Fetching the paper…
Reading the bibliography…
Reference-guided image inpainting restores image pixels by leveraging the content from another single reference image.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
Earlier work this paper cites.
A computer algorithm for reconstructing a scene from two projections
H Christopher Longuet-Higgins · 1981
Earlier work this paper cites.
A computational approach to edge detection
John Canny · 1986
Earlier work this paper cites.
Footprint evaluation for volume rendering
Lee Westover · 1990
Earlier work this paper cites.
In defense of the eight-point algorithm
Richard I Hartley · 1997
Earlier work this paper cites.
Triangulation
Richard I Hartley and Peter Sturm · 1997
Earlier work this paper cites.
Object recognition from local scale-invariant features
David G Lowe · 1999
Earlier work this paper cites.
Image inpainting
Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester · 2000
Earlier work this paper cites.
Multiple view geometry in computer vision
Richard Hartley and Andrew Zisserman · 2003
Earlier work this paper cites.
Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
Earlier work this paper cites.
Space-time video completion
Yonatan Wexler, Eli Shechtman, and Michal Irani · 2004
Earlier work this paper cites.
Video inpainting of occluding and occluded objects
Kedar A Patwardhan, Guillermo Sapiro, and Marcelo Bertalmio · 2005
Earlier work this paper cites.
Surf: Speeded up robust features
Herbert Bay, Tinne Tuytelaars, and Luc Van Gool · 2006
Earlier work this paper cites.
Space-time completion of video
Yonatan Wexler, Eli Shechtman, and Michal Irani · 2007
Earlier work this paper cites.
Stereoscopic inpainting: Joint color and depth completion from stereo images
Liang Wang, Hailin Jin, Ruigang Yang, and Minglun Gong · 2008
Earlier work this paper cites.
Patchmatch: A randomized correspondence algorithm for structural image editing
Connelly Barnes, Eli Shechtman, Adam Finkelstein, and Dan B Goldman · 2009
Earlier work this paper cites.
Inpainting in multi-image stereo
Arnav V Bhavsar and Ambasamudram N Rajagopalan · 2010
Earlier work this paper cites.
Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
Earlier work this paper cites.
Background inpainting for videos with dynamic objects and a free-moving camera
Miguel Granados, Kwang In Kim, James Tompkin, Jan Kautz, and Christian Theobalt · 2012
Earlier work this paper cites.
Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
Earlier work this paper cites.
Posenet: A convolutional network for real-time 6-dof camera relocalization
Alex Kendall, Matthew Grimes, and Roberto Cipolla · 2015
Earlier work this paper cites.
Face alignment by coarse-to-fine shape searching
Shizhan Zhu, Cheng Li, Chen Change Loy, and Xiaoou Tang · 2015
Earlier work this paper cites.
Multiview image completion with space structure propagation
Seung-Hwan Baek, Inchang Choi, and Min H Kim · 2016
Earlier work this paper cites.
Deeper depth prediction with fully convolutional residual networks
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab · 2016
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
Earlier work this paper cites.
Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
Earlier work this paper cites.
Multi-view inpainting for image-based scene editing and rendering
Theo Thonat, Eli Shechtman, Sylvain Paris, and George Drettakis · 2016
Earlier work this paper cites.
Lift: Learned invariant feature transform
Kwang Moo Yi, Eduard Trulls, Vincent Lepetit, and Pascal Fua · 2016
Cited alongside, same era.
Dsac-differentiable ransac for camera localization
Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, and Carsten Rother · 2017
Cited alongside, same era.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Cited alongside, same era.
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2017
Cited alongside, same era.
Globally and locally consistent image completion
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 2017
Cited alongside, same era.
Multi-scale continuous crfs as sequential deep networks for monocular depth estimation
Onion-peel networks for deep video completion
Seoung Wug Oh, Sungho Lee, Joon-Young Lee, and Seon Joo Kim · 2019
Later among the works it cites.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Later among the works it cites.
Structureflow: Image inpainting via structure-aware appearance flow
Yurui Ren, Xiaoming Yu, Ruonan Zhang, Thomas H Li, Shan Liu, and Ge Li · 2019
Later among the works it cites.
Video inpainting by jointly learning temporal structure and spatial details
Chuan Wang, Haibin Huang, Xiaoguang Han, and Jue Wang · 2019
Later among the works it cites.
Foreground-aware image inpainting
Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, and Jiebo Luo · 2019
Later among the works it cites.
