Arlo0o/HTCL
[ECCV 2024, IEEE TPAMI] Official PyTorch Implementation of HTCL : Hierarchical Temporal Context Learning for Camera-based Semantic Scene Completion
This project helps self-driving car engineers and robotics researchers by converting a stream of 2D camera images into a detailed 3D map of the environment, identifying objects and open spaces. It takes video feeds from vehicle cameras and outputs a rich, semantically labeled 3D occupancy grid, which is crucial for navigation and obstacle avoidance. The main users are perception system developers for autonomous vehicles and robotics.
Use this if you need to generate highly accurate 3D semantic maps of dynamic outdoor environments solely from camera data, outperforming even some LiDAR-based methods.
Not ideal if your application does not involve camera-based 3D scene reconstruction for autonomous navigation or if you primarily work with static environments.
Stars
51
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
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