About

The semantic segmentation task is to assign a label from a label set to each pixel in an image. In the case of fully supervised setting, the dataset consists of images and their corresponding pixel-level class-specific annotations (expensive pixel-level annotations). However, in the weakly-supervised setting, the dataset consists of images and corresponding annotations that are relatively easy to obtain, such as tags/labels of objects present in the image.

( Image credit: Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing )

Benchmarks

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Datasets

Greatest papers with code

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations

CVPR 2019 jiwoon-ahn/irn

For generating the pseudo labels, we first identify confident seed areas of object classes from attention maps of an image classification model, and propagate them to discover the entire instance areas with accurate boundaries.

IMAGE CLASSIFICATION INSTANCE SEGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

CVPR 2020 YudeWang/SEAM

Our method is based on the observation that equivariance is an implicit constraint in fully supervised semantic segmentation, whose pixel-level labels take the same spatial transformation as the input images during data augmentation.

DATA AUGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Spatio-temporal video autoencoder with differentiable memory

19 Nov 2015viorik/ConvLSTM

At each time step, the system receives as input a video frame, predicts the optical flow based on the current observation and the LSTM memory state as a dense transformation map, and applies it to the current frame to generate the next frame.

MOTION ESTIMATION OPTICAL FLOW ESTIMATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation

CVPR 2018 jiwoon-ahn/psa

To alleviate this issue, we present a novel framework that generates segmentation labels of images given their image-level class labels.

WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation

9 Feb 2015TheLegendAli/DeepLab-Context

Deep convolutional neural networks (DCNNs) trained on a large number of images with strong pixel-level annotations have recently significantly pushed the state-of-art in semantic image segmentation.

SEMI-SUPERVISED SEMANTIC SEGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing

CVPR 2018 speedinghzl/DSRG

Inspired by the traditional image segmentation methods of seeded region growing, we propose to train a semantic segmentation network starting from the discriminative regions and progressively increase the pixel-level supervision using by seeded region growing.

WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Weakly- and Semi-Supervised Panoptic Segmentation

ECCV 2018 qizhuli/Weakly-Supervised-Panoptic-Segmentation

We present a weakly supervised model that jointly performs both semantic- and instance-segmentation -- a particularly relevant problem given the substantial cost of obtaining pixel-perfect annotation for these tasks.

INSTANCE SEGMENTATION PANOPTIC SEGMENTATION WEAKLY-SUPERVISED INSTANCE SEGMENTATION WEAKLY-SUPERVISED PANOPTIC SEGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Constrained-CNN losses for weakly supervised segmentation

12 May 2018meng-tang/rloss

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.

MEDICAL IMAGE SEGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Weakly-Supervised Semantic Segmentation via Sub-category Exploration

CVPR 2020 Juliachang/SC-CAM

Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions.

WEAKLY-SUPERVISED SEMANTIC SEGMENTATION

Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation

ECCV 2020 GuoleiSun/MCIS_wsss

Moreover, our approach ranked 1st place in the Weakly-Supervised Semantic Segmentation Track of CVPR2020 Learning from Imperfect Data Challenge.

OBJECT LOCALIZATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION