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Team HPC
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Team HPC

The Human Performance Capture (HPC) team specializes in topics related to the fast and precise tracking of human movement and their interactions with the surroundings from highly constrained input, such as monocular, depth and/or stereo videos. Our objective is to comprehend, simulate, replicate, and assess human performance with a focus on virtual and augmented reality applications.

Recent News

1st Place at the 9th HANDS Workshop Challenge – ARCTIC (ICCV 2025)

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Recent Publications

GHOST: Fast Category-agnostic Hand-Object Interaction Reconstruction from RGB Videos using Gaussian Splatting

Fast-HaMeR: Boosting Hand Mesh Reconstruction using Knowledge Distillation

HandMvNet: Real-Time 3D Hand Pose Estimation Using Multi-View Cross-Attention Fusion

SurgeoNet: Realtime 3D Pose Estimation of Articulated Surgical Instruments from Stereo Images using a Synthetically-trained Network

ShapeGraFormer: GraFormer-Based Network for Hand-Object Reconstruction From a Single Depth Map

THOR-Net: End-to-End Graformer-Based Realistic Two Hands and Object Reconstruction With Self-Supervision

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