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We propose SparseDC, a model for Depth Completion of Sparse and non-uniform depth inputs.
Towards total scene understanding: Classification, annotation and segmentation in an automatic framework
Li-Jia Li, Richard Socher, and Li Fei-Fei · 2009
Earlier work this paper cites.
Lidar velodyne hdl-64e calibration using pattern planes
Gerardo Atanacio-Jiménez, José-Joel González-Barbosa, Juan B Hurtado-Ramos, Francisco J Ornelas-Rodríguez, Hugo Jiménez-Hernández, Teresa García-Ramirez, and Ricardo González-Barbosa · 2011
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Stereoscan: Dense 3d reconstruction in real-time
Andreas Geiger, Julius Ziegler, and Christoph Stiller · 2011
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Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
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Augmented reality: An overview and five directions for ar in education
Steve Chi-Yin Yuen, Gallayanee Yaoyuneyong, and Erik Johnson · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
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Microsoft kinect sensor and its effect
Zhengyou Zhang · 2012
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Autonomous driving: technical, legal and social aspects
Markus Maurer, J Christian Gerdes, Barbara Lenz, and Hermann Winner · 2016
Earlier work this paper cites.
Dense 3d reconstruction combining depth and rgb information
Hailong Pan, Tao Guan, Yawei Luo, Liya Duan, Yuan Tian, Liu Yi, Yizhu Zhao, and Junqing Yu · 2016
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Submanifold sparse convolutional networks
Benjamin Graham and Laurens Van der Maaten · 2017
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Intel realsense stereoscopic depth cameras
Leonid Keselman, John Iselin Woodfill, Anders Grunnet-Jepsen, and Achintya Bhowmik · 2017
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Sparsity invariant cnns
Jonas Uhrig, Nick Schneider, Lukas Schneider, Uwe Franke, Thomas Brox, and Andreas Geiger · 2017
Earlier work this paper cites.
Deep learning using rectified linear units (relu)
Abien Fred Agarap · 2018
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Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network
Xinjing Cheng, Peng Wang, and Ruigang Yang · 2018
Cited alongside, same era.
Sparse-to-dense: Depth prediction from sparse depth samples and a single image
Fangchang Ma and Sertac Karaman · 2018
Cited alongside, same era.
CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion, 2019
Xinjing Cheng, Peng Wang, Chenye Guan, and Ruigang Yang · 2019
Cited alongside, same era.
Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries
Junjie Hu, Mete Ozay, Yan Zhang, and Takayuki Okatani · 2019
Cited alongside, same era.
A literature overview of virtual reality (vr) in treatment of psychiatric disorders: recent advances and limitations
Mi Jin Park, Dong Jun Kim, Unjoo Lee, Eun Jin Na, and Hong Jin Jeon · 2019
Cited alongside, same era.
Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Adaptive Context-Aware Multi-Modal Network for Depth Completion
Shanshan Zhao, Mingming Gong, Huan Fu, and Dacheng Tao · 2021
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Spconv: Spatially sparse convolution library
Spconv Contributors · 2022
Later among the works it cites.
ABCD: Attentive Bilateral Convolutional Network for Robust Depth Completion
Yurim Jeon, Hwichang Kim, and Seung-Woo Seo · 2022
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Dynamic Spatial Propagation Network for Depth Completion
Yuankai Lin, Tao Cheng, Qi Zhong, Wending Zhou, and Hua Yang · 2022
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GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs, 2022
Xin Liu, Xiaofei Shao, Bo Wang, Yali Li, and Shengjin Wang · 2022
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Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image
Jiaxiong Qiu, Zhaopeng Cui, Yinda Zhang, Xingdi Zhang, Shuaicheng Liu, Bing Zeng, and Marc Pollefeys · 2019
Cited alongside, same era.
Learning Guided Convolutional Network for Depth Completion, 2019
Jie Tang, Fei-Peng Tian, Wei Feng, Jian Li, and Ping Tan · 2019
Cited alongside, same era.
Depth completion from sparse lidar data with depth-normal constraints
Yan Xu, Xinge Zhu, Jianping Shi, Guofeng Zhang, Hujun Bao, and Hongsheng Li · 2019
Cited alongside, same era.
Free-form image inpainting with gated convolution
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2019
Cited alongside, same era.
FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion
Lina Liu, Xibin Song, Xiaoyang Lyu, Junwei Diao, Mengmeng Wang, Yong Liu, and Liangjun Zhang · 2020
Cited alongside, same era.
Non-local Spatial Propagation Network for Depth Completion
Jinsun Park, Kyungdon Joo, Zhe Hu, Chi-Kuei Liu, and In So Kweon · 2020
Cited alongside, same era.
GuideFormer: Transformers for Image Guided Depth Completion
Kyeongha Rho, Jinsung Ha, and Youngjung Kim · 2020
Cited alongside, same era.
Later among the works it cites.
Pc2-pu: Patch correlation and point correlation for effective point cloud upsampling
Chen Long, WenXiao Zhang, Ruihui Li, Hao Wang, Zhen Dong, and Bisheng Yang · 2022
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Guided Depth Super-Resolution by Deep Anisotropic Diffusion, 2022
Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2022
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Segmentation-guided Domain Adaptation for Efficient Depth Completion, 2022
Fabian Märkert, Martin Sunkel, Anselm Haselhoff, and Stefan Rudolph · 2022
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Pvtv2: Improved baselines with pyramid vision transformer
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2022
Later among the works it cites.
Sparse spn: Depth completion from sparse keypoints
Yuqun Wu, Jae Yong Lee, and Derek Hoiem · 2022
Later among the works it cites.
RigNet: Repetitive Image Guided Network for Depth Completion, 2022
Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, and Jian Yang · 2022
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Sparsity agnostic depth completion
Andrea Conti, Matteo Poggi, and Stefano Mattoccia · 2023
Closest in time.
Deep Depth Completion from Extremely Sparse Data: A Survey
Junjie Hu, Chenyu Bao, Mete Ozay, Chenyou Fan, Qing Gao, Honghai Liu, and Tin Lun Lam · 2023
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Urcdc-depth: Uncertainty rectified cross-distillation with cutflip for monocular depth estimation
Shuwei Shao, Zhongcai Pei, Weihai Chen, Ran Li, Zhong Liu, and Zhengguo Li · 2023
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Lrru: Long-short range recurrent updating networks for depth completion
Yufei Wang, Bo Li, Ge Zhang, Qi Liu, Tao Gao, and Yuchao Dai · 2023
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Convnext v2: Co-designing and scaling convnets with masked autoencoders
Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, and Saining Xie · 2023
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CompletionFormer: Depth Completion with Convolutions and Vision Transformers, 2023
Zhang Youmin, Guo Xianda, Poggi Matteo, Zhu Zheng, Huang Guan, and Mattoccia Stefano · 2023
Closest in time.
BEV@ DC: Bird’s-Eye View Assisted Training for Depth Completion
Wending Zhou, Xu Yan, Yinghong Liao, Yuankai Lin, Jin Huang, Gangming Zhao, Shuguang Cui, and Zhen Li · 2023
Closest in time.