Building Open-Set 3D Representation: Feature Fusion and Geometric-Semantic Merging

15/12/2025 6 min
Building Open-Set 3D Representation: Feature Fusion and Geometric-Semantic Merging

Listen "Building Open-Set 3D Representation: Feature Fusion and Geometric-Semantic Merging"

Episode Synopsis



This story was originally published on HackerNoon at: https://hackernoon.com/building-open-set-3d-representation-feature-fusion-and-geometric-semantic-merging.
O3D-SIM is built by projecting 2D masks and embeddings to 3D, using DBSCAN for initial refinement.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #deep-learning, #o3d-sim-creation, #3d-point-cloud-projectio, #dbscan-clustering, #incremental-mapping, #geometric-semantic-fusion, #feature-embedding-averaging, #scene-refinement, and more.


This story was written by: @instancing. Learn more about this writer by checking @instancing's about page,
and for more stories, please visit hackernoon.com.



O3D-SIM is built by projecting 2D masks and embeddings to 3D, using DBSCAN for initial refinement.


More episodes of the podcast Machine Learning Tech Brief By HackerNoon