Learning Accurate Dense Correspondences and When to Trust Them

Learning Accurate Dense Correspondences and When to Trust Them

5 January 2021

Martin Danelljan

Luc Van Gool

Radu Timofte

Papers citing "Learning Accurate Dense Correspondences and When to Trust Them"

11 / 11 papers shown

Title
$IM360: Textured Mesh Reconstruction for Large-scale Indoor Mapping with 360$^\circ$ Cameras$ IM360: Textured Mesh Reconstruction for Large-scale Indoor Mapping with 360 $^\circ$ Cameras Dongki Jung Jaehoon Choi Yonghan Lee Dinesh Manocha 35 0 0 20 Feb 2025
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training Xingyi He He Hao Yu Sida Peng Dongli Tan Zehong Shen Hujun Bao Xiaowei Zhou 33 3 0 13 Jan 2025
OmniGlue: Generalizable Feature Matching with Foundation Model Guidance Hanwen Jiang Arjun Karpur Bingyi Cao Qixing Huang André Araujo VLM 21 27 0 21 May 2024
Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence Junyi Zhang Charles Herrmann Junhwa Hur Eric Chen Varun Jampani Deqing Sun Ming-Hsuan Yang 6 37 0 28 Nov 2023
BASED: Bundle-Adjusting Surgical Endoscopic Dynamic Video Reconstruction using Neural Radiance Fields Shreya Saha Sainan Liu Shan Lin Jingpei Lu Michael C. Yip Sainan Liu MedIm 24 4 0 27 Sep 2023
Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases Eugen Šlapak Enric Pardo Matús Dopiriak T. Maksymyuk Juraj Gazda AI4CE 4 11 0 14 Aug 2023
Supervised Homography Learning with Realistic Dataset Generation Hai Jiang Haipeng Li Songchen Han Haoqiang Fan Bing Zeng Shuaicheng Liu GAN 12 8 0 28 Jul 2023
Dyn-E: Local Appearance Editing of Dynamic Neural Radiance Fields Shangzhan Zhang Sida Peng Yinji ShenTu Qing Shuai Tianrun Chen Kaicheng Yu Hujun Bao Xiaowei Zhou 38 7 0 24 Jul 2023
NeuralMarker: A Framework for Learning General Marker Correspondence Zhaoyang Huang Xiao Pan Weihong Pan Weikang Bian Yan Xu Ka Chun Cheung Guofeng Zhang Hongsheng Li 17 5 0 19 Sep 2022
Semantic Understanding of Scenes through the ADE20K Dataset Bolei Zhou Hang Zhao Xavier Puig Tete Xiao Sanja Fidler Adela Barriuso Antonio Torralba SSeg 243 1,817 0 18 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 243 9,042 0 06 Jun 2015