Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation

11/22/2019
by   Bowen Cheng, et al.
10

In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast system for panoptic segmentation, aiming to establish a solid baseline for bottom-up methods that can achieve comparable performance of two-stage methods while yielding fast inference speed. In particular, PanopticDeepLab adopts the dual-ASPP and dual-decoder structures specific to semantic, and instance segmentation, respectively. 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. As a result, our single Panoptic-DeepLab simultaneously ranks first at all three Cityscapes benchmarks, setting the new state-of-art of 84.2 MobileNetV3, Panoptic-DeepLab runs nearly in real-time with a single 1025 x 2049 image (15.8 frames per second), while achieving a competitive performance on Cityscapes (54.1 PQ ensemble of six models attains 42.7 2018 by a healthy margin of 1.5 on par with several topdown approaches on the challenging COCO dataset. For the first time, we demonstrate a bottom-up approach could deliver state-of-the-art results on panoptic segmentation.

READ FULL TEXT

page 1

page 8

page 10

page 14

page 15

page 16

10/10/2019

Panoptic-DeepLab

We present Panoptic-DeepLab, a bottom-up and single-shot approach for pa...
01/08/2019

Panoptic Feature Pyramid Networks

The recently introduced panoptic segmentation task has renewed our commu...
09/29/2019

PolarMask: Single Shot Instance Segmentation with Polar Representation

In this paper, we introduce an anchor-box free and single shot instance ...
04/24/2018

SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach

The SimpleQuestions dataset is one of the most commonly used benchmarks ...
03/31/2020

EOLO: Embedded Object Segmentation only Look Once

In this paper, we introduce an anchor-free and single-shot instance segm...
10/08/2022

Sequential Ensembling for Semantic Segmentation

Ensemble approaches for deep-learning-based semantic segmentation remain...
08/23/2020

Seesaw Loss for Long-Tailed Instance Segmentation

This report presents the approach used in the submission of the LVIS Cha...

Code Repositories

panoptic-deeplab

This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)


view repo

Poster_presentation_unlv_REUsummer2021

None


view repo

Overview-of-REU-Summer-2021-Smart-Cities-UNLV-

None


view repo

panoptic-deeplab

Implementation of the paper: https://arxiv.org/pdf/1911.10194.pdf


view repo

PanopticCenter

PanopticCenter Network


view repo

Please sign up or login with your details

Forgot password? Click here to reset