Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the
Wild

Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild

18 January 2021

Shenlong Wang

Papers citing "Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild"

9 / 9 papers shown

Title
NF-SLAM: Effective, Normalizing Flow-supported Neural Field representations for object-level visual SLAM in automotive applications Li Cui Yang Ding Richard Hartley Zirui Xie L. Kneip Zhenghua Yu 41 0 0 14 Mar 2025
CrossOver: 3D Scene Cross-Modal Alignment S. Sarkar O. Mikšík Marc Pollefeys Daniel Barath Iro Armeni 3DPC 71 0 0 20 Feb 2025
L-PR: Exploiting LiDAR Fiducial Marker for Unordered Low Overlap Multiview Point Cloud Registration Yibo Liu Jinjun Shan Amaldev Haridevan Shuo Zhang 63 2 0 05 Jun 2024
CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation Jingkang Wang S. Manivasagam Yun Chen Ze Yang Ioan Andrei Bârsan A. Yang Wei-Chiu Ma R. Urtasun 3DV 35 24 0 02 Nov 2023
DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair N. Lamb Sean Banerjee N. Banerjee 3DV 27 7 0 22 Nov 2022
Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild Jianglong Ye Yuntao Chen Naiyan Wang Xiaolong Wang 3DPC 49 9 0 24 Nov 2021
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images Chen-Hsuan Lin Chaoyang Wang Simon Lucey 73 99 0 20 Oct 2020
Convolutional Occupancy Networks Songyou Peng Michael Niemeyer L. Mescheder Marc Pollefeys Andreas Geiger 3DV AI4CE 212 968 0 10 Mar 2020
PS-FCN: A Flexible Learning Framework for Photometric Stereo Guanying Chen Kai Han Kwan-Yee Kenneth Wong 46 134 0 23 Jul 2018