Dichotomous Image Segmentation

18 papers with code • 5 benchmarks • 1 datasets

Currently, existing image segmentation tasks mainly focus on segmenting objects with specific characteristics, e.g., salient, camouflaged, meticulous, or specific categories. Most of them have the same input/output formats, and barely use exclusive mechanisms designed for segmenting targets in their models, which means almost all tasks are dataset-dependent. Thus, it is very promising to formulate a category-agnostic DIS task for accurately segmenting objects with different structure complexities, regardless of their characteristics. Compared with semantic segmentation, the proposed DIS task usually focuses on images with single or a few targets, from which getting richer accurate details of each target is more feasible.

Libraries

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6 papers
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Datasets


Most implemented papers

U-Net: Convolutional Networks for Biomedical Image Segmentation

labmlai/annotated_deep_learning_paper_implementations 18 May 2015

There is large consent that successful training of deep networks requires many thousand annotated training samples.

Rethinking Atrous Convolution for Semantic Image Segmentation

tensorflow/models 17 Jun 2017

To handle the problem of segmenting objects at multiple scales, we design modules which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates.

Pyramid Scene Parsing Network

hszhao/PSPNet CVPR 2017

Scene parsing is challenging for unrestricted open vocabulary and diverse scenes.

Searching for MobileNetV3

tensorflow/models ICCV 2019

We achieve new state of the art results for mobile classification, detection and segmentation.

Deep High-Resolution Representation Learning for Visual Recognition

open-mmlab/mmdetection 20 Aug 2019

High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection.

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

NathanUA/U-2-Net 18 May 2020

In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

PaddlePaddle/PaddleSeg ECCV 2018

Semantic segmentation requires both rich spatial information and sizeable receptive field.

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

hszhao/ICNet ECCV 2018

We focus on the challenging task of real-time semantic segmentation in this paper.

Rethinking BiSeNet For Real-time Semantic Segmentation

MichaelFan01/STDC-Seg CVPR 2021

BiSeNet has been proved to be a popular two-stream network for real-time segmentation.

F3Net: Fusion, Feedback and Focus for Salient Object Detection

weijun88/F3Net 26 Nov 2019

Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.