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20152023
most citedMLCVNet: Multi-Level Context VoteNet for 3D Object Detection

28 citations · 120 across the 20 of their papers we have counts for

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Showing 2019 · cs.CVShow all

10 papers · 2 filters

cs.CV2019

Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering

Kai Xu, Xiao-Jun Wu, Wen-Bo Hu

Based on further studying the low-rank subspace clustering (LRSC) and L2-graph subspace clustering algorithms, we propose a F-graph subspace clustering algorithm with a symmetric c…

cs.CV2019

Decoupling Features and Coordinates for Few-shot RGB Relocalization

Siyan Dong, Songyin Wu, Yixin Zhuang +3

Cross-scene model adaption is crucial for camera relocalization in real scenarios. It is often preferable that a pre-learned model can be fast adapted to a novel scene with as few…

cs.CV2019

PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes

Rundi Wu, Yixin Zhuang, Kai Xu +2

We introduce PQ-NET, a deep neural network which represents and generates 3D shapes via sequential part assembly. The input to our network is a 3D shape segmented into parts, where…

cs.CV2019

Rescan: Inductive Instance Segmentation for Indoor RGBD Scans

Maciej Halber, Yifei Shi, Kai Xu +1

In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e.g., as part of re…

cs.CV2019

Learning Part Generation and Assembly for Structure-aware Shape Synthesis

Jun Li, Chengjie Niu, Kai Xu

Learning powerful deep generative models for 3D shape synthesis is largely hindered by the difficulty in ensuring plausibility encompassing correct topology and reasonable geometry…

cs.CV2019★ 1 cited

Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction

Yifei Shi, Angel Xuan Chang, Zhelun Wu +2

Indoor scenes exhibit rich hierarchical structure in 3D object layouts. Many tasks in 3D scene understanding can benefit from reasoning jointly about the hierarchical context of a…