3D Object Part Segmentation Using Self-supervised Learning

Last updated on Nov 28, 2023

The project addresses the challenge of 3D object segmentation with limited supervision by incorporating the adaptation of SimCLR contrastive learning into a comprehensive framework. This innovative approach contributes significantly to the advancement of self-supervised learning methods, specifically enhancing the effectiveness of 3D object part segmentation.

Deep Learning Computer Vision Point Clouds Self-supervised Learning SimCLR
Merve Karalı
Merve Karalı
AI Researcher & Data Engineer

Passionate about leveraging technology to drive innovation and solve complex challenges, I am a seasoned professional with expertise in both AI research and data engineering. Holding a Master’s degree in Informatics from Technical University of Munich, my journey has been marked by hands-on experience in crafting and implementing cutting-edge solutions that bridge the realms of artificial intelligence and data-driven insights.