Realistic human-centric rendering plays a key role in both computer vision and computer
graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing …

This paper addresses the challenge of efficiently reconstructing volumetric videos of
dynamic humans from sparse multi-view videos. Some recent works represent a dynamic …

Humans constantly interact with objects in daily life tasks. Capturing such processes and
subsequently conducting visual inferences from a fixed viewpoint suffers from occlusions …

We introduce HOSNeRF, a novel 360deg free-viewpoint rendering method that reconstructs
neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild …

We explore the task of embodied view synthesis from monocular videos of deformable
scenes. Given a minute-long RGBD video of people interacting with their pets, we render the …

Recently, the editing of neural radiance fields (NeRFs) has gained considerable attention,
but most prior works focus on static scenes while research on the appearance editing of …

In this paper we present a method to reconstruct the world and multiple dynamic humans in
3D from a monocular video input. As a key idea we represent both the world and multiple …

The realistic fusion of human bodies and virtual lighting environments has important
application value in digital tourism, virtual conferences, and other fields. To achieve this …

We present MultiPly a novel framework to reconstruct multiple people in 3D from monocular
in-the-wild videos. Reconstructing multiple individuals moving and interacting naturally from …

Capturing the 3D human body is one of the important tasks in computer vision with a wide
range of applications such as virtual reality and sports analysis. However conventional …