33 citations · 67 across the 23 of their papers we have counts for
5 papers · 1 filter
Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
Zhihong Liu, Xin Xu, Peng Qiao +1
Deep reinforcement learning has led to dramatic breakthroughs in the field of artificial intelligence for the past few years. As the amount of rollout experience data and the size…
VoxNeuS: Enhancing Voxel-Based Neural Surface Reconstruction via Gradient Interpolation
Sidun Liu, Peng Qiao, Zongxin Ye +2
Neural Surface Reconstruction learns a Signed Distance Field~(SDF) to reconstruct the 3D model from multi-view images. Previous works adopt voxel-based explicit representation to i…
DistGrid: Scalable Scene Reconstruction with Distributed Multi-resolution Hash Grid
Sidun Liu, Peng Qiao, Zongxin Ye +2
Neural Radiance Field~(NeRF) achieves extremely high quality in object-scaled and indoor scene reconstruction. However, there exist some challenges when reconstructing large-scale…
AbsGS: Recovering Fine Details for 3D Gaussian Splatting
Zongxin Ye, Wenyu Li, Sidun Liu +2
3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanc…
TFDMNet: A Novel Network Structure Combines the Time Domain and Frequency Domain Features
Hengyue Pan, Yixin Chen, Zhiliang Tian +3
Convolutional neural network (CNN) has achieved impressive success in computer vision during the past few decades. The image convolution operation helps CNNs to get good performanc…