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Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation

Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation

Xiaoyu Zhao
Xiaoqian Chen
Zhiqiang Gong
Wen Yao
Yunyang Zhang
Xiaohu Zheng
    VLM
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Papers citing "Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation"

4 / 4 papers shown
Title
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
Zhihe Lu
Sen He
Xiatian Zhu
Li Zhang
Yi-Zhe Song
Tao Xiang
ViT
171
173
0
06 Aug 2021
Learning Meta-class Memory for Few-Shot Semantic Segmentation
Learning Meta-class Memory for Few-Shot Semantic Segmentation
Zhonghua Wu
Xiangxi Shi
Guosheng lin
Jianfei Cai
VLM
78
108
0
06 Aug 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
526
11,727
0
09 Mar 2017
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
475
15,657
0
02 Nov 2015