The advent of affordable consumer grade RGB‐D cameras has brought about a profound
advancement of visual scene reconstruction methods. Both computer graphics and …

Implicit neural representation has paved the way for new approaches to dynamic scene
reconstruction. Nonetheless cutting-edge dynamic neural rendering methods rely heavily on …

We present Tensor4D, an efficient yet effective approach to dynamic scene modeling. The
key of our solution is an efficient 4D tensor decomposition method so that the dynamic scene …

We present the first method capable of photorealistically reconstructing deformable scenes
using photos/videos captured casually from mobile phones. Our approach augments neural …

We propose a novel approach for 3D video synthesis that is able to represent multi-view
video recordings of a dynamic real-world scene in a compact, yet expressive representation …

Accurately and efficiently modeling dynamic scenes and motions is considered so
challenging a task due to temporal dynamics and motion complexity. To address these …

Coordinate-based volumetric representations have the potential to generate photo-realistic
virtual avatars from images. However, virtual avatars need to be controllable and be …

We present the first dense SLAM system capable of reconstructing non-rigidly deforming
scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our …

We present a novel approach for the reconstruction of dynamic geometric shapes using a
single hand-held consumer-grade RGB-D sensor at real-time rates. Our method builds up …

We propose a novel learnable representation for detail preserving shape deformation. The
goal of our method is to warp a source shape to match the general structure of a target …