Search Results for author:
Found 9 papers, 4 papers with code
EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answering
Earth vision research typically focuses on extracting geospatial object locations and categories but neglects the exploration of relations between objects and comprehensive reasoning.
Seeing Beyond the Patch: Scale-Adaptive Semantic Segmentation of High-resolution Remote Sensing Imagery based on Reinforcement Learning
This shortcoming poses a significant challenge in processing complex and variable geo-objects, which results in semantic inconsistency in segmentation results.
FarSeg++: Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
Generic semantic segmentation methods mainly focus on the scale variation in natural scenarios.
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection from Multi-Source Satellite Imagery
The objective of the competition is to automatically detect landslides based on large-scale multiple sources of satellite imagery collected globally.
AutoLC: Search Lightweight and Top-Performing Architecture for Remote Sensing Image Land-Cover Classification
Land-cover classification has long been a hot and difficult challenge in remote sensing community.
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
Deep learning approaches have shown promising results in remote sensing high spatial resolution (HSR) land-cover mapping.
Ranked #12 on
Semantic Segmentation
on LoveDA
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery
The small object semantic segmentation task is aimed at automatically extracting key objects from high-resolution remote sensing (HRS) imagery.
Ranked #13 on
Semantic Segmentation
on iSAID
Ajalon: Simplifying the Authoring of Wearable Cognitive Assistants
Wearable Cognitive Assistance (WCA) amplifies human cognition in real time through a wearable device and low-latency wireless access to edge computing infrastructure.
Edge-computing
Human-Computer Interaction
Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
However, general semantic segmentation methods mainly focus on scale variation in the natural scene, with inadequate consideration of the other two problems that usually happen in the large area earth observation scene.
Ranked #18 on
Semantic Segmentation
on iSAID
