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20152020
most citedUnsupervised Learning of Geometry with Edge-aware Depth-Normal Consistency

105 citations · 144 across the 10 of their papers we have counts for

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Showing 2018Show all

20 papers · 1 filter

cs.MM2018

ADNet: A Deep Network for Detecting Adverts

Murhaf Hossari, Soumyabrata Dev, Matthew Nicholson +6

Online video advertising gives content providers the ability to deliver compelling content, reach a growing audience, and generate additional revenue from online media. Recently, a…

cs.CL2018

DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction

Shun Zheng, Xu Han, Yankai Lin +5

Pattern-based labeling methods have achieved promising results in alleviating the inevitable labeling noises of distantly supervised neural relation extraction. However, these meth…

cs.CL2018

A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification

Mounica Maddela, Wei Xu

Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity…

cs.CV2018

Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo Videos

Yang Wang, Zhenheng Yang, Peng Wang +3

Learning depth and optical flow via deep neural networks by watching videos has made significant progress recently. In this paper, we jointly solve the two tasks by exploiting the…

cs.DS2018

No Place to Hide: Catching Fraudulent Entities in Tensors

Yikun Ban, Xin Liu, Yitao Duan +2

Many approaches focus on detecting dense blocks in the tensor of multimodal data to prevent fraudulent entities (e.g., accounts, links) from retweet boosting, hashtag hijacking, li…

cs.CV2018

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

Chenxu Luo, Zhenheng Yang, Peng Wang +4

Learning to estimate 3D geometry in a single frame and optical flow from consecutive frames by watching unlabeled videos via deep convolutional network has made significant progres…