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Filip Maric

5 accepted papers

2026

EgoPoseFormer v2: Accurate Egocentric Human Motion Estimation for AR/VR

CVPR 2026

Egocentric 3D human motion estimation is essential for AR/VR experiences, yet remains challenging due to limited body coverage from the egocentric viewpoint, frequent occlusions, and scarce labeled data. We present EgoPoseFormer v2, a method that addresses these challenges through two key contributi

Cited by 2SourceScholar
2024

GISR: Geometric Initialization and Silhouette-Based Refinement for Single-View Robot Pose and Configuration Estimation

RA-L 2024

In autonomous robotics, measurement of the robot's internal state and perception of its environment, including interaction with other agents such as collaborative robots, are essential. Estimating the pose of the robot arm from a single view has the potential to replace classical eye-to-hand calibra

Cited by 1SourceScholar
2023

CIDGIKc: Distance-Geometric Inverse Kinematics for Continuum Robots

RA-L 2023

The small size, high dexterity, and intrinsic compliance of continuum robots (CRs) make them well suited for constrained environments. Solving the inverse kinematics (IK), that is finding robot joint configurations that satisfy desired position or pose queries, is a fundamental challenge in motion p

Cited by 8SourceScholar
2022

Convex Iteration for Distance-Geometric Inverse Kinematics

RA-L 2022

Inverse kinematics (IK) is the problem of finding robot joint configurations that satisfy constraints on the position or pose of one or more end-effectors. For robots with redundant degrees of freedom, there is often an infinite, nonconvex set of solutions. The IK problem is further complicated when

Cited by 31SourcecodeScholar
2020

Heteroscedastic Uncertainty for Robust Generative Latent Dynamics

RA-L 2020

Learning or identifying dynamics from a sequence of high-dimensional observations is a difficult challenge in many domains, including reinforcement learning, and control. The problem has recently been studied from a generative perspective through latent dynamics: high-dimensional observations are em

Cited by 9SourcecodeScholar