3 citations · 3 across the 2 of their papers we have counts for
5 papers
DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation
Hongyang Li, Jiehong Lin, Kui Jia
Establishment of point correspondence between camera and object coordinate systems is a promising way to solve 6D object poses. However, surrogate objectives of correspondence lear…
DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency
Jiehong Lin, Zewei Wei, Zhihao Li +3
Category-level 6D object pose and size estimation is to predict full pose configurations of rotation, translation, and size for object instances observed in single, arbitrary views…
CAD-PU: A Curvature-Adaptive Deep Learning Solution for Point Set Upsampling
Jiehong Lin, Xian Shi, Yuan Gao +2
Point set is arguably the most direct approximation of an object or scene surface, yet its practical acquisition often suffers from the shortcoming of being noisy, sparse, and poss…
Geometry-Aware Generation of Adversarial Point Clouds
Yuxin Wen, Jiehong Lin, Ke Chen +2
Machine learning models have been shown to be vulnerable to adversarial examples. While most of the existing methods for adversarial attack and defense work on the 2D image domain,…
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers
Kui Jia, Jiehong Lin, Mingkui Tan +1
Many machine learning problems concern with discovering or associating common patterns in data of multiple views or modalities. Multi-view learning is of the methods to achieve suc…