Free-form image inpainting with gated convolution
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dan Xu, Elisa Ricci, Wanli Ouyang, Xiaogang Wang, and Nicu Sebe · 2017
Cited alongside, same era.
High-resolution image inpainting using multi-scale neural patch synthesis
Chao Yang, Xin Lu, Zhe Lin, Eli Shechtman, Oliver Wang, and Hao Li · 2017
Cited alongside, same era.
Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
Cited alongside, same era.
Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
Cited alongside, same era.
High quality monocular depth estimation via transfer learning
Ibraheem Alhashim and Peter Wonka · 2018
Cited alongside, same era.
Superpoint: Self-supervised interest point detection and description
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
Cited alongside, same era.
Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
Cited alongside, same era.
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2019
Later among the works it cites.
Learning two-view correspondences and geometry using order-aware network
Jiahui Zhang, Dawei Sun, Zixin Luo, Anbang Yao, Lei Zhou, Tianwei Shen, Yurong Chen, Long Quan, and Hongen Liao · 2019
Later among the works it cites.
All-weather deep outdoor lighting estimation
Jinsong Zhang, Kalyan Sunkavalli, Yannick Hold-Geoffroy, Sunil Hadap, Jonathan Eisenman, and Jean-Fran · 2019
Later among the works it cites.
Pluralistic image completion
Chuanxia Zheng, Tat-Jen Cham, and Jianfei Cai · 2019
Later among the works it cites.
Guiding monocular depth estimation using depth-attention volume
Lam Huynh, Phong Nguyen-Ha, Jiri Matas, Esa Rahtu, and Janne Heikkilä · 2020
Later among the works it cites.
Guidance and evaluation: Semantic-aware image inpainting for mixed scenes
Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, and Shin’ichi Satoh · 2020
Later among the works it cites.
Learning across views for stereo image completion
Wei Ma, Mana Zheng, Wenguang Ma, Shibiao Xu, and Xiaopeng Zhang · 2020
Later among the works it cites.
Accelerating 3d deep learning with pytorch3d
Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
Later among the works it cites.
Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
Later among the works it cites.
Contextual residual aggregation for ultra high-resolution image inpainting
Zili Yi, Qiang Tang, Shekoofeh Azizi, Daesik Jang, and Zhan Xu · 2020
Later among the works it cites.
Learning joint spatial-temporal transformations for video inpainting
Yanhong Zeng, Jianlong Fu, and Hongyang Chao · 2020
Later among the works it cites.
High-resolution image inpainting with iterative confidence feedback and guided upsampling
Yu Zeng, Zhe Lin, Jimei Yang, Jianming Zhang, Eli Shechtman, and Huchuan Lu · 2020
Later among the works it cites.
Towards better generalization: Joint depth-pose learning without posenet
Wang Zhao, Shaohui Liu, Yezhi Shu, and Yong-Jin Liu · 2020
Later among the works it cites.
Domain decluttering: Simplifying images to mitigate synthetic-real domain shift and improve depth estimation
Yunhan Zhao, Shu Kong, Daeyun Shin, and Charless Fowlkes · 2020
Later among the works it cites.
Wide-baseline relative camera pose estimation with directional learning
Kefan Chen, Noah Snavely, and Ameesh Makadia · 2021
Later among the works it cites.
Transfusion: Cross-view fusion with transformer for 3d human pose estimation
Haoyu Ma, Liangjian Chen, Deying Kong, Zhe Wang, Xingwei Liu, Hao Tang, Xiangyi Yan, Yusheng Xie, Shih-Yao Lin, and Xiaohui Xie · 2021
Later among the works it cites.
Fov-net: Field-of-view extrapolation using self-attention and uncertainty
Liqian Ma, Stamatios Georgoulis, Xu Jia, and Luc Van Gool · 2021
Later among the works it cites.
Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
Later among the works it cites.
Deep two-view structure-from-motion revisited
Jianyuan Wang, Yiran Zhong, Yuchao Dai, Stan Birchfield, Kaihao Zhang, Nikolai Smolyanskiy, and Hongdong Li · 2021
Later among the works it cites.
Large scale image completion via co-modulated generative adversarial networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, and Yan Xu · 2021
Later among the works it cites.
Camera pose matters: Improving depth prediction by mitigating pose distribution bias
Yunhan Zhao, Shu Kong, and Charless Fowlkes · 2021
Later among the works it cites.
Transfill: Reference-guided image inpainting by merging multiple color and spatial transformations
Yuqian Zhou, Connelly Barnes, Eli Shechtman, and Sohrab Amirghodsi · 2021
Later among the works it cites.