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BlazeWild/README.md
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πŸ”¬ AI Researcher from Nepal | Computer Vision & Multimodal Learning

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AI Coding

πŸ”¬ Research Focus

  • πŸŽ₯ Multimodal Video Captioning - Audio-Visual understanding
  • πŸ‘οΈ Computer Vision - 3D Reconstruction, Pose Estimation
  • πŸ€– Vision Transformers - Attention mechanisms for visual tasks
  • πŸ“Š Deep Learning Research - PyTorch implementations
  • 🌐 Portfolio | πŸ“§ ashokbk215@gmail.com

🌟 Research Projects

Hav-Cocap Real-Time Motion Transfer

πŸ› οΈ Research Stack

PyTorch Transformers OpenCV CUDA TensorFlow Python W&B Jupyter MediaPipe NumPy C++

πŸ“Š GitHub Statistics

GitHub Stats GitHub Streak
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πŸ† GitHub Trophies

GitHub Trophies

πŸ“ˆ Contribution Graph

Contribution Graph

🀝 Connect With Me

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"Researching multimodal AI systems for real-world applications"

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  1. Real-Time-Motion-Transfer-to-a-3D-Avatar Real-Time-Motion-Transfer-to-a-3D-Avatar Public

    Real-time human pose detection and motion transfer to 3D avatars using MediaPipe, DNN, and Three.js β€” supports webcam and video inputs with custom avatar integration.

    Python 15 6

  2. Custom_LLM_DataGen_Template Custom_LLM_DataGen_Template Public

    πŸ”§ Modular pipeline for generating high-quality, domain-specific datasets for LLM fine-tuning β€” from PDFs and web scraping to synthetic Q&A generation, quality filtering, and training-ready formatting.

    Python 2 1

  3. TrekNepal-3B__Finetuned-Llama3.2-3B TrekNepal-3B__Finetuned-Llama3.2-3B Public

    Fine-tuning pipeline for LLaMA 3.2-3B on Nepal trekking using custom synthetic Q&A data, LLM-based filtering, and QLoRA optimization.

    Python

  4. Hav-Cocap Hav-Cocap Public

    Hav-Cocap: Hybrid Audio-Visual Compressed Video Captioning framework. Extends CoCap with an Audio Encoder and evaluated on the AVCaps dataset.

    Jupyter Notebook