FGN: Fully Guided Network for Few-Shot Instance Segmentation

31 March 2020

Papers citing "FGN: Fully Guided Network for Few-Shot Instance Segmentation"

8 / 8 papers shown

Title
Zero-Shot Automatic Annotation and Instance Segmentation using LLM-Generated Datasets: Eliminating Field Imaging and Manual Annotation for Deep Learning Model Development Ranjan Sapkota Achyut Paudel Manoj Karkee SyDa 55 7 0 18 Nov 2024
Integrated Image-Text Based on Semi-supervised Learning for Small Sample Instance Segmentation Ruting Chi Zhiyi Huang Yuexing Han ISeg 23 0 0 21 Oct 2024
BIV-Priv-Seg: Locating Private Content in Images Taken by People With Visual Impairments Yu-Yun Tseng Tanusree Sharma Lotus Zhang Abigale Stangl Leah Findlater Yang Wang Danna Gurari 61 0 0 25 Jul 2024
ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation Moon Ye-Bin D. Choi Y. Kwon Junsik Kim Tae-Hyun Oh ISeg 25 6 0 20 Feb 2023
Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentation Yue Han Jiangning Zhang Zhucun Xue Chao Xu Xintian Shen Yabiao Wang Chengjie Wang Yong Liu Xiangtai Li 27 16 0 03 Jan 2023
VizWiz-FewShot: Locating Objects in Images Taken by People With Visual Impairments Yu-Yun Tseng Alexander Bell Danna Gurari 19 8 0 24 Jul 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities Yisheng Song Ting-Yuan Wang S. Mondal J. P. Sahoo SLR 36 341 0 13 May 2022
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning Xiaopeng Yan Ziliang Chen Anni Xu Xiaoxi Wang Xiaodan Liang Liang Lin ObjD 154 440 0 28 Sep 2019