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m-saeid/README.md

👋 Hi, I’m Mohammad Saeid (@m-saeid)

🎯 I work on efficient 3D perception and point cloud learning, with a focus on lightweight segmentation models and representation learning for LiDAR-based systems.

🔬 My current research interests include:

  • Efficient 3D point cloud learning
  • LiDAR-based semantic & instance segmentation
  • Model compression and distillation for 3D vision
  • Geometric representation learning

🌱 I’m currently deepening my work in:

  • 3D deep learning architectures
  • Efficient transformer-based perception models

💡 I’m open to collaborating on research in 3D vision and point cloud understanding.

📫 Contact: imm.saeid@gmail.com

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  1. SLNet SLNet Public

    Official repository for paper "SLNet: A Super-Lightweight Geometry-Adaptive Network for 3D Point Cloud Recognition"

    Python 3 1

  2. NPNet NPNet Public

    Official code for paper NPNet: A Non-Parametric Network for 3D point cloud classification and segmentation using adaptive Gaussian–Fourier Positional Encoding. No training, no parameters, state-of-…

    Python 4

  3. ModeNetR_PointSkipNet ModeNetR_PointSkipNet Public

    Official repository for paper "Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet"

    Python 3

  4. SIMUROSOT-ROBOCHALLENGE SIMUROSOT-ROBOCHALLENGE Public

    Artificial intelligence and robotics competition, the last of us 2023

    Python 1