Weakly supervised segmentation

64 papers with code • 0 benchmarks • 3 datasets

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Most implemented papers

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

IntuitionMachines/OrigamiNet CVPR 2020

On IAM we even surpass single line methods that use accurate localization information during training.

Learn To Pay Attention

SaoYan/LearnToPayAttention ICLR 2018

We propose an end-to-end-trainable attention module for convolutional neural network (CNN) architectures built for image classification.

Constrained-CNN losses for weakly supervised segmentation

LIVIAETS/SizeLoss_WSS 12 May 2018

To the best of our knowledge, the method of [Pathak et al., 2015] is the only prior work that addresses deep CNNs with linear constraints in weakly supervised segmentation.

WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

hilab-git/word 3 Nov 2021

Deep learning-based medical image segmentation has shown the potential to reduce manual delineation efforts, but it still requires a large-scale fine annotated dataset for training, and there is a lack of large-scale datasets covering the whole abdomen region with accurate and detailed annotations for the whole abdominal organ segmentation.

Integral Object Mining via Online Attention Accumulation

PengtaoJiang/OAA-PyTorch ICCV 2019

In order to accumulate the discovered different object parts, we propose an online attention accumulation (OAA) strategy which maintains a cumulative attention map for each target category in each training image so that the integral object regions can be gradually promoted as the training goes.

Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty

sbelharbi/deep-wsl-histo-min-max-uncertainty 14 Nov 2020

We propose novel regularization terms, which enable the model to seek both non-discriminative and discriminative regions, while discouraging unbalanced segmentations.

Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs

biomedsciai/histocartography 4 Mar 2021

Thus, weakly-supervised semantic segmentation techniques are proposed to utilize weak supervision that is cheaper and quicker to acquire.

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations

kangningthu/adele CVPR 2022

We discover a phenomenon that has been previously reported in the context of classification: the networks tend to first fit the clean pixel-level labels during an "early-learning" phase, before eventually memorizing the false annotations.

Land Cover Segmentation with Sparse Annotations from Sentinel-2 Imagery

links-ads/igarss-spada 28 Jun 2023

Land cover (LC) segmentation plays a critical role in various applications, including environmental analysis and natural disaster management.

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

pathak22/ccnn ICCV 2015

We propose Constrained CNN (CCNN), a method which uses a novel loss function to optimize for any set of linear constraints on the output space (i. e. predicted label distribution) of a CNN.