Anastasios Yiannakidis — accepted AI-conference papers

2026

MAMMA: Markerless Accurate Multi-person Motion Acquisition

Hanz Cuevas Velasquez, Anastasios Yiannakidis, Soyong Shin, Giorgio Becherini, Markus Höschle, Joachim Tesch +4

CVPR 2026

We present MAMMA, a markerless motion-capture pipeline that accurately recovers SMPL-X parameters from multi-view video. Traditional motion-capture systems rely on physical markers. Although they offer high accuracy, their requirements of specialized hardware, manual marker placement, and extensive

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2025

BEDLAM2.0: Synthetic humans and cameras in motion

Joachim Tesch, Giorgio Becherini, Prerana Achar, Anastasios Yiannakidis, Muhammed Kocabas, Priyanka Patel +1

NeurIPS 2025oral

Inferring 3D human motion from video remains a challenging problem with many applications. While traditional methods estimate the human in image coordinates, many applications require human motion to be estimated in world coordinates. This is particularly challenging when there is both human and cam…

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2025

Generative Zoo

Tomasz Niewiadomski, Anastasios Yiannakidis, Hanz Cuevas-Velasquez, Soubhik Sanyal, Michael J. Black, Silvia Zuffi +1

ICCV 2025poster

The model-based estimation of 3D animal pose and shape from images enables computational modeling of animal behavior. Training models for this purpose requires large amounts of labeled image data with precise pose and shape annotations. However, capturing such data requires the use of multi-view or…

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