11 citations · 29 across the 11 of their papers we have counts for
5 papers · 2 filters
PlueckerNet: Learn to Register 3D Line Reconstructions
Liu Liu, Hongdong Li, Haodong Yao +1
Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve correspondences and relative pose between line recon…
Weak-shot Fine-grained Classification via Similarity Transfer
Junjie Chen, Li Niu, Liu Liu +1
Recognizing fine-grained categories remains a challenging task, due to the subtle distinctions among different subordinate categories, which results in the need of abundant annotat…
Solving the Blind Perspective-n-Point Problem End-To-End With Robust Differentiable Geometric Optimization
Dylan Campbell, Liu Liu, Stephen Gould
Blind Perspective-n-Point (PnP) is the problem of estimating the position and orientation of a camera relative to a scene, given 2D image points and 3D scene points, without prior…
Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution
Xibin Song, Yuchao Dai, Dingfu Zhou +4
Despite the remarkable progresses made in deep-learning based depth map super-resolution (DSR), how to tackle real-world degradation in low-resolution (LR) depth maps remains a maj…
Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem
Liu Liu, Dylan Campbell, Hongdong Li +3
Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given. When the correspond…