This project implements an Interactive 4D (Dynamic) Point Cloud Retrieval System designed to index and search spatio-temporal 3D representations (dynamic point clouds over time) using natural language commands.
The system leverages the CL4D (Contrastive Language–4D Pretraining) model to encode dynamic point clouds and text queries into a shared embedding space, allowing users to query complex 3D human actions and physical interactions.
📐 System Architecture
System architecture overview: Spatio-temporal sequences of action point clouds are encoded using the CL4D Encoder, stored in a Vector Database, and queried interactively via natural language commands mapped to text embeddings.
🎬 Demonstration Video
Below is the demonstration of the interactive query processing and retrieval visualization interface:
Interactive query retrieval visualization showing dynamic point cloud frames (e.g., drilling a hole) matched to a user command.