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We would like to congratulate @MohamedAfham14 and his team for the acceptance of their paper CrossPoint at CVPR! πŸŽ‰

CrossPoint learns 3D point cloud features in a self-supervised manner and it achieves state-of-the-art performance in downstream tasks such as 3D object classification, few-shot learning and part segmentation over existing unsupervised learning methods.
Paper link:

Engineering Team
Pasindu Wijesena
Competitive programming enthusiast. Full-stack software engineer. Researcher on music information retrieval techniques with artificial intelligence. Experience in building scalable web and mobile applications, and leading teams to build comprehensive software solutions.
Nandun Yashmika
A programmer, developer who has learned to code through trial and error. Full stack developer with expertise in JS/TS based technologies.
Nishan Wijethunga
Experience in UI/UX and web development.
Sashika Nawarathne
Experience in mobile application development with Flutter and Kotlin, and Machine learning with Python and Tensorflow.
Vidura Dhananjaya
Jack of All Trades, Story Teller, Trainer and Passionate Volunteer.
Chamath Ekanayake
Self-taught graphic designer, pragmatic programmer, and certificated ethical hacker.A diversified individual with knowledge in both physical sciences and business management. Interested in researching the areas of information security and machine learning.
Seniya Dissanayake
A self-taught programmer, Who have experience in react.js web development.
Research Team
Ramith Hettiarachchi
Ramith believes in technology to empower people’s lives. He invests time in technology and volunteering to discover his reason for being. His research interests include Signal Processing , Machine Learning & Computer Vision. He has previously worked as research student at the Robotics and Autonomous Systems Group at CSIRO DATA61
Kithmini Herath
Kithmini's research interests include signal processing, machine learning and Human Computer Interaction. She recently followed a 6-month internship as a Visiting Researcher (Student) in the School of Computer Science within the Faculty of Engineering at the University of Sydney, Australia.
Udith Haputhanthri
Udith Haputhanthri's research interests include Deep Learning, Medical Imaging, Generative Adversarial Networks. He recently published papers related to Generative Adversarial Networks and Biomedical signal processing.
Mohamed Afham
Afham is passionate in Machine Learning and has cutting-edge research experience in Few-Shot Learning, Meta-Learning in Computer Vision. He has won awards in IEEE SMC conference, International Mathematics Competition for University Students and International Mathematics Olympiad.
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