most citedMoManifold: Learning to Measure 3D Human Motion via Decoupled Joint Acceleration Manifolds

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2025

GaussianUpdate: Continual 3D Gaussian Splatting Update for Changing Environments

Lin Zeng, Boming Zhao, Jiarui Hu +4

Novel view synthesis with neural models has advanced rapidly in recent years, yet adapting these models to scene changes remains an open problem. Existing methods are either labor-…

cs.CV2025

NeuraLoc: Visual Localization in Neural Implicit Map with Dual Complementary Features

Hongjia Zhai, Boming Zhao, Hai Li +5

Recently, neural radiance fields (NeRF) have gained significant attention in the field of visual localization. However, existing NeRF-based approaches either lack geometric constra…

cs.CV2024

GURecon: Learning Detailed 3D Geometric Uncertainties for Neural Surface Reconstruction

Zesong Yang, Ru Zhang, Jiale Shi +5

Neural surface representation has demonstrated remarkable success in the areas of novel view synthesis and 3D reconstruction. However, assessing the geometric quality of 3D reconst…

cs.CV2024

SplatLoc: 3D Gaussian Splatting-based Visual Localization for Augmented Reality

Hongjia Zhai, Xiyu Zhang, Boming Zhao +5

Visual localization plays an important role in the applications of Augmented Reality (AR), which enable AR devices to obtain their 6-DoF pose in the pre-build map in order to rende…

cs.CV20241 cited

MoManifold: Learning to Measure 3D Human Motion via Decoupled Joint Acceleration Manifolds

Ziqiang Dang, Tianxing Fan, Boming Zhao +4

Incorporating temporal information effectively is important for accurate 3D human motion estimation and generation which have wide applications from human-computer interaction to A…