Point Cloud Completion
51 papers with code • 3 benchmarks • 4 datasets
These leaderboards are used to track progress in Point Cloud Completion
Most implemented papers
It differs from the previous attention attempts in that, instead of using attention to blend hidden units of an encoder to a context vector at each decoder step, it uses attention as a pointer to select a member of the input sequence as the output.
PCN: Point Completion Network
Shape completion, the problem of estimating the complete geometry of objects from partial observations, lies at the core of many vision and robotics applications.
AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation
We introduce a method for learning to generate the surface of 3D shapes.
Unpaired Point Cloud Completion on Real Scans using Adversarial Training
As 3D scanning solutions become increasingly popular, several deep learning setups have been developed geared towards that task of scan completion, i. e., plausibly filling in regions there were missed in the raw scans.
Morphing and Sampling Network for Dense Point Cloud Completion
3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community.
PF-Net: Point Fractal Network for 3D Point Cloud Completion
Unlike existing point cloud completion networks, which generate the overall shape of the point cloud from the incomplete point cloud and always change existing points and encounter noise and geometrical loss, PF-Net preserves the spatial arrangements of the incomplete point cloud and can figure out the detailed geometrical structure of the missing region(s) in the prediction.
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
However, previous methods usually suffered from discrete nature of point cloud and unstructured prediction of points in local regions, which makes it hard to reveal fine local geometric details on the complete shape.
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
Based on the MVP dataset, this paper reports methods and results in the Multi-View Partial Point Cloud Challenge 2021 on Completion and Registration.
TopNet: Structural Point Cloud Decoder
a collection of manifolds or surfaces, for the generated point cloud of a 3D object.
Cascaded Refinement Network for Point Cloud Completion
Point clouds are often sparse and incomplete.