About

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 )

Benchmarks

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Greatest papers with code

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

ECCV 2020 tensorflow/models

We view this work as a notable step towards building a simple procedure to harness unlabeled video sequences and extra images to surpass state-of-the-art performance on core computer vision tasks.

OPTICAL FLOW ESTIMATION PANOPTIC SEGMENTATION PATCH MATCHING SCENE SEGMENTATION

FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

CVPR 2019 tensorflow/models

Many of the recent successful methods for video object segmentation (VOS) are overly complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of limited practical use.

SEMANTIC SEGMENTATION SEMI-SUPERVISED VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

CVPR 2019 tensorflow/models

Therefore, we propose to search the network level structure in addition to the cell level structure, which forms a hierarchical architecture search space.

IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH SEMANTIC SEGMENTATION

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

NeurIPS 2018 tensorflow/models

Recent progress has demonstrated that such meta-learning methods may exceed scalable human-invented architectures on image classification tasks.

IMAGE CLASSIFICATION META-LEARNING SEMANTIC SEGMENTATION STREET SCENE PARSING

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

PointRend: Image Segmentation as Rendering

CVPR 2020 facebookresearch/detectron2

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

INSTANCE SEGMENTATION 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

Panoptic-DeepLab

10 Oct 2019facebookresearch/detectron2

The semantic segmentation branch is the same as the typical design of any semantic segmentation model (e. g., DeepLab), while the instance segmentation branch is class-agnostic, involving a simple instance center regression.

INSTANCE SEGMENTATION PANOPTIC SEGMENTATION

Pointly-Supervised Instance Segmentation

13 Apr 2021facebookresearch/detectron2

Our experiments show that the new module is more suitable for the proposed point-based supervision.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION