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20192023
most citedA Survey of Deep Learning-based Object Detection

1.3k citations · 1.5k across the 18 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022★ 11 cited

Enhancing Deformable Convolution based Video Frame Interpolation with Coarse-to-fine 3D CNN

Duolikun Danier, Fan Zhang, David Bull

This paper presents a new deformable convolution-based video frame interpolation (VFI) method, using a coarse to fine 3D CNN to enhance the multi-flow prediction. This model first…

cs.CV2021★ 48 cited

ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation

Duolikun Danier, Fan Zhang, David Bull

Video frame interpolation (VFI) is currently a very active research topic, with applications spanning computer vision, post production and video encoding. VFI can be extremely chal…

cs.CV2021★ 1 cited

Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases

Xiao Huang, Di Zhu, Fan Zhang +3

The rapid development of remote sensing techniques provides rich, large-coverage, and high-temporal information of the ground, which can be coupled with the emerging deep learning…

cs.CV2020★ 1 cited

A simulation environment for drone cinematography

Fan Zhang, David Hall, Tao Xu +2

In this paper, we present a workflow for the simulation of drone operations exploiting realistic background environments constructed within Unreal Engine 4 (UE4). Methods for envir…

cs.CV2020★ 8 cited

MultiResolution Attention Extractor for Small Object Detection

Fan Zhang, Licheng Jiao, Lingling Li +2

Small objects are difficult to detect because of their low resolution and small size. The existing small object detection methods mainly focus on data preprocessing or narrowing th…

cs.CV2019★ 1.3k cited

A Survey of Deep Learning-based Object Detection

Licheng Jiao, Fan Zhang, Fang Liu +4

Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in peoples life, such as monitoring security, autonomous dr…