ch3cook-fdu/Vote2Cap-DETR

[T-PAMI 2024] & [CVPR 2023] Vote2Cap-DETR; A set-to-set perspective towards 3D Dense Captioning; State-of-the-Art 3D Dense Captioning methods

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/ 100
Emerging

This project helps computer vision researchers and engineers automatically describe 3D scenes. It takes 3D point cloud data of indoor environments as input and generates detailed textual captions for individual objects within that scene. This allows for automated understanding and description of complex 3D environments.

104 stars. No commits in the last 6 months.

Use this if you are working with 3D point cloud data and need to automatically identify objects and generate descriptive sentences about them, similar to how a person would describe a room.

Not ideal if your primary goal is general object detection or classification without the need for dense, natural language descriptions of specific objects in 3D space.

3D-scene-understanding computer-vision robotics-perception augmented-reality spatial-computing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

104

Forks

10

Language

Python

License

MIT

Last pushed

Aug 17, 2024

Commits (30d)

0

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