【论文笔记】Anchor-free目标检测论文推荐

前言

 Anchor-free 目标检测是目标检测近几年的主流趋势之一，本文分享一个汇总了最近几年Anchor-free论文的github项目。

Anchor-free目标检测

项目作者：Xin Zhang, Xuesong Wang, nuo xu

地址：https://github.com/XinZhangNLPR/awesome-anchor-free-object-detection

本项目共计涵盖 24篇anchor-free目标检测论文，其中论文大多为顶会且已开源！

• 论文以年份进行归类划分（从2015到2020）

• 每篇论文给出了是否收录的状态（如arXiv，CVPR）

• 已开源的论文给出了相应实现的框架名称（如PyTorch）

• 已开源的论文star数量>100，则带有  标识

2020

• [arXiv] OneNet: End-to-End One-Stage Object Detection by Classification Cost.[pytorch]

• [arXiv] End-to-End Object Detection with Fully Convolutional Network

• [arXiv] Sparse R-CNN: End-to-End Object Detection with Learnable Proposals.[pytorch]

• [arXiv] End-to-End Object Detection with Transformers.[pytorch]

• [arXiv] AutoAssign: Differentiable Label Assignment for Dense Object Detection.

• [arXiv] RepPoints V2: Verification Meets Regression for Object Detection. [pytorch]

• [ECCV] Corner Proposal Network for Anchor-free, Two-stage Object Detection. [Available soon]

• [ECCV] HoughNet: Integrating near and long-range evidence for bottom-up object detection. [pytorch]

• [CVPR] Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection. [pytorch]

• [CVPR] Soft Anchor-Point Object Detection. [Keras]

• [CVPR] CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection. [pytorch]

• [arXiv] SaccadeNet: A Fast and Accurate Object Detector. [pytorch]

• [arXiv] Localization Uncertainty Estimation for Anchor-Free Object Detection.

• [ECCV] Dense RepPoints: Representing Visual Objects with Dense Point Sets. [pytorch]

• [ECCV] BorderDet: Border Feature for Dense Object Detection. [pytorch]

• [arXiv] Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection. [pytorch]

2019

• [ICCV] RepPoints: Point Set Representation for Object Detection. [pytorch]

• [arXiv] Segmentation is All You Need.

• [arXiv] FCOS: Fully Convolutional One-Stage Object Detection. [pytorch]

• [arXiv] CenterNet: Keypoint Triplets for Object Detection. [pytorch]

• [arXiv] Objects as Points. [pytorch]

• [arXiv] FoveaBox: Beyond Anchor-based Object Detector. [pytorch]

• [CVPR] Feature Selective Anchor-Free Module for Single-Shot Object Detection. [pytorch]

• [arXiv] ExtremeNet: Bottom-up Object Detection by Grouping Extreme and Center Points. [pytorch]

2018

• [ECCV] CornerNet: Detecting Objects as Paired Keypoints. [pytorch]

• [arXiv] An Anchor-Free Region Proposal Network for Faster R-CNN based Text Detection Approaches.

2016

• [CVPR] You Only Look Once: Unified, Real-Time Object Detection. [tensorflow] [darknet]

• [acm multimedia] UnitBox: An Advanced Object Detection Network. [tensorflow]

2015

• [arXiv] DenseBox: Unifying Landmark Localization with End to End Object Detection. [caffe]