26 citations · 73 across the 12 of their papers we have counts for
8 papers · 1 filter
Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos
Liao Wang, Qiang Hu, Qihan He +5
The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that util…
HumanGen: Generating Human Radiance Fields with Explicit Priors
Suyi Jiang, Haoran Jiang, Ziyu Wang +3
Recent years have witnessed the tremendous progress of 3D GANs for generating view-consistent radiance fields with photo-realism. Yet, high-quality generation of human radiance fie…
Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objects
Ziyu Wang, Yu Deng, Jiaolong Yang +2
3D-aware generative models have demonstrated their superb performance to generate 3D neural radiance fields (NeRF) from a collection of monocular 2D images even for topology-varyin…
MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging
Ziyu Wang, Liao Wang, Fuqiang Zhao +3
Photo-realistic neural reconstruction and rendering of the human portrait are critical for numerous VR/AR applications. Still, existing solutions inherently rely on multi-view capt…
Geodesic-HOF: 3D Reconstruction Without Cutting Corners
Ziyun Wang, Eric A. Mitchell, Volkan Isler +1
Single-view 3D object reconstruction is a challenging fundamental problem in computer vision, largely due to the morphological diversity of objects in the natural world. In particu…
EventGAN: Leveraging Large Scale Image Datasets for Event Cameras
Alex Zihao Zhu, Ziyun Wang, Kaung Khant +1
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, t…
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks
Ziyun Wang, Volkan Isler, Daniel D. Lee
We address the problem of generating a high-resolution surface reconstruction from a single image. Our approach is to learn a Higher Order Function (HOF) which takes an image of an…
Motion Equivariance OF Event-based Camera Data with the Temporal Normalization Transform
Ziyun Wang
In this work, we focus on using convolution neural networks (CNN) to perform object recognition on the event data. In object recognition, it is important for a neural network to be…