4 accepted papers
Rendering dynamic scenes from monocular videos is a crucial yet challenging task. The recent deformable Gaussian Splatting has emerged as a robust solution to represent real-world dynamic scenes. However, it often leads to heavily redundant Gaussians, attempting to fit every training view at various…
Novel view synthesis from limited observations remains a significant challenge due to the lack of information in under-sampled regions, often resulting in noticeable artifacts. We introduce Generative Sparse-view Gaussian Splatting (GS-GS), a general pipeline designed to enhance the rendering qualit…
3D Gaussian Splatting (3DGS) has recently emerged as an efficient representation for high-quality 3D reconstruction and rendering. Despite its superior rendering quality and speed, 3DGS heavily relies on the assumption of geometric consistency among input images. In real-world scenarios, violations…
Text-to-motion generation is a formidable task, aiming to produce human motions that align with the input text while also adhering to human capabilities and physical laws. While there have been advancements in diffusion models, their application in discrete spaces remains underexplored. Current meth…