Scanline Resolution-invariant Depth Completion using a Single Image and Sparse LiDAR Point Cloud- Author : Kwonyoung Ryu(KAIST), Kang-il Lee (KAIST), Jegyeong Cho (KAIST) and Kuk-Jin Yoon (KAIST) – Published Date : TBD – Category : Depth Completion – Place of publication : IEEE Robotics and Automation Letters (RA-L) 2021 Abstract: Most existing deep learning-based depth completion methods are…
Scanline Resolution-invariant Depth Completion using a Single Image and Sparse LiDAR Point Cloud- Author : 류권영, 조제경, 이강일, 윤국진 – Published Date : 2021/02/03 – Category : Depth Estimation – Place of publication : The 33rd Workshop on Image Processing and Image Understanding (IPIU 2021) Abstract: Most existing deep learning-based depth completion methods are only…
Loop-Net: Joint Unsupervised Disparity and Optical Flow Estimation of Stereo Videos with Spatiotemporal Loop Consistency- Author : Tae-woo Kim, Kwon-young Ryu*, Kyeong-Seob Song*, and Kuk-Jin Yoon ( * : contributed equally) – Published Date : February 5, 2020 – Category : Stereo Matching, Optical flow, Scene Flow – Place of publication : 제32회 영상처리 및…
We have one paper accepted to the IEEE Robotics and Automation Letters (RA-L). The paper is “Loop-Net: Joint Unsupervised Disparity and Optical Flow Estimation of Stereo Videos with Spatiotemporal Loop Consistency” by Taewoo Kim, Kwonyoung Ryu, Kyeongseob Song, and Kuk-Jin Yoon. [Publication Link]
Loop-Net: Joint Unsupervised Disparity and Optical Flow Estimation of Stereo Videos with Spatiotemporal Loop Consistency- Author : Taewoo Kim, Kwonyoung Ryu*, Kyeongseob Song*, and Kuk-Jin Yoon – Published Date : TBD – Category : Stereo Matching, Optical Flow – Place of publication : IEEE Robotics and Automation Letters (RA-L) Abstract: Most of existing deep learning-based depth…