TD-NeRF: Novel Truncated Depth Prior for Joint Camera Pose and Neural Radiance Field Optimization

no code implementations • 11 May 2024 • Zhen Tan, Zongtan Zhou, Yangbing Ge, Zi Wang, Xieyuanli Chen, Dewen Hu

Our approach explicitly utilizes monocular depth priors through three key advancements: 1) we propose a novel depth-based ray sampling strategy based on the truncated normal distribution, which improves the convergence speed and accuracy of pose estimation; 2) to circumvent local minima and refine depth geometry, we introduce a coarse-to-fine training strategy that progressively improves the depth precision; 3) we propose a more robust inter-frame point constraint that enhances robustness against depth noise during training.

Convolutional Neural Networks with A Topographic Representation Module for EEG-Based Brain-Computer Interfaces

no code implementations • 23 Aug 2022 • Xinbin Liang, Yaru Liu, Yang Yu, Kaixuan Liu, Yadong Liu, Zongtan Zhou

Significance: We improve the classification performance of 3 CNNs on 2 datasets by the use of TRM, indicating that it has the capability to mine the EEG spatial topological information.

Classification EEG

Robot Navigation in a Crowd by Integrating Deep Reinforcement Learning and Online Planning

1 code implementation • 26 Feb 2021 • Zhiqian Zhou, Pengming Zhu, Zhiwen Zeng, Junhao Xiao, Huimin Lu, Zongtan Zhou

Deep reinforcement learning is a promising solution to this problem.

reinforcement-learning Reinforcement Learning (RL) +1