Search Results for author:
Found 19 papers, 14 papers with code
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model
We also propose several ongoing derivatives for instance segmentation tasks, drawing on recent advancements within the SAM community, and compare their performance with RSPrompter.
Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection
Change detection, a prominent research area in remote sensing, is pivotal in observing and analyzing surface transformations.
Ranked #6 on
Change Detection
on LEVIR-CD
RSMamba: Remote Sensing Image Classification with State Space Model
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation.
Diffusion Models for Imperceptible and Transferable Adversarial Attack
Many existing adversarial attacks generate $L_p$-norm perturbations on image RGB space.
OvarNet: Towards Open-vocabulary Object Attribute Recognition
In this paper, we consider the problem of simultaneously detecting objects and inferring their visual attributes in an image, even for those with no manual annotations provided at the training stage, resembling an open-vocabulary scenario.
Ranked #1 on
Open Vocabulary Attribute Detection
on OVAD benchmark
(using extra training data)
Zero-Shot Image Harmonization with Generative Model Prior
Initially, we employ a pretrained vision-language model (VLM) to generate descriptions for the composite image.
Building Extraction from Remote Sensing Images with Sparse Token Transformers
Deep learning methods have achieved considerable progress in remote sensing image building extraction.
Building change detection for remote sensing images
Extracting Buildings In Remote Sensing Images
Dense Pixel-to-Pixel Harmonization via Continuous Image Representation
High-resolution (HR) image harmonization is of great significance in real-world applications such as image synthesis and image editing.
Ranked #8 on
Image Harmonization
on iHarmony4
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
The Change-Agent integrates a multi-level change interpretation (MCI) model as the eyes and a large language model (LLM) as the brain.
Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function Space
Despite its fruitful applications in remote sensing, image super-resolution is troublesome to train and deploy as it handles different resolution magnifications with separate models.
Continuous Cross-resolution Remote Sensing Image Change Detection
Toward continuous cross-resolution CD, we propose scale-invariant learning to enforce the model consistently predicting HR results given synthesized samples of varying resolution differences.
Geographical Knowledge-driven Representation Learning for Remote Sensing Images
The proliferation of remote sensing satellites has resulted in a massive amount of remote sensing images.
DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling
Next, we construct hyper-networks based on deep learning methods to directly learn weather patterns from a large amount of meteorological data.
Object Detection in 20 Years: A Survey
Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years.
Reconstruction of Cardiac Cine MRI under Free-breathing using Motion-guided Deformable Alignment and Multi-resolution Fusion
On the ACMRI dataset, the results are SSIM of 87. 65%$\pm$4. 20%, PSNR of 30. 04$\pm$1. 18 dB, and NMSE of 0. 0473$\pm$0. 0072.
Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change Captioning
The existing methods for Remote Sensing Image Change Captioning (RSICC) perform well in simple scenes but exhibit poorer performance in complex scenes.
Learning to detect cloud and snow in remote sensing images from noisy labels
This paper is the first to consider the impact of label noise on the detection of clouds and snow in remote sensing images.
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
In this paper, we extend meteorological downscaling to arbitrary scattered station scales, establish a brand new benchmark and dataset, and retrieve meteorological states at any given station location from a coarse-resolution meteorological field.
MarsSeg: Mars Surface Semantic Segmentation with Multi-level Extractor and Connector
The Mini-ASPP and PSA are specifically designed for shadow feature enhancement, thereby enabling the expression of local details and small objects.
