2 citations · 2 across the 4 of their papers we have counts for
4 papers
Self-Intersection-Aware 3D Human Motion Generation Using an Efficient Human Sphere Proxy
Pascal Herrmann, Maarten Bieshaar, Dennis Mack +2
Human motion generation has made tremendous progress in recent years, with state-of-the-art approaches surpassing ground truth data in leading evaluation benchmarks. However, visua…
LC-SLab -- An object-based deep learning framework for large-scale land cover classification from satellite imagery and sparse in-situ labels
Johannes Leonhardt, Juergen Gall, Ribana Roscher
Large-scale land cover maps generated using deep learning play a critical role across a wide range of Earth science applications. Open in-situ datasets from principled land cover s…
Massively Multi-Person 3D Human Motion Forecasting with Scene Context
Felix B Mueller, Julian Tanke, Juergen Gall
Forecasting long-term 3D human motion is challenging: the stochasticity of human behavior makes it hard to generate realistic human motion from the input sequence alone. Informatio…
Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models
Jifeng Wang, Kaouther Messaoud, Yuejiang Liu +2
Recent advancements in motion forecasting have been significantly accelerated by self-supervised pre-training techniques. However, current methods typically rely on extensive fine-…