Shape Completion from a Single RGBD Image
By Dongping Li, Tianjia Shao, Hongzhi Wu, Kun Zhou. 2017
51 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Vineet Kosaraju
- Hamid Rezatofighi
- Christoph Mertz
- David Held
- Martial Hebert
- Ian David Reid
- Silvio Savarese
- Lyne P. Tchapmi
In Computer Graphics and Computer-Aided Design
- Christoph Mertz
- David Held
- Martial Hebert
- Ian David Reid
- Silvio Savarese
- Wentao Yuan
- Tejas Khot
- Abhinav Kumar Gupta
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Trevor Darrell
- Jitendra Malik
- Dacheng Tao
- Xiaogang Wang
- Silvio Savarese
- Andrew Zisserman
- Bernt Schiele
Citations in the corpus
- Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis (2016, neutral): “Li et al. [20] use single RGB-D images as input and run a similar pipeline, where they first find and deform nearest models form a database.”
- TopNet: Structural Point Cloud Decoder (2019, background): “These works have shown great success in the tasks of 3D Reconstruction [5, 11], shape completion [6, 14, 36, 19], and shape generation from embeddings [3].”
- PCN: Point Completion Network (2018, methodology): “Other works [6, 12, 14, 21, 22, 39] deform the retrieved model to synthesize shapes that are more consistent with the input.”