Search Results for author:
Found 7 papers, 4 papers with code
SpikingNeRF: Making Bio-inspired Neural Networks See through the Real World
In this paper, we propose SpikingNeRF, which aligns the radiance ray with the temporal dimension of SNN, to naturally accommodate the SNN to the reconstruction of Radiance Fields.
Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model
To address these issues, in this work, we propose a low-rank diffusion model for hyperspectral pansharpening by simultaneously leveraging the power of the pre-trained deep diffusion model and better generalization ability of Bayesian methods.
Probability-based Global Cross-modal Upsampling for Pansharpening
Pansharpening is an essential preprocessing step for remote sensing image processing.
$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
Through an in-depth analysis of the topology of GNNs, we observe that the topology of the graph leads to significant differences between nodes, and most of the nodes in a graph appear to have a small aggregation value.
Multi-Task Conditional Imitation Learning for Autonomous Navigation at Crowded Intersections
A multi-task conditional imitation learning framework is proposed to adapt both lateral and longitudinal control tasks for safe and efficient interaction.
Country Image in COVID-19 Pandemic: A Case Study of China
Therefore, in this study, we take China as a specific and typical case and investigate its image with aspect-based sentiment analysis on a large-scale Twitter dataset.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning
Different cost functions of traversability analysis are learned and tested at various scenes of capability in guiding the trajectory planning of different behaviors.
