activity
20182024
most citedSmartEmbed: A Tool for Clone and Bug Detection in Smart Contracts through Structural Code Embedding

87 citations · 165 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CV2024

GAN Based Top-Down View Synthesis in Reinforcement Learning Environments

Usama Younus, Vinoj Jayasundara, Shivam Mishra +1

Human actions are based on the mental perception of the environment. Even when all the aspects of an environment are not visible, humans have an internal mental model that can gene…

cs.CV2023

Chop & Learn: Recognizing and Generating Object-State Compositions

Nirat Saini, Hanyu Wang, Archana Swaminathan +4

Recognizing and generating object-state compositions has been a challenging task, especially when generalizing to unseen compositions. In this paper, we study the task of cutting o…

cs.CV2023

FlexNeRF: Photorealistic Free-viewpoint Rendering of Moving Humans from Sparse Views

Vinoj Jayasundara, Amit Agrawal, Nicolas Heron +2

We present FlexNeRF, a method for photorealistic freeviewpoint rendering of humans in motion from monocular videos. Our approach works well with sparse views, which is a challengin…

cs.CV2021

PointCaps: Raw Point Cloud Processing using Capsule Networks with Euclidean Distance Routing

Dishanika Denipitiyage, Vinoj Jayasundara, Ranga Rodrigo +1

Raw point cloud processing using capsule networks is widely adopted in classification, reconstruction, and segmentation due to its ability to preserve spatial agreement of the inpu…

cs.CV2021

PatchGame: Learning to Signal Mid-level Patches in Referential Games

Kamal Gupta, Gowthami Somepalli, Anubhav Gupta +3

We study a referential game (a type of signaling game) where two agents communicate with each other via a discrete bottleneck to achieve a common goal. In our referential game, the…

cs.CV2020

FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition

Vinoj Jayasundara, Debaditya Roy, Basura Fernando

Capsule networks (CapsNets) have recently shown promise to excel in most computer vision tasks, especially pertaining to scene understanding. In this paper, we explore CapsNet's ca…

cs.LG2019

Device-Free User Authentication, Activity Classification and Tracking using Passive Wi-Fi Sensing: A Deep Learning Based Approach

Vinoj Jayasundara, Hirunima Jayasekara, Tharaka Samarasinghe +1

Privacy issues related to video camera feeds have led to a growing need for suitable alternatives that provide functionalities such as user authentication, activity classification…

cs.LG2019★ 2 cited

TimeCaps: Capturing Time Series Data With Capsule Networks

Hirunima Jayasekara, Vinoj Jayasundara, Mohamed Athif +4

Capsule networks excel in understanding spatial relationships in 2D data for vision related tasks. Even though they are not designed to capture 1D temporal relationships, with Time…

cs.LG2019★ 3 cited

TreeCaps: Tree-Structured Capsule Networks for Program Source Code Processing

Vinoj Jayasundara, Nghi Duy Quoc Bui, Lingxiao Jiang +1

Program comprehension is a fundamental task in software development and maintenance processes. Software developers often need to understand a large amount of existing code before t…

cs.SE2019★ 87 cited

SmartEmbed: A Tool for Clone and Bug Detection in Smart Contracts through Structural Code Embedding

Zhipeng Gao, Vinoj Jayasundara, Lingxiao Jiang +3

Ethereum has become a widely used platform to enable secure, Blockchain-based financial and business transactions. However, a major concern in Ethereum is the security of its smart…

cs.CV2019

DeepCaps: Going Deeper with Capsule Networks

Jathushan Rajasegaran, Vinoj Jayasundara, Sandaru Jayasekara +3

Capsule Network is a promising concept in deep learning, yet its true potential is not fully realized thus far, providing sub-par performance on several key benchmark datasets with…

cs.CV2019★ 58 cited

TextCaps : Handwritten Character Recognition with Very Small Datasets

Vinoj Jayasundara, Sandaru Jayasekara, Hirunima Jayasekara +3

Many localized languages struggle to reap the benefits of recent advancements in character recognition systems due to the lack of substantial amount of labeled training data. This…

cs.CV2018★ 15 cited

Combined Static and Motion Features for Deep-Networks Based Activity Recognition in Videos

Sameera Ramasinghe, Jathushan Rajasegaran, Vinoj Jayasundara +3

Activity recognition in videos in a deep-learning setting---or otherwise---uses both static and pre-computed motion components. The method of combining the two components, whilst k…