7 papers · 1 filter
AnyAct: Towards Human Reenactment of Character Motion From Video
Liuhan Chen, Lei Zhong, Jiawei Wang +6
We study the problem of directly deriving an initial human reenactment from a monocular video of a non-human character. Our goal is not to reconstruct the source character itself b…
CLIP-GS: CLIP-Informed Gaussian Splatting for View-Consistent 3D Indoor Semantic Understanding
Guibiao Liao, Jiankun Li, Zhenyu Bao +3
Exploiting 3D Gaussian Splatting (3DGS) with Contrastive Language-Image Pre-Training (CLIP) models for open-vocabulary 3D semantic understanding of indoor scenes has emerged as an…
MGStream: Motion-aware 3D Gaussian for Streamable Dynamic Scene Reconstruction
Zhenyu Bao, Qing Li, Guibiao Liao +2
3D Gaussian Splatting (3DGS) has gained significant attention in streamable dynamic novel view synthesis (DNVS) for its photorealistic rendering capability and computational effici…
SPC-GS: Gaussian Splatting with Semantic-Prompt Consistency for Indoor Open-World Free-view Synthesis from Sparse Inputs
Guibiao Liao, Qing Li, Zhenyu Bao +2
3D Gaussian Splatting-based indoor open-world free-view synthesis approaches have shown significant performance with dense input images. However, they exhibit poor performance when…
OV-NeRF: Open-vocabulary Neural Radiance Fields with Vision and Language Foundation Models for 3D Semantic Understanding
Guibiao Liao, Kaichen Zhou, Zhenyu Bao +2
The development of Neural Radiance Fields (NeRFs) has provided a potent representation for encapsulating the geometric and appearance characteristics of 3D scenes. Enhancing the ca…
LoopSparseGS: Loop Based Sparse-View Friendly Gaussian Splatting
Zhenyu Bao, Guibiao Liao, Kaichen Zhou +3
Despite the photorealistic novel view synthesis (NVS) performance achieved by the original 3D Gaussian splatting (3DGS), its rendering quality significantly degrades with sparse in…