ReAge3D trains a diffusion re-aging model on synthetic pairs then uses masked propagation from a frontal pivot view to produce consistent multi-view images that supervise 3D face optimization.
Gaussctrl: Multi-view consistent text-driven 3d gaussian splatting editing
3 Pith papers cite this work. Polarity classification is still indexing.
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STaR-Quant provides a state-time consistent PTQ framework for DLLMs using SGAT and TAC to improve low-bit weight-activation quantization.
citing papers explorer
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ReAge3D: Re-Aging 3D Faces with View Consistency
ReAge3D trains a diffusion re-aging model on synthetic pairs then uses masked propagation from a frontal pivot view to produce consistent multi-view images that supervise 3D face optimization.
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STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models
STaR-Quant provides a state-time consistent PTQ framework for DLLMs using SGAT and TAC to improve low-bit weight-activation quantization.
- GSDeformer: Direct, Real-time and Extensible Cage-based Deformation for 3D Gaussian Splatting