Search Results for author: Bingbing Zhuang

Found 11 papers, 0 papers with code

Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty

no code implementations CVPR 2021 Bingbing Zhuang, Manmohan Chandraker

While we focus on relative pose, we envision that our pipeline is broadly applicable for fusing classical geometry and deep learning.

Pose Estimation

Weakly But Deeply Supervised Occlusion-Reasoned Parametric Road Layouts

no code implementations CVPR 2022 Buyu Liu, Bingbing Zhuang, Manmohan Chandraker

We propose an end-to-end network that takes a single perspective RGB image of a complex road scene as input, to produce occlusion-reasoned layouts in perspective space as well as a parametric bird's-eye-view (BEV) space.

Image Stitching and Rectification for Hand-Held Cameras

no code implementations ECCV 2020 Bingbing Zhuang, Quoc-Huy Tran

In this paper, we derive a new differential homography that can account for the scanline-varying camera poses in Rolling Shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one stroke.

Image Stitching

Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction

no code implementations ECCV 2020 Lokender Tiwari, Pan Ji, Quoc-Huy Tran, Bingbing Zhuang, Saket Anand, Manmohan Chandraker

Classical monocular Simultaneous Localization And Mapping (SLAM) and the recently emerging convolutional neural networks (CNNs) for monocular depth prediction represent two largely disjoint approaches towards building a 3D map of the surrounding environment.

Depth Estimation Depth Prediction +1

Learning Structure-And-Motion-Aware Rolling Shutter Correction

no code implementations CVPR 2019 Bingbing Zhuang, Quoc-Huy Tran, Pan Ji, Loong-Fah Cheong, Manmohan Chandraker

In view of the complex RS geometry, we then propose a Convolutional Neural Network (CNN)-based method which learns the underlying geometry (camera motion and scene structure) from just a single RS image and perform RS image correction.

Rolling-Shutter-Aware Differential SfM and Image Rectification

no code implementations ICCV 2017 Bingbing Zhuang, Loong-Fah Cheong, Gim Hee Lee

We demonstrate that the dense depth maps recovered from the relative pose of the RS camera can be used in a RS-aware warping for image rectification to recover high-quality Global Shutter (GS) images.

3D Reconstruction Optical Flow Estimation +1

Baseline Desensitizing In Translation Averaging

no code implementations CVPR 2018 Bingbing Zhuang, Loong-Fah Cheong, Gim Hee Lee

Many existing translation averaging algorithms are either sensitive to disparate camera baselines and have to rely on extensive preprocessing to improve the observed Epipolar Geometry graph, or if they are robust against disparate camera baselines, require complicated optimization to minimize the highly nonlinear angular error objective.


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