Convex Relaxation for Robust Vanishing Point Estimation in Manhattan World

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Convex Relaxation for Robust Vanishing Point Estimation in Manhattan World

7 May 2025

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Papers citing "Convex Relaxation for Robust Vanishing Point Estimation in Manhattan World"

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Title
PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus Florian Kluger Bodo Rosenhahn 43 6 0 26 Jan 2024
Deep vanishing point detection: Geometric priors make dataset variations vanish Yancong Lin R. Wiersma S. Pintea Klaus Hildebrandt E. Eisemann Jan van Gemert AAML 3DPC 88 24 0 16 Mar 2022
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus Florian Kluger Eric Brachmann H. Ackermann Carsten Rother M. Yang Bodo Rosenhahn 111 60 0 08 Jan 2020
MAGSAC++, a fast, reliable and accurate robust estimator Dániel Baráth Jana Noskova Maksym Ivashechkin Jirí Matas 71 250 0 11 Dec 2019
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution Yichao Zhou Haozhi Qi Jingwei Huang Yi-An Ma 3DPC 82 44 0 14 Oct 2019
Learning to Reconstruct 3D Manhattan Wireframes from a Single Image Yichao Zhou Haozhi Qi Yuexiang Zhai Qi Sun Zhili Chen Li-Yi Wei Yi-An Ma 3DV 62 65 0 17 May 2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences Huu Le Thanh-Toan Do Tuan Hoang Ngai-Man Cheung 3DV 3DPC 79 89 0 06 Apr 2019
An Efficient Solution to Non-Minimal Case Essential Matrix Estimation Ji Zhao 77 51 0 21 Mar 2019
MAGSAC: marginalizing sample consensus Dániel Baráth Jana Noskova Jirí Matas 58 278 0 20 Mar 2018
Detecting Vanishing Points using Global Image Context in a Non-Manhattan World Menghua Zhai Scott Workman Nathan Jacobs 89 105 0 19 Aug 2016