4 citations · 7 across the 9 of their papers we have counts for
9 papers
Affine Subspace Models and Clustering for Patch-Based Image Denoising
Tharindu Wickremasinghe, Marco F. Duarte
Image tile-based approaches are popular in many image processing applications such as denoising (e.g., non-local means). A key step in their use is grouping the images into cluster…
FlowSteer: Conditioning Flow Field for Consistent Image Restoration
Tharindu Wickremasinghe, Chenyang Qi, Harshana Weligampola +2
Flow-based text-to-image (T2I) models excel at prompt-driven image generation, but falter on Image Restoration (IR), often "drifting away" from being faithful to the measurement. P…
SeeU: Seeing the Unseen World via 4D Dynamics-aware Generation
Yu Yuan, Tharindu Wickremasinghe, Zeeshan Nadir +3
Images and videos are discrete 2D projections of the 4D world (3D space + time). Most visual understanding, prediction, and generation operate directly on 2D observations, leading…
NewtonGen: Physics-Consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics
Yu Yuan, Xijun Wang, Tharindu Wickremasinghe +3
A primary bottleneck in large-scale text-to-video generation today is physical consistency and controllability. Despite recent advances, state-of-the-art models often produce unrea…
Max-Min Fairness for IRS-Assisted Secure Two-Way Communications
Harindu Jayarathne, Tharindu Wickremasinghe, Kasun T. Hemachandra +2
This paper investigates an intelligent reflective surface (IRS) assisted secure multi-user two-way communication system. The aim of this paper is to enhance the physical layer secu…
Fill in the blanks: Rethinking Interpretability in vision
Pathirage N. Deelaka, Tharindu Wickremasinghe, Devin Y. De Silva +1
Model interpretability is a key challenge that has yet to align with the advancements observed in contemporary state-of-the-art deep learning models. In particular, deep learning a…
MOSAIC: Masked Optimisation with Selective Attention for Image Reconstruction
Pamuditha Somarathne, Tharindu Wickremasinghe, Amashi Niwarthana +3
Compressive sensing (CS) reconstructs images from sub-Nyquist measurements by solving a sparsity-regularized inverse problem. Traditional CS solvers use iterative optimizers with h…
HPGNN: Using Hierarchical Graph Neural Networks for Outdoor Point Cloud Processing
Arulmolivarman Thieshanthan, Amashi Niwarthana, Pamuditha Somarathne +2
Inspired by recent improvements in point cloud processing for autonomous navigation, we focus on using hierarchical graph neural networks for processing and feature learning over l…
Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systems
Oshada Jayasinghe, Sahan Hemachandra, Damith Anhettigama +5
Recent work done on traffic sign and traffic light detection focus on improving detection accuracy in complex scenarios, yet many fail to deliver real-time performance, specificall…