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Panoptic Segmentation Edit

17 papers with code · Computer Vision

Panoptic segmentation unifies the typically distinct tasks of semantic segmentation (assign a class label to each pixel) and instance segmentation (detect and segment each object instance).

( Image credit: Detectron2 )

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Mask R-CNN

Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.

64,128

Panoptic Feature Pyramid Networks

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.

10,432

ResNeSt: Split-Attention Networks

19 Apr 2020dmlc/gluon-cv

While image classification models have recently continued to advance, most downstream applications such as object detection and semantic segmentation still employ ResNet variants as the backbone network due to their simple and modular structure.

3,930

End-to-End Object Detection with Transformers

26 May 2020facebookresearch/detr

We present a new method that views object detection as a direct set prediction problem.

2,710

SOLOv2: Dynamic, Faster and Stronger

23 Mar 2020aim-uofa/AdelaiDet

Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.

777

UPSNet: A Unified Panoptic Segmentation Network

More importantly, we introduce a parameter-free panoptic head which solves the panoptic segmentation via pixel-wise classification.

505

CenterMask : Real-Time Anchor-Free Instance Segmentation

We hope that CenterMask and VoVNetV2 can serve as a solid baseline of real-time instance segmentation and backbone network for various vision tasks, respectively.

#3 best model for Instance Segmentation on COCO test-dev (AP50 metric)

489

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

We introduce a fast and efficient convolutional neural network, ESPNet, for semantic segmentation of high resolution images under resource constraints.

434

AdaptIS: Adaptive Instance Selection Network

Given an input image and a point $(x, y)$, it generates a mask for the object located at $(x, y)$.

286

Seamless Scene Segmentation

In this work we introduce a novel, CNN-based architecture that can be trained end-to-end to deliver seamless scene segmentation results.

204