A new paper introduces RealMe, a framework for generating high-resolution, 4D-consistent volumetric videos from minimal captures using a video diffusion model. This approach enhances sparse video data to create immersive content, outperforming existing methods on benchmarks like DNA-Rendering and RealVV. Separately, the Ornith-1.5-122B and Tess-4.5-27B models, both fine-tuned on Qwen, have been released, with Tess-4.5 demonstrating improved efficiency by using fewer tokens for similar or better results. AI
IMPACT RealMe could enable more accessible creation of immersive volumetric content, while Qwen fine-tunes highlight efficiency gains in LLM token usage.
RANK_REASON The cluster contains a research paper on volumetric video generation and announcements of fine-tuned language models.
Read on Hugging Face Daily Papers →
- arXiv
- Claude Agent SDK
- DNA rendering of polyhedral meshes at the nanoscale.
- Hugging Face
- llama.cpp
- Ornith-1.5-122B
- Qwen
- RealMe
- RealVV
- Tess-4.5-27B
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