Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain
complex phenomena such as thin structures, evolving topology, translucency, scattering …

We propose DeepHuman, an image-guided volume-to-volume translation CNN for 3D
human reconstruction from a single RGB image. To reduce the ambiguities associated with …

While the ready availability of 3D scan data has influenced research throughout computer
vision, less attention has focused on 4D data; that is 3D scans of moving non-rigid objects …

We present a learning‐based approach for virtual try‐on applications based on a fully
convolutional graph neural network. In contrast to existing data‐driven models, which are …

The commoditization of virtual and augmented reality devices and the availability of
inexpensive consumer depth cameras have catalyzed a resurgence of interest in …

In recent years, traffic flow prediction has been extensively explored in Intelligent
Transportation Systems, which is beneficial for reducing traffic jams and accidents as well as …

In this paper, we propose a controllable high-quality free viewpoint video generation method
based on the motion graph and neural radiance fields (NeRF). Different from existing pose …

In this paper we propose a framework for spatially and temporally coherent semantic co-
segmentation and reconstruction of complex dynamic scenes from multiple static or moving …

Conformal parameterizations over the sphere provide high‐quality maps between genus
zero surfaces, and are essential for applications such as data transfer and comparative …

We convert a sequence of unstructured textured meshes into a mesh with incrementally
changing connectivity and atlas parameterization. Like prior work on surface tracking, we …