Learning to Detect Every Thing in an Open World

3 December 2021

Papers citing "Learning to Detect Every Thing in an Open World"

7 / 7 papers shown

Title
Generalized Class Discovery in Instance Segmentation Cuong Manh Hoang Yeejin Lee Byeongkeun Kang ISeg 87 0 0 12 Feb 2025
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance Robin Schon K. Ludwig Rainer Lienhart VLM MDE 22 2 0 12 Apr 2023
OpenInst: A Simple Query-Based Method for Open-World Instance Segmentation Cheng Wang Guoli Wang Qian Zhang Pengning Guo Wenyu Liu Xinggang Wang ISeg VLM 19 7 0 28 Mar 2023
Towards Generalized Few-Shot Open-Set Object Detection Binyi Su Hua Zhang Jingzhi Li Zhongjun Zhou 43 9 0 28 Oct 2022
Tunable Hybrid Proposal Networks for the Open World Matthew J. Inkawhich Nathan Inkawhich H. Li Yiran Chen 19 2 0 23 Aug 2022
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 168 686 0 22 Apr 2021
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 226 966 0 13 Dec 2020