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Learning Fully Dense Neural Networks for Image Semantic Segmentation

Learning Fully Dense Neural Networks for Image Semantic Segmentation

Mingmin Zhen
Jinglu Wang
Lei Zhou
Tian Fang
Long Quan
    SSeg
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Papers citing "Learning Fully Dense Neural Networks for Image Semantic Segmentation"

6 / 6 papers shown
Title
A Simple and Generalist Approach for Panoptic Segmentation
A Simple and Generalist Approach for Panoptic Segmentation
Nedyalko Prisadnikov
Wouter Van Gansbeke
Danda Pani Paudel
Luc Van Gool
VLM
53
0
0
29 Aug 2024
Spatial-information Guided Adaptive Context-aware Network for Efficient RGB-D Semantic Segmentation
Spatial-information Guided Adaptive Context-aware Network for Efficient RGB-D Semantic Segmentation
Yang Zhang
Chenyun Xiong
Junjie Liu
Xuhui Ye
Guodong Sun
36
15
0
11 Aug 2023
Weakly supervised training of universal visual concepts for multi-domain semantic segmentation
Weakly supervised training of universal visual concepts for multi-domain semantic segmentation
Petra Bevandić
Marin Orsic
Ivan Grubišić
Josip Saric
Sinisa Segvic
36
5
0
20 Dec 2022
Transferable Semantic Augmentation for Domain Adaptation
Transferable Semantic Augmentation for Domain Adaptation
Shuang Li
Mixue Xie
Kaixiong Gong
Chi Harold Liu
Yulin Wang
Wei Li
TTA
30
123
0
23 Mar 2021
Joint Semantic Segmentation and Boundary Detection using Iterative Pyramid Contexts
Joint Semantic Segmentation and Boundary Detection using Iterative Pyramid Contexts
Mingmin Zhen
Jinglu Wang
Lei Zhou
Shiwei Li
Tianwei Shen
Jiaxiang Shang
Tian Fang
Quan Long
24
129
0
16 Apr 2020
SEMEDA: Enhancing Segmentation Precision with Semantic Edge Aware Loss
SEMEDA: Enhancing Segmentation Precision with Semantic Edge Aware Loss
Yifu Chen
Arnaud Dapogny
Matthieu Cord
SSeg
24
24
0
06 May 2019