Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts

2 July 2024

Papers citing "Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts"

5 / 5 papers shown

Title
MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance Hallee E. Wong Jose Javier Gonzalez Ortiz John Guttag Adrian V. Dalca 80 0 0 19 Dec 2024
Segment Any Class (SAC): Multi-Class Few-Shot Semantic Segmentation via Class Region Proposals Hussni Mohd Zakir Eric Tatt Wei Ho VLM 64 0 0 21 Nov 2024
Edit Everything: A Text-Guided Generative System for Images Editing Defeng Xie Ruichen Wang Jiancang Ma Chen Chen H. Lu D. Yang Fobo Shi Xiaodong Lin DiffM 80 31 0 27 Apr 2023
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,659 0 09 Mar 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 232 75,445 0 18 May 2015