Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …

Active simultaneous localization and mapping (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …

We address the problem of synthesizing novel views from a monocular video depicting a
complex dynamic scene. State-of-the-art methods based on temporally varying Neural …

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 a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision
and graphics. Recently Gaussian splatting has emerged as a robust technique to represent …

Neural Radiance Fields (NeRF) are able to reconstruct scenes with unprecedented fidelity,
and various recent works have extended NeRF to handle dynamic scenes. A common …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

We present a method that simultaneously addresses the tasks of dynamic scene novel-view
synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We …

This paper addresses the challenge of reconstructing an animatable human model from a
multi-view video. Some recent works have proposed to decompose a non-rigidly deforming …