Tadanori Hirano

Papers

Total Citations

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About

Tadanori Hirano is a researcher whose work lies at the intersection of computer vision and robotics, with a particular focus on 6D object pose estimation—a critical capability for enabling robots to perceive and interact with their environment. His most influential contribution, "Iterative Coarse-to-Fine 6D-Pose Estimation Using Back-propagation" (2021), introduces a novel method that estimates an object’s full 3D position and orientation from a single RGB image, specifically designed for robotic grasping tasks. Unlike many deep learning approaches that falter when faced with variations in object appearance or viewpoint, Hirano’s technique leverages an iterative, coarse-to-fine refinement process using back-propagation, making it more robust to real-world changes. While still early in its citation impact (5 citations), this work addresses a fundamental challenge in robotics: enabling machines to reliably locate and manipulate objects in unstructured environments. Hirano’s research is particularly valuable for students and engineers working on autonomous systems, as it bridges the gap between theoretical pose estimation and practical deployment in robotic manipulation. His contributions highlight the ongoing need for methods that combine accuracy with adaptability in vision-based robotics.