5 papers
Pseudo-View Enhancement via Confidence Fusion for Unposed Sparse-View Reconstruction
Beizhen Zhao, Sicheng Yu, Guanzhi Ding +2
3D scene reconstruction under unposed sparse viewpoints is a highly challenging yet practically important problem, especially in outdoor scenes due to complex lighting and scale va…
Enhanced Partially Relevant Video Retrieval through Inter- and Intra-Sample Analysis with Coherence Prediction
Junlong Ren, Gangjian Zhang, Yu Hu +3
Partially Relevant Video Retrieval (PRVR) aims to retrieve the target video that is partially relevant to the text query. The primary challenge in PRVR arises from the semantic asy…
VGGT4D: Mining Motion Cues in Visual Geometry Transformers for 4D Scene Reconstruction
Yu Hu, Chong Cheng, Sicheng Yu +2
Reconstructing dynamic 4D scenes is challenging, as it requires robust disentanglement of dynamic objects from the static background. While 3D foundation models like VGGT provide a…
Unposed 3DGS Reconstruction with Probabilistic Procrustes Mapping
Chong Cheng, Zijian Wang, Sicheng Yu +3
3D Gaussian Splatting (3DGS) has emerged as a core technique for 3D representation. Its effectiveness largely depends on precise camera poses and accurate point cloud initializatio…
RegGS: Unposed Sparse Views Gaussian Splatting with 3DGS Registration
Chong Cheng, Yu Hu, Sicheng Yu +3
3D Gaussian Splatting (3DGS) has demonstrated its potential in reconstructing scenes from unposed images. However, optimization-based 3DGS methods struggle with sparse views due to…