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20162024
most citedRelation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection

45 citations · 115 across the 27 of their papers we have counts for

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Showing 2019 · cs.CVShow all

5 papers · 2 filters

cs.CV2019★ 8 cited

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

Yiyi Zhou, Rongrong Ji, Gen Luo +5

Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description. Most ex…

cs.CV2019

Learning Rate Dropout

Huangxing Lin, Weihong Zeng, Xinghao Ding +3

The performance of a deep neural network is highly dependent on its training, and finding better local optimal solutions is the goal of many optimization algorithms. However, exist…

cs.CV2019

Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images

Jiexiang Wang, Cheng Bian, Meng Li +6

Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases. However, because of…

cs.CV2019★ 18 cited

Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes

Chengquan Zhang, Borong Liang, Zuming Huang +4

Previous scene text detection methods have progressed substantially over the past years. However, limited by the receptive field of CNNs and the simple representations like rectang…

cs.CV2019

Rain O'er Me: Synthesizing real rain to derain with data distillation

Huangxing Lin, Yanlong Li, Xinghao Ding +3

We present a supervised technique for learning to remove rain from images without using synthetic rain software. The method is based on a two-stage data distillation approach: 1) A…