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Building Damage Assessment

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하위 태스크: 0
평가표: 1
보존된 평가 기록: 7

Predicting building damage levels from earth observation data

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/DIUx-xView/xview2-baseline

공식 코드

xBD: A Dataset for Assessing Building Damage from Satellite Imagery

https://github.com/Henryjiepanli/Building-Guided-Pseudo-Label-Learning-for-Cross-Modal-Building-Damage-Mapping

공식 코드

Building-Guided Pseudo-Label Learning for Cross-Modal Building Damage Mapping

https://github.com/ShaneShen/BDANet-Building-Damage-Assessment

공식 코드

BDANet: Multiscale Convolutional Neural Network with Cross-directional Attention for Building Damage Assessment from Satellite Images

https://github.com/TManzini/NowYouSeeItNowYouDont

공식 코드

Now you see it, Now you don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery

https://github.com/YimingXiao98/DamageCAT

공식 코드

DamageCAT: A Deep Learning Transformer Framework for Typology-Based Post-Disaster Building Damage Categorization

https://github.com/bloodaxe/xview2-solution

공식 코드

Fully convolutional Siamese neural networks for buildings damage assessment from satellite images

https://github.com/chenhongruixuan/bright

공식 코드

BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response

https://github.com/chenhongruixuan/mambacd

공식 코드

ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model

https://github.com/ethanweber/xview2

공식 코드

Building Disaster Damage Assessment in Satellite Imagery with Multi-Temporal Fusion

https://github.com/fzmi/ubdd

공식 코드

Learning Efficient Unsupervised Satellite Image-based Building Damage Detection

https://github.com/nka77/dahitra

공식 코드

Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Images

https://github.com/qcao10/DamageDetection

공식 코드

Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural Networks

https://github.com/violayhho/flood-damagesense

공식 코드

Flood-DamageSense: Multimodal Mamba with Multitask Learning for Building Flood Damage Assessment using SAR Remote Sensing Imagery

https://github.com/xia-zs/SSLBDA

공식 코드

Self-Supervised Learning for Building Damage Assessment from Large-scale xBD Satellite Imagery Benchmark Datasets

https://github.com/zhuduowang/Change3D

공식 코드

Change3D: Revisiting Change Detection and Captioning from A Video Modeling Perspective

https://gitlab.com/awadailab/sage-project

공식 코드

Towards Cross-Disaster Building Damage Assessment with Graph Convolutional Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.