Zizhuang Wei

Peking University | PKU · School of Electronic and Computer Engineering

Recently, deep learning based multi-view stereo (MVS) networks have demonstrated their excellent performance on various benchmarks. In this paper, we present an effective and efficient recurrent neural network (RNN) for accurate and complete dense point cloud reconstruction. Instead of regularizing the cost volume via conventional 3D CNN or unidire...

In this paper, we present a novel recurrent multi-view stereo network based on long short-term memory (LSTM) with adaptive aggregation, namely AA-RMVSNet. We firstly introduce an intra-view aggregation module to adaptively extract image features by using context-aware convolution and multi-scale aggregation, which efficiently improves the performan...

In this paper, we propose an effective and efficient pyramid multi-view stereo (MVS) net with self-adaptive view aggregation for accurate and complete dense point cloud reconstruction. Different from using mean square variance to generate cost volume in previous deep-learning based MVS methods, our VA-MVSNet incorporates the cost variances in diffe...

In this paper, we propose an efficient and effective dense hybrid recurrent multi-view stereo net with dynamic consistency checking, namely \(D^{2}\)HC-RMVSNet, for accurate dense point cloud reconstruction. Our novel hybrid recurrent multi-view stereo net consists of two core modules: 1) a light DRENet (Dense Reception Expanded) module to extract...

In this paper, we propose an efficient and effective dense hybrid recurrent multi-view stereo net with dynamic consistency checking, namely $D^{2}$HC-RMVSNet, for accurate dense point cloud reconstruction. Our novel hybrid recurrent multi-view stereo net consists of two core modules: 1) a light DRENet (Dense Reception Expanded) module to extract de...

Semantic modeling is a challenging task that has received widespread attention in recent years. With the help of mini Unmanned Aerial Vehicles (UAVs), multi-view high-resolution aerial images of large-scale scenes can be conveniently collected. In this paper, we propose a semantic Multi-View Stereo (MVS) method to reconstruct 3D semantic models fro...

In this paper, we propose an effective and efficient pyramid multi-view stereo (MVS) net for accurate and complete dense point cloud reconstruction. Different from existing deep-learning based MVS methods, our VA-MVSNet incorporates the cost variance between different views by introducing two novel self-adaptive view aggregation: pixel-wise view ag...