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Instance segmentation is the task of detecting and delineating each distinct object of interest appearing in an image.

( Image credit: Weakly Supervised Panoptic Segmentation )

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Greatest papers with code

The surprising impact of mask-head architecture on novel class segmentation

1 Apr 2021tensorflow/models

Within this family, we show that the architecture of the mask-head plays a surprisingly important role in generalization to classes for which we do not observe masks during training.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

CVPR 2020 tensorflow/models

We propose SpineNet, a backbone with scale-permuted intermediate features and cross-scale connections that is learned on an object detection task by Neural Architecture Search.

IMAGE CLASSIFICATION INSTANCE SEGMENTATION NEURAL ARCHITECTURE SEARCH REAL-TIME OBJECT DETECTION

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

Non-local Neural Networks

CVPR 2018 facebookresearch/detectron

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time.

Ranked #8 on Keypoint Detection on COCO (Validation AP metric)

ACTION CLASSIFICATION ACTION RECOGNITION INSTANCE SEGMENTATION KEYPOINT DETECTION OBJECT DETECTION

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-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

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