8 papers
OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention
Kunyi Li, Michael Niemeyer, Sen Wang +3
Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semantic predictions across multi-view…
SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors
Kunyi Li, Michael Niemeyer, Sen Wang +3
Recent advances in dense 3D reconstruction have demonstrated strong capability in accurately capturing local geometry. However, extending these methods to incremental global recons…
Visibility-Aware Language Aggregation for Open-Vocabulary Segmentation in 3D Gaussian Splatting
Sen Wang, Kunyi Li, Siyun Liang +4
Recently, distilling open-vocabulary language features from 2D images into 3D Gaussians has attracted significant attention. Although existing methods achieve impressive language-b…
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians
Siyun Liang, Sen Wang, Kunyi Li +5
3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While its vanilla representation is mainly designed for view synthesis, recen…
MonoGSDF: Exploring Monocular Geometric Cues for Gaussian Splatting-Guided Implicit Surface Reconstruction
Kunyi Li, Michael Niemeyer, Zeyu Chen +2
Accurate meshing from monocular images remains a key challenge in 3D vision. While state-of-the-art 3D Gaussian Splatting (3DGS) methods excel at synthesizing photorealistic novel…
OracleGS: Grounding Generative Priors for Sparse-View Gaussian Splatting
Atakan Topaloglu, Kunyi Li, Michael Niemeyer +3
Sparse-view novel view synthesis is fundamentally ill-posed due to severe geometric ambiguity. Current methods are caught in a trade-off: regressive models are geometrically faithf…