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20162023
most citedNatural Language Guided Visual Relationship Detection

23 citations · 70 across the 24 of their papers we have counts for

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Showing 2020 · cs.CVShow all

11 papers · 2 filters

cs.CV2020

Self-supervised monocular depth estimation from oblique UAV videos

Logambal Madhuanand, Francesco Nex, Michael Ying Yang

UAVs have become an essential photogrammetric measurement as they are affordable, easily accessible and versatile. Aerial images captured from UAVs have applications in small and l…

cs.CV2020★ 1 cited

LGENet: Local and Global Encoder Network for Semantic Segmentation of Airborne Laser Scanning Point Clouds

Yaping Lin, George Vosselman, Yanpeng Cao +1

Interpretation of Airborne Laser Scanning (ALS) point clouds is a critical procedure for producing various geo-information products like 3D city models, digital terrain models and…

cs.CV2020

Real-time Semantic Segmentation with Context Aggregation Network

Michael Ying Yang, Saumya Kumaar, Ye Lyu +1

With the increasing demand of autonomous systems, pixelwise semantic segmentation for visual scene understanding needs to be not only accurate but also efficient for potential real…

cs.CV2020

Exploring Dynamic Context for Multi-path Trajectory Prediction

Hao Cheng, Wentong Liao, Xuejiao Tang +3

To accurately predict future positions of different agents in traffic scenarios is crucial for safely deploying intelligent autonomous systems in the real-world environment. Howeve…

cs.CV2020

On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID

Yang Long, Gui-Song Xia, Shengyang Li +5

The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there…

cs.CV2020

AMENet: Attentive Maps Encoder Network for Trajectory Prediction

Hao Cheng, Wentong Liao, Michael Ying Yang +2

Trajectory prediction is critical for applications of planning safe future movements and remains challenging even for the next few seconds in urban mixed traffic. How an agent move…