cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey
Hirokatsu Kataoka, Soma Shirakabe, Yun He, Shunya Ueta, Teppei Suzuki,, Kaori Abe, Asako Kanezaki, Shin'ichiro Morita, Toshiyuki Yabe, Yoshihiro, Kanehara, Hiroya Yatsuyanagi, Shinya Maruyama, Ryosuke Takasawa, Masataka, Fuchida, Yudai Miyashita, Kazushige Okayasu, Yuta Matsuzaki
TL;DR
This survey reviews over 1,600 papers from major computer vision conferences and journals from 2015-2016, highlighting futuristic challenges and trends in the field.
Contribution
It provides a comprehensive overview of recent advancements and future challenges in computer vision based on an extensive survey of 1,600+ papers.
Findings
Identified key futuristic challenges in computer vision
Summarized recent trends from top conferences and journals
Highlighted emerging research directions
Abstract
The paper gives futuristic challenges disscussed in the cvpaper.challenge. In 2015 and 2016, we thoroughly study 1,600+ papers in several conferences/journals such as CVPR/ICCV/ECCV/NIPS/PAMI/IJCV.
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Taxonomy
TopicsHuman Pose and Action Recognition · Multimodal Machine Learning Applications · Advanced Image and Video Retrieval Techniques