Robotics and Computer Vision Lab

Publications

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저 자 Tae-Hyun Oh, Kyungdon Joo, Neel Joshi, Baoyuan Wang, In So Kweon, Sing Bing Kang
학 회 IEEE International Conference on Computer Vision (ICCV)
논문일시(Year) 2017
논문일시(Month) 10
Cinemagraphs are a compelling way to convey dynamic aspects of a scene. In these media, dynamic and still elements are juxtaposed to create an artistic and narrative experience. Creating a high-quality, aesthetically pleasing cinemagraph requires isolating objects in a semantically meaningful way and then selecting good start times and looping periods for those objects to minimize visual artifacts (such a tearing). To achieve this, we present a new technique that uses object recognition and semantic segmentation as part of an optimization method to automatically create cinemagraphs from videos that are both visually appealing and semantically meaningful. Given a scene with multiple objects, there are many cinemagraphs one could create. Our method evaluates these multiple candidates and presents the best one, as determined by a model trained to predict human preferences in a collaborative way. We demonstrate the effectiveness of our approach with multiple results and a user study.



We would like to thank all the participants in our user study. We are also grateful to Jian Sun and Jinwoo Shin for the helpful discussions. This work was mostly done while the first author was an intern at Microsoft Research, Redmond. It was completed at KAIST with the support of the Technology Innovation Program (No. 10048320), which is funded by the Korean government (MOTIE).

** The first and second authors contributed equally to this work.

List of Articles
528. VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
Seokju Lee, Junsik Kim, Jae Shin Yoon, Seunghak Shin, Oleksandr Bailo, Namil Kim, Tae-Hee Lee, Hyun Seok Hong, Seung-Hoon Han, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
527. Two-Phase Learning for Weakly Supervised Object Localization
Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
526. Weakly- and Self- Supervised Learning for Content-Aware Deep Image Retargeting
Donghyeon Cho, Jinsun Park, Tae-Hyun Oh, Yu-Wing Tai, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
525. Deltille Grids for Geometric Camera Calibration
Hyowon Ha, Michal Perdoch, Hatem Alismail, In So Kweon, Yaser Sheikh
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
» Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning
Tae-Hyun Oh, Kyungdon Joo, Neel Joshi, Baoyuan Wang, In So Kweon, Sing Bing Kang
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
523. Noise Robust Depth From Focus Using a Ring Difference Filter
Jaeheung Surh, Hae-Gon Jeon, Yunwon Park, Sunghoon Im, Hyowon Ha, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
522. Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks
Jae Shin Yoon, Francois Rameau, Junsik Kim, Seokju Lee, Seunghak Shin, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
521. A Real-Time and Energy-Efficient Embedded System for Intelligent ADAS with RNN-Based Deep Risk Prediction using Stereo Camera
Kyuho Lee, Gyeongmin Choe, Kyeongryeol Bong, Changhyeon Kim, In So Kweon, Hoi-Jun Yoo
International Conference on Computer Vision Systems (ICVS) 2017 / 07
520. A Closed-Form Solution to Rotation Estimation for Structure from Small Motion
Hyowon Ha, Tae-Hyun Oh, In So Kweon
IEEE Signal Processing Letters 2017 / 05
519. Local deformation calibration for autostereoscopic 3D display
Hyoseok Hwang, Hyun Sung Chang, In So Kweon
OSA Optics Express 2017 / 05
518. A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation
Jinsun Park, Yu-Wing Tai, Donghyeon Cho, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
517. Multi-Image Deblurring using Complementary Sets of Fluttering Patterns
Hae-Gon Jeon, Joon-Young Lee, Yudeog Han, Seon Joo Kim, In So Kweon
IEEE Transactions on Image Processing 2017 / 05
516. Light Field Image Super-Resolution using Convolutional Neural Network
Youngjin Yoon, Hae-Gon Jeon, Donggeun Yoo, Joon-Young Lee, In So Kweon
IEEE Signal Processing Letters 2017 / 02
515. Structure-From-Motion in 3D Space Using 2D Lidars
Dong-Geol Choi, Yunsu Bok, Jun-sik Kim, Inwook Shim, In So Kweon
Sensors 2017 / 02
514. Deep Representation of Industrial Components using Simulated Images
Seong-Heum Kim, Gyeongmin Choe, Byungtae Ahn, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2017 / 05
513. 3D Display Calibration by Visual Pattern Analysis
Hyoseok Hwang, Hyun Sung Chang, Dongkyung Nam, In So Kweon
IEEE Transactions on Image Processing (TIP), accepted 2017 / 02
512. Single Image Depth Estimation using Convolutional Neural Networks with NCC-based Loss
Jinsun Park, In So Kweon
International Workshop on Frontiers of Computer Vision (FCV) 2017 / 02
511. Robust Road Marking Detection and Recognition Using Density-Based Grouping and Machine Learning Techniques
Oleksandr Bailo, Seokju Lee, Francois Rameau, Jae Shin Yoon, In So Kweon
Winter Conference of Applications on Computer Vision (WACV) 2017 / 03
510. Robot System of DRC‐HUBO+ and Control Strategy of Team KAIST in DARPA Robotics Challenge Finals
Jeongsoo Lim, Inho Lee, Inwook Shim, Hyobin Jung, Hyun Min Joe, Hyoin Bae, Okkee Sim, Jaesung Oh, Taejin Jung, Seunghak Shin, Kyungdon Joo, Mingeuk Kim, Kangkyu Lee, Yunsu Bok, Dong-Geol Choi, Buyoun Cho, Sungwoo Kim, Jungwoo Heo, Inhyeok Kim, Jungho Lee, In So Kweon, Jun‐Ho Oh
Journal of Field Robotics 2016 / 09
509. Control strategies for a humanoid robot to drive and then egress a utility vehicle for remote approach
Hyobin Jeong, Jaesung Oh, Mingeuk Kim, Kyungdon Joo, In So Kweon, Jun-Ho Oh
IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids) 2015 / 11
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