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20222024
most citedRA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation

7 citations · 16 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

3D Geometry-aware Deformable Gaussian Splatting for Dynamic View Synthesis

Zhicheng Lu, Xiang Guo, Le Hui +5

In this paper, we propose a 3D geometry-aware deformable Gaussian Splatting method for dynamic view synthesis. Existing neural radiance fields (NeRF) based solutions learn the defo…

cs.CV20234 cited

Self-Supervised 3D Scene Flow Estimation Guided by Superpoints

Yaqi Shen, Le Hui, Jin Xie +1

3D scene flow estimation aims to estimate point-wise motions between two consecutive frames of point clouds. Superpoints, i.e., points with similar geometric features, are usually…

cs.CV2022

Point Cloud Registration-Driven Robust Feature Matching for 3D Siamese Object Tracking

Haobo Jiang, Kaihao Lan, Le Hui +3

Learning robust feature matching between the template and search area is crucial for 3D Siamese tracking. The core of Siamese feature matching is how to assign high feature similar…

cs.CV2022

Unsupervised Domain Adaptation for Point Cloud Semantic Segmentation via Graph Matching

Yikai Bian, Le Hui, Jianjun Qian +1

Unsupervised domain adaptation for point cloud semantic segmentation has attracted great attention due to its effectiveness in learning with unlabeled data. Most of existing method…

cs.CV20224 cited

3D Siamese Transformer Network for Single Object Tracking on Point Clouds

Le Hui, Lingpeng Wang, Linghua Tang +3

Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area. Due to the large appearance…

cs.CV20227 cited

RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation

Mu He, Le Hui, Yikai Bian +3

Existing self-supervised monocular depth estimation methods can get rid of expensive annotations and achieve promising results. However, these methods suffer from severe performanc…