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Semantic Segmentation

779 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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Greatest papers with code

ParseNet: Looking Wider to See Better

15 Jun 2015tensorflow/models

When we add our proposed global feature, and a technique for learning normalization parameters, accuracy increases consistently even over our improved versions of the baselines.

SEMANTIC SEGMENTATION

Learning to Segment Every Thing

CVPR 2018 facebookresearch/detectron

Most methods for object instance segmentation require all training examples to be labeled with segmentation masks.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Mask Scoring R-CNN

CVPR 2019 open-mmlab/mmdetection

In this paper, we study this problem and propose Mask Scoring R-CNN which contains a network block to learn the quality of the predicted instance masks.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Hybrid Task Cascade for Instance Segmentation

CVPR 2019 open-mmlab/mmdetection

In exploring a more effective approach, we find that the key to a successful instance segmentation cascade is to fully leverage the reciprocal relationship between detection and segmentation.

 SOTA for Instance Segmentation on COCO test-dev (using extra training data)

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

Deformable ConvNets v2: More Deformable, Better Results

CVPR 2019 open-mmlab/mmdetection

The superior performance of Deformable Convolutional Networks arises from its ability to adapt to the geometric variations of objects.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

PointRend: Image Segmentation as Rendering

17 Dec 2019facebookresearch/detectron2

We present a new method for efficient high-quality image segmentation of objects and scenes.

SEMANTIC SEGMENTATION

TensorMask: A Foundation for Dense Object Segmentation

ICCV 2019 facebookresearch/detectron2

To formalize this, we treat dense instance segmentation as a prediction task over 4D tensors and present a general framework called TensorMask that explicitly captures this geometry and enables novel operators on 4D tensors.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

Panoptic Feature Pyramid Networks

CVPR 2019 facebookresearch/detectron2

In this work, we perform a detailed study of this minimally extended version of Mask R-CNN with FPN, which we refer to as Panoptic FPN, and show it is a robust and accurate baseline for both tasks.

INSTANCE SEGMENTATION PANOPTIC SEGMENTATION