Search Results for author:
Found 7 papers, 4 papers with code
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects
We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene.
DSP-SLAM: Object Oriented SLAM with Deep Shape Priors
We propose DSP-SLAM, an object-oriented SLAM system that builds a rich and accurate joint map of dense 3D models for foreground objects, and sparse landmark points to represent the background.
Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects
In this paper we introduce Co-Fusion, a dense SLAM system that takes a live stream of RGB-D images as input and segments the scene into different objects (using either motion or semantic cues) while simultaneously tracking and reconstructing their 3D shape in real time.
HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion
To close the gap to production-level quality, we introduce HumanRF, a 4D dynamic neural scene representation that captures full-body appearance in motion from multi-view video input, and enables playback from novel, unseen viewpoints.
FroDO: From Detections to 3D Objects
We introduce FroDO, a method for accurate 3D reconstruction of object instances from RGB video that infers object location, pose and shape in a coarse-to-fine manner.
Learning Neural Parametric Head Models
We propose a novel 3D morphable model for complete human heads based on hybrid neural fields.
MonoNPHM: Dynamic Head Reconstruction from Monocular Videos
We present Monocular Neural Parametric Head Models (MonoNPHM) for dynamic 3D head reconstructions from monocular RGB videos.
