Robotics and Computer Vision Lab

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International Conference
2020.07.03 13:52

Non-Local Spatial Propagation Network for Depth Completion

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저 자 Jinsun Park, Kyungdon Joo, Zhe Hu, Chi-Kuei Liu, In So Kweon
학 회 European Conference on Computer Vision (ECCV)
논문일시(Year) 2020
논문일시(Month) 08

In this paper, we propose a robust and efficient end-to-end non-local spatial propagation network for depth completion. The proposed network takes RGB and sparse depth images as inputs and estimates non-local neighbors and their affinities of each pixel, as well as an initial depth map with pixel-wise confidences. The initial depth prediction is then iteratively refined by its confidence and non-local spatial propagation procedure based on the predicted non-local neighbors and corresponding affinities. Unlike previous algorithms that utilize fixed-local neighbors, the proposed algorithm effectively avoids irrelevant local neighbors and concentrates on relevant non-local neighbors during propagation. In addition, we introduce a learnable affinity normalization to better learn the affinity combinations compared to conventional methods. The proposed algorithm is inherently robust to the mixed-depth problem on depth boundaries, which is one of the major issues for existing depth estimation/completion algorithms. Experimental results on indoor and outdoor datasets demonstrate that the proposed algorithm is superior to conventional algorithms in terms of depth completion accuracy and robustness to the mixed-depth problem. Our implementation is publicly available on the project page.

 

Acknowledgement :

This work was partially supported by the National Information Society Agency for construction of training data for artificial intelligence (2100-2131-305-107-19).

 


List of Articles
608. UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging
Chaoning Zhang*, Philipp Benz*, Adil Karjauv*, Geng Sun, In-So Kweon (*: equal-contribution)
NeurIPS, 2020 2020 / 12
607. Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
KwanYong Park, Sanghyun Woo, Inkyu Shin, In So Kweon
NeurIPS, 2020 2020 / 12
606. An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
Kyunghyun Lee, Byeong-Uk Lee, Ukcheol Shin, In So Kweon
NeurIPS, 2020 2020 / 12
605. Align-and-Attend Network for Globally and Locally Coherent Video Inpainting
Sanghyun Woo, Dahun Kim, KwanYong Park, Joon-Young Lee, In So Kweon
British Machine Vision Conference (BMVC) 2020 / 09
604. SideGuide: A Large-scale Sidewalk Dataset for Guiding Impaired People
Kibaek Park*, Youngtaek Oh*, Soomin Ham*, Kyungdon Joo*, HYOKYOUNG KIM, HyoYoung Kum, In So Kweon
IROS, 2020 2020 / 10
603. Two-Phase Pseudo Label Densification for Self-training based Domain Adaptation
Inkyu Shin, Sanghyun Woo, Fei Pan, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
602. Global-and-Local Relative Position Embedding for Unsupervised Video Summarization
Yunjae Jung, Donghyeon Cho, Sanghyun Woo, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
» Non-Local Spatial Propagation Network for Depth Completion
Jinsun Park, Kyungdon Joo, Zhe Hu, Chi-Kuei Liu, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
600. Detecting Human-Object Interactions with Action Co-occurrence Priors
Dong-Jin Kim, Xiao Sun, Jinsoo Choi, Stephen Lin, and In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
599. Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
598. Robust Reference-based Super-Resolution with Similarity-Aware Deformable Convolution
Gyumin Shim, Jinsun Park, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
597. Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations
Chaoning Zhang*, Philipp Benz*, Tooba Imtiaz, In So Kweon (Chaoning Zhang, Philipp Benz are co-first author)
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
596. Video Panoptic Segmentation
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
595. Salient View Selection for Visual Recognition of Industrial Components
Seong-heum Kim, Gyeongmin Choe, Min-Gyu Park, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
594. Linear RGB-D SLAM for Atlanta World
Kyungdon Joo, Tae-Hyun Oh, Francois Rameau, Jean-Charles Bazin and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
593. Globally Optimal Relative Pose Estimation for Camera on a Selfie Stick
Kyungdon Joo, Hongdong Li, Tae-Hyun Oh, Yunsu Bok and and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
592. CNN-based Simultaneous Dehazing and Depth Estimation
Byeong-Uk Lee, Kyunghyun Lee, Jean Oh and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
591. A Simple and Light-weight Attention Module for Convolutional Neural Networks
Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, In-So Kweon
International Journal of Computer Vision (IJCV) 2019 / 12
590. Recurrent Temporal Aggregation Framework for Deep Video Inpainting
Dahun Kim*, Sanghyun Woo*, Joon-Young Lee, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019 / 11
589. Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications
Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019 / 10
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