activity
20152023
most citedObject Detection in Aerial Images: A Large-Scale Benchmark and Challenges

665 citations · 990 across the 48 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

eess.IV2019★ 1 cited

Deep Neural Network for Fast and Accurate Single Image Super-Resolution via Channel-Attention-based Fusion of Orientation-aware Features

Du Chen, Zewei He, Yanpeng Cao +5

Recently, Convolutional Neural Networks (CNNs) have been successfully adopted to solve the ill-posed single image super-resolution (SISR) problem. A commonly used strategy to boost…

cs.CV2019★ 1 cited

LIP: Learning Instance Propagation for Video Object Segmentation

Ye Lyu, George Vosselman, Gui-Song Xia +1

In recent years, the task of segmenting foreground objects from background in a video, i.e. video object segmentation (VOS), has received considerable attention. In this paper, we…

cs.CV2019

Temporally Consistent Horizon Lines

Florian Kluger, Hanno Ackermann, Michael Ying Yang +1

The horizon line is an important geometric feature for many image processing and scene understanding tasks in computer vision. For instance, in navigation of autonomous vehicles or…

cs.CV2019★ 4 cited

Unsupervised Domain Adaptation for Multispectral Pedestrian Detection

Dayan Guan, Xing Luo, Yanpeng Cao +4

Multimodal information (e.g., visible and thermal) can generate robust pedestrian detections to facilitate around-the-clock computer vision applications, such as autonomous driving…

cs.CV2019★ 3 cited

Robust object extraction from remote sensing data

Sophie Crommelinck, Mila Koeva, Michael Ying Yang +1

The extraction of object outlines has been a research topic during the last decades. In spite of advances in photogrammetry, remote sensing and computer vision, this task remains c…

cs.CV2019

Target-Tailored Source-Transformation for Scene Graph Generation

Wentong Liao, Cuiling Lan, Wenjun Zeng +2

Scene graph generation aims to provide a semantic and structural description of an image, denoting the objects (with nodes) and their relationships (with edges). The best performin…