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Semantic Segmentation

847 papers with code · Computer Vision

Semantic segmentation, or image segmentation, is the task of clustering parts of an image together which belong to the same object class. It is a form of pixel-level prediction because each pixel in an image is classified according to a category.

Some example benchmarks for this task are Cityscapes, PASCAL VOC and ADE20K. Models are usually evaluated with the Mean Intersection-Over-Union (Mean IoU) and Pixel Accuracy metrics.

( Image credit: CSAILVision )

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Latest papers without code

The Edge of Depth: Explicit Constraints between Segmentation and Depth

1 Apr 2020

In this work we study the mutual benefits of two common computer vision tasks, self-supervised depth estimation and semantic segmentation from images.

MONOCULAR DEPTH ESTIMATION SEMANTIC SEGMENTATION

Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation

31 Mar 2020

To satisfy the stringent requirements on computational resources in the field of real-time semantic segmentation, most approaches focus on the hand-crafted design of light-weight segmentation networks.

NEURAL ARCHITECTURE SEARCH REAL-TIME SEMANTIC SEGMENTATION

Attention-based Assisted Excitation for Salient Object Segmentation

31 Mar 2020

In this paper, object-based attention in human visual cortex inspires us to introduce a mechanism for modification of activations in feature maps of CNNs.

SEMANTIC SEGMENTATION

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

31 Mar 2020

The proposed method outperforms state-of-the-art segmentation methods on the public RETOUCH dataset having images captured from different acquisition procedures.

DATA AUGMENTATION IMAGE GENERATION MEDICAL IMAGE SEGMENTATION SEMANTIC SEGMENTATION

BANet: Bidirectional Aggregation Network with Occlusion Handling for Panoptic Segmentation

31 Mar 2020

Panoptic segmentation aims to perform instance segmentation for foreground instances and semantic segmentation for background stuff simultaneously.

INSTANCE SEGMENTATION PANOPTIC SEGMENTATION

FGN: Fully Guided Network for Few-Shot Instance Segmentation

31 Mar 2020

Few-shot instance segmentation (FSIS) conjoins the few-shot learning paradigm with general instance segmentation, which provides a possible way of tackling instance segmentation in the lack of abundant labeled data for training.

FEW-SHOT LEARNING INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Segmenting Transparent Objects in the Wild

31 Mar 2020

To address this important problem, this work proposes a large-scale dataset for transparent object segmentation, named Trans10K, consisting of 10, 428 images of real scenarios with carefully manual annotations, which are 10 times larger than the existing datasets.

SEMANTIC SEGMENTATION

Attention-based Multi-modal Fusion Network for Semantic Scene Completion

31 Mar 2020

This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the occupancy and semantic labels of a volumetric 3D scene from single-view RGB-D images.

SEMANTIC SEGMENTATION

EOLO: Embedded Object Segmentation only Look Once

31 Mar 2020

In this paper, we introduce an anchor-free and single-shot instance segmentation method, which is conceptually simple with 3 independent branches, fully convolutional and can be used by easily embedding it into mobile and embedded devices.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Weakly-supervised land classification for coastal zone based on deep convolutional neural networks by incorporating dual-polarimetric characteristics into training dataset

30 Mar 2020

In this work we explore the performance of DCNNs on semantic segmentation using spaceborne polarimetric synthetic aperture radar (PolSAR) datasets.

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