papers
Towards Reproducible Learning-based Compression
Jiahao Pang, Muhammad Asad Lodhi, Junghyun Ahn +2
A deep learning system typically suffers from a lack of reproducibility that is partially rooted in hardware or software implementation details. The irreproducibility leads to skep…
WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
Eric Lei, Muhammad Asad Lodhi, Jiahao Pang +2
There have been recent efforts to learn more meaningful representations via fixed length codewords from mesh data, since a mesh serves as a complete model of underlying 3D shape co…
GRASP-Net: Geometric Residual Analysis and Synthesis for Point Cloud Compression
Jiahao Pang, Muhammad Asad Lodhi, Dong Tian
Point cloud compression (PCC) is a key enabler for various 3-D applications, owing to the universality of the point cloud format. Ideally, 3D point clouds endeavor to depict object…
FESTA: Flow Estimation via Spatial-Temporal Attention for Scene Point Clouds
Haiyan Wang, Jiahao Pang, Muhammad A. Lodhi +2
Scene flow depicts the dynamics of a 3D scene, which is critical for various applications such as autonomous driving, robot navigation, AR/VR, etc. Conventionally, scene flow is es…
Learning Product Graphs Underlying Smooth Graph Signals
Muhammad Asad Lodhi, Waheed U. Bajwa
Real-world data is often times associated with irregular structures that can analytically be represented as graphs. Having access to this graph, which is sometimes trivially eviden…
Detection Theory for Union of Subspaces
Muhammad Asad Lodhi, Waheed U. Bajwa
The focus of this paper is on detection theory for union of subspaces (UoS). To this end, generalized likelihood ratio tests (GLRTs) are presented for detection of signals conformi…