✨Implicit Neural Representation Facilitates Unified Universal Vision Encoding
📝 Summary:
This paper unifies image representation learning for both recognition and generation. It uses a hyper-network for implicit neural representation with knowledge distillation to create compressed embeddings. The model achieves state-of-the-art results and enables generative capabilities.
🔹 Publication Date: Published on Jan 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.14256
• PDF: https://arxiv.org/pdf/2601.14256
• Github: https://github.com/tiktok/huvr
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#ComputerVision #DeepLearning #GenerativeAI #RepresentationLearning #VisionEncoding
📝 Summary:
This paper unifies image representation learning for both recognition and generation. It uses a hyper-network for implicit neural representation with knowledge distillation to create compressed embeddings. The model achieves state-of-the-art results and enables generative capabilities.
🔹 Publication Date: Published on Jan 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.14256
• PDF: https://arxiv.org/pdf/2601.14256
• Github: https://github.com/tiktok/huvr
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#ComputerVision #DeepLearning #GenerativeAI #RepresentationLearning #VisionEncoding