71 citations · 432 across the 57 of their papers we have counts for
20 papers · 1 filter
Efficient Semantic Splatting for Remote Sensing Multi-view Segmentation
Zipeng Qi, Hao Chen, Haotian Zhang +2
In this paper, we propose a novel semantic splatting approach based on Gaussian Splatting to achieve efficient and low-latency. Our method projects the RGB attributes and semantic…
Remote Sensing SpatioTemporal Vision-Language Models: A Comprehensive Survey
Chenyang Liu, Jiafan Zhang, Keyan Chen +3
The interpretation of multi-temporal remote sensing imagery is critical for monitoring Earth's dynamic processes-yet previous change detection methods, which produce binary or sema…
Joint-Optimized Unsupervised Adversarial Domain Adaptation in Remote Sensing Segmentation with Prompted Foundation Model
Shuchang Lyu, Qi Zhao, Guangliang Cheng +4
Unsupervised Domain Adaptation for Remote Sensing Semantic Segmentation (UDA-RSSeg) addresses the challenge of adapting a model trained on source domain data to target domain sampl…
Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes
Jianqi Chen, Panwen Hu, Xiaojun Chang +3
Recent advancements in human motion synthesis have focused on specific types of motions, such as human-scene interaction, locomotion or human-human interaction, however, there is a…
Exploring Fine-Grained Image-Text Alignment for Referring Remote Sensing Image Segmentation
Sen Lei, Xinyu Xiao, Tianlin Zhang +3
Given a language expression, referring remote sensing image segmentation (RRSIS) aims to identify ground objects and assign pixel-wise labels within the imagery. The one of key cha…
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling
Zili Liu, Hao Chen, Lei Bai +4
In an era of frequent extreme weather and global warming, obtaining precise, fine-grained near-surface weather forecasts is increasingly essential for human activities. Downscaling…
Towards Optimal Aggregation of Varying Range Dependencies in Haze Removal
Xiaozhe Zhang, Fengying Xie, Haidong Ding +2
Haze removal aims to restore a clear image from a hazy input. Existing methods achieve notable success by specializing in either short-range dependencies to preserve local details…
Learning at a Glance: Towards Interpretable Data-limited Continual Semantic Segmentation via Semantic-Invariance Modelling
Bo Yuan, Danpei Zhao, Zhenwei Shi
Continual semantic segmentation (CSS) based on incremental learning (IL) is a great endeavour in developing human-like segmentation models. However, current CSS approaches encounte…
Semantic-CC: Boosting Remote Sensing Image Change Captioning via Foundational Knowledge and Semantic Guidance
Yongshuo Zhu, Lu Li, Keyan Chen +3
Remote sensing image change captioning (RSICC) aims to articulate the changes in objects of interest within bi-temporal remote sensing images using natural language. Given the limi…
Open-CD: A Comprehensive Toolbox for Change Detection
Kaiyu Li, Jiawei Jiang, Andrea Codegoni +13
We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of…
A Late-Stage Bitemporal Feature Fusion Network for Semantic Change Detection
Chenyao Zhou, Haotian Zhang, Han Guo +2
Semantic change detection is an important task in geoscience and earth observation. By producing a semantic change map for each temporal phase, both the land use land cover categor…
CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection
Haotian Zhang, Keyan Chen, Chenyang Liu +3
Recently, the Mamba architecture based on state space models has demonstrated remarkable performance in a series of natural language processing tasks and has been rapidly applied t…
RSCaMa: Remote Sensing Image Change Captioning with State Space Model
Chenyang Liu, Keyan Chen, Bowen Chen +3
Remote Sensing Image Change Captioning (RSICC) aims to describe surface changes between multi-temporal remote sensing images in language, including the changed object categories, l…
MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation
Zhiping Yu, Chenyang Liu, Liqin Liu +2
The recent advancement of generative foundational models has ushered in a new era of image generation in the realm of natural images, revolutionizing art design, entertainment, env…
MarsSeg: Mars Surface Semantic Segmentation with Multi-level Extractor and Connector
Junbo Li, Keyan Chen, Gengju Tian +2
The segmentation and interpretation of the Martian surface play a pivotal role in Mars exploration, providing essential data for the trajectory planning and obstacle avoidance of r…
RSMamba: Remote Sensing Image Classification with State Space Model
Keyan Chen, Bowen Chen, Chenyang Liu +3
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements…
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
Chenyang Liu, Keyan Chen, Haotian Zhang +3
Monitoring changes in the Earth's surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Re…
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu, Hao Chen, Lei Bai +6
Downscaling (DS) of meteorological variables involves obtaining high-resolution states from low-resolution meteorological fields and is an important task in weather forecasting. Pr…
Learning to detect cloud and snow in remote sensing images from noisy labels
Zili Liu, Hao Chen, Wenyuan Li +5
Detecting clouds and snow in remote sensing images is an essential preprocessing task for remote sensing imagery. Previous works draw inspiration from semantic segmentation models…
DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling
Wenyuan Li, Zili Liu, Keyan Chen +4
Accurate weather forecasting holds significant importance to human activities. Currently, there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and De…