2 citations · 3 across the 2 of their papers we have counts for
8 papers
UniFuse: Unidirectional Fusion for 360 Panorama Depth Estimation
Hualie Jiang, Zhe Sheng, Siyu Zhu +2
Learning depth from spherical panoramas is becoming a popular research topic because a panorama has a full field-of-view of the environment and provides a relatively complete descr…
MeshMVS: Multi-View Stereo Guided Mesh Reconstruction
Rakesh Shrestha, Zhiwen Fan, Qingkun Su +3
Deep learning based 3D shape generation methods generally utilize latent features extracted from color images to encode the semantics of objects and guide the shape generation proc…
Self-Supervised Human Depth Estimation from Monocular Videos
Feitong Tan, Hao Zhu, Zhaopeng Cui +3
Previous methods on estimating detailed human depth often require supervised training with `ground truth' depth data. This paper presents a self-supervised method that can be train…
End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
Lei Li, Siyu Zhu, Hongbo Fu +2
In this work, we propose an end-to-end framework to learn local multi-view descriptors for 3D point clouds. To adopt a similar multi-view representation, existing studies use hand-…
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
Xiaodong Gu, Zhiwen Fan, Zuozhuo Dai +3
The deep multi-view stereo (MVS) and stereo matching approaches generally construct 3D cost volumes to regularize and regress the output depth or disparity. These methods are limit…
A Neural Network for Detailed Human Depth Estimation from a Single Image
Sicong Tang, Feitong Tan, Kelvin Cheng +3
This paper presents a neural network to estimate a detailed depth map of the foreground human in a single RGB image. The result captures geometry details such as cloth wrinkles, wh…