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A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of
  Foundation Models

A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models

20 January 2024
Reda Bensaid
Vincent Gripon
Franccois Leduc-Primeau
Lukas Mauch
G. B. Hacene
Fabien Cardinaux
    VLM
ArXivPDFHTML

Papers citing "A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models"

6 / 6 papers shown
Title
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment
  Anything Model
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong
Zhiqiang Tang
Tong He
Haoyang Fang
Chun Yuan
33
40
0
31 Jan 2024
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
258
7,412
0
11 Nov 2021
Learning to Prompt for Vision-Language Models
Learning to Prompt for Vision-Language Models
Kaiyang Zhou
Jingkang Yang
Chen Change Loy
Ziwei Liu
VPVLM
CLIP
VLM
322
2,249
0
02 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
298
5,761
0
29 Apr 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
243
11,659
0
09 Mar 2017
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
249
1,821
0
18 Aug 2016
1