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20192023
most citedRSGPT: A Remote Sensing Vision Language Model and Benchmark

36 citations · 40 across the 3 of their papers we have counts for

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6 papers · 1 filter

cs.CV20231 cited

AutoEncoding Tree for City Generation and Applications

Wenyu Han, Congcong Wen, Lazarus Chok +4

City modeling and generation have attracted an increased interest in various applications, including gaming, urban planning, and autonomous driving. Unlike previous works focused o…

cs.CV202336 cited

RSGPT: A Remote Sensing Vision Language Model and Benchmark

Yuan Hu, Jianlong Yuan, Congcong Wen +2

The emergence of large-scale large language models, with GPT-4 as a prominent example, has significantly propelled the rapid advancement of artificial general intelligence and spar…

cs.CV2023

Vision-Language Models in Remote Sensing: Current Progress and Future Trends

Xiang Li, Congcong Wen, Yuan Hu +2

The remarkable achievements of ChatGPT and GPT-4 have sparked a wave of interest and research in the field of large language models for Artificial General Intelligence (AGI). These…

cs.CV2021

Fooling LiDAR Perception via Adversarial Trajectory Perturbation

Yiming Li, Congcong Wen, Felix Juefei-Xu +1

LiDAR point clouds collected from a moving vehicle are functions of its trajectories, because the sensor motion needs to be compensated to avoid distortions. When autonomous vehicl…

cs.CV20203 cited

Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network

Congcong Wen, Xiang Li, Xiaojing Yao +2

Airborne light detection and ranging (LiDAR) plays an increasingly significant role in urban planning, topographic mapping, environmental monitoring, power line detection and other…

cs.CV2019

Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification

Congcong Wen, Lina Yang, Ling Peng +2

Point cloud classification plays an important role in a wide range of airborne light detection and ranging (LiDAR) applications, such as topographic mapping, forest monitoring, pow…