3DFR: A Swift 3D Feature Reductionist Framework for Scene Independent Change Detection

26 December 2019

Papers citing "3DFR: A Swift 3D Feature Reductionist Framework for Scene Independent Change Detection"

7 / 7 papers shown

Title
SAEN-BGS: Energy-Efficient Spiking AutoEncoder Network for Background Subtraction Zhenru Zhang Xuzhao Li Qiang Liu 31 0 0 12 May 2025
LangGas: Introducing Language in Selective Zero-Shot Background Subtraction for Semi-Transparent Gas Leak Detection with a New Dataset Wenqi Guo Yiyang Du Shan Du 81 1 0 04 Mar 2025
FADE: A Dataset for Detecting Falling Objects around Buildings in Video Zhigang Tu Zitao Gao Zhengbo Zhang Chunluan Zhou Junsong Yuan Bo Du 56 0 0 11 Aug 2024
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs Murari Mandal Santosh Kumar Vipparthi 27 83 0 04 May 2021
BSUV-Net 2.0: Spatio-Temporal Data Augmentations for Video-Agnostic Supervised Background Subtraction M. Tezcan Prakash Ishwar Janusz Konrad 21 77 0 23 Jan 2021
MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos Murari Mandal L. Kumar Santosh Kumar Vipparthi 36 48 0 04 Aug 2020
BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos M. Tezcan Prakash Ishwar Janusz Konrad VOS 29 96 0 26 Jul 2019