6 papers
A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation
Shuting He, Peilin Ji, Yitong Yang +4
In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radiance Field (NeRF), enabling high…
DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimization
Yitong Yang, Xuexin Liu, Yinglin Wang +4
3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods st…
FantasyStyle: Controllable Stylized Distillation for 3D Gaussian Splatting
Yitong Yang, Yinglin Wang, Changshuo Wang +2
The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1)…
SplitFlux: Learning to Decouple Content and Style from a Single Image
Yitong Yang, Yinglin Wang, Changshuo Wang +3
Disentangling image content and style is essential for customized image generation. Existing SDXL-based methods struggle to achieve high-quality results, while the recently propose…
ReferSplat: Referring Segmentation in 3D Gaussian Splatting
Shuting He, Guangquan Jie, Changshuo Wang +4
We introduce Referring 3D Gaussian Splatting Segmentation (R3DGS), a new task that aims to segment target objects in a 3D Gaussian scene based on natural language descriptions, whi…
Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation
Changshuo Wang, Shuting He, Xiang Fang +3
Few-shot point cloud semantic segmentation aims to accurately segment "unseen" new categories in point cloud scenes using limited labeled data. However, pretraining-based methods n…