74 citations · 216 across the 38 of their papers we have counts for
6 papers · 1 filter
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training
Yifan Jiang, Peter Hedman, Ben Mildenhall +4
Neural Radiance Fields (NeRFs) are a powerful representation for modeling a 3D scene as a continuous function. Though NeRF is able to render complex 3D scenes with view-dependent e…
NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views
Dejia Xu, Yifan Jiang, Peihao Wang +3
Virtual reality and augmented reality (XR) bring increasing demand for 3D content. However, creating high-quality 3D content requires tedious work that a human expert must do. In t…
NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes
Zhiwen Fan, Peihao Wang, Yifan Jiang +3
Neural volumetric representations have shown the potential that Multi-layer Perceptrons (MLPs) can be optimized with multi-view calibrated images to represent scene geometry and ap…
Signal Processing for Implicit Neural Representations
Dejia Xu, Peihao Wang, Yifan Jiang +2
Implicit Neural Representations (INRs) encoding continuous multi-media data via multi-layer perceptrons has shown undebatable promise in various computer vision tasks. Despite many…
Unified Implicit Neural Stylization
Zhiwen Fan, Yifan Jiang, Peihao Wang +3
Representing visual signals by implicit representation (e.g., a coordinate based deep network) has prevailed among many vision tasks. This work explores a new intriguing direction:…
SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image
Dejia Xu, Yifan Jiang, Peihao Wang +3
Despite the rapid development of Neural Radiance Field (NeRF), the necessity of dense covers largely prohibits its wider applications. While several recent works have attempted to…