原始連結:https://github.com/amusi/awesome-object-detection

object-detection

This is a list of awesome articles about object detection.

• R-CNN
• Fast R-CNN
• Faster R-CNN
• Light-Head R-CNN
• Cascade R-CNN
• SPP-Net
• YOLO
• YOLOv2
• YOLOv3
• YOLT
• SSD
• DSSD
• FSSD
• ESSD
• MDSSD
• Pelee
• Fire SSD
• R-FCN
• FPN
• DSOD
• RetinaNet
• MegNet
• RefineNet
• DetNet
• SSOD
• 3D Object Detection
• ZSD（Zero-Shot Object Detection）
• OSD（One-Shot object Detection）
• Other

Papers&Codes

R-CNN

Rich feature hierarchies for accurate object detection and semantic segmentation

Fast R-CNN

Fast R-CNN

A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

Faster R-CNN

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

R-CNN minus R

Faster R-CNN in MXNet with distributed implementation and data parallelization

Contextual Priming and Feedback for Faster R-CNN

An Implementation of Faster RCNN with Study for Region Sampling

Interpretable R-CNN

• intro: North Carolina State University & Alibaba
• keywords: AND-OR Graph (AOG)

Light-Head R-CNN

Light-Head R-CNN: In Defense of Two-Stage Object Detector

Cascade R-CNN

Cascade R-CNN: Delving into High Quality Object Detection

SPP-Net

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection

Object Detectors Emerge in Deep Scene CNNs

segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection

Object Detection Networks on Convolutional Feature Maps

Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction

DeepBox: Learning Objectness with Convolutional Networks

YOLO

You Only Look Once: Unified, Real-Time Object Detection

darkflow - translate darknet to tensorflow. Load trained weights, retrain/fine-tune them using tensorflow, export constant graph def to C++

Start Training YOLO with Our Own Data

YOLO: Core ML versus MPSNNGraph

TensorFlow YOLO object detection on Android

• intro: Real-time object detection on Android using the YOLO network with TensorFlow

Computer Vision in iOS – Object Detection

YOLOv2

YOLO9000: Better, Faster, Stronger

darknet_scripts

• intro: Auxilary scripts to work with (YOLO) darknet deep learning famework. AKA -> How to generate YOLO anchors?

Yolo_mark: GUI for marking bounded boxes of objects in images for training Yolo v2

LightNet: Bringing pjreddie's DarkNet out of the shadows

YOLO v2 Bounding Box Tool

• intro: Bounding box labeler tool to generate the training data in the format YOLO v2 requires.

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

• intro: LRM is the first hard example mining strategy which could fit YOLOv2 perfectly and make it better applied in series of real scenarios where both real-time rates and accurate detection are strongly demanded.

Object detection at 200 Frames Per Second

Event-based Convolutional Networks for Object Detection in Neuromorphic Cameras

• intro: YOLE--Object Detection in Neuromorphic Cameras

OmniDetector: With Neural Networks to Bounding Boxes

YOLOv3

YOLOv3: An Incremental Improvement

YOLT

You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

SSD

SSD: Single Shot MultiBox Detector

What's the diffience in performance between this new code you pushed and the previous code? #327

DSSD

DSSD : Deconvolutional Single Shot Detector

Enhancement of SSD by concatenating feature maps for object detection

Context-aware Single-Shot Detector

• keywords: CSSD, DiCSSD, DeCSSD, effective receptive fields (ERFs), theoretical receptive fields (TRFs)

Feature-Fused SSD: Fast Detection for Small Objects

FSSD

FSSD: Feature Fusion Single Shot Multibox Detector

Weaving Multi-scale Context for Single Shot Detector

• intro: WeaveNet
• keywords: fuse multi-scale information

ESSD

Extend the shallow part of Single Shot MultiBox Detector via Convolutional Neural Network

Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection

MDSSD

MDSSD: Multi-scale Deconvolutional Single Shot Detector for small objects

Pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

Fire SSD

Fire SSD: Wide Fire Modules based Single Shot Detector on Edge Device

• intro:low cost, fast speed and high mAP on factor edge computing devices

R-FCN

R-FCN: Object Detection via Region-based Fully Convolutional Networks

R-FCN-3000 at 30fps: Decoupling Detection and Classification

Recycle deep features for better object detection

FPN

Feature Pyramid Networks for Object Detection

Action-Driven Object Detection with Top-Down Visual Attentions

Beyond Skip Connections: Top-Down Modulation for Object Detection

Wide-Residual-Inception Networks for Real-time Object Detection

Attentional Network for Visual Object Detection

• intro: University of Maryland & Mitsubishi Electric Research Laboratories

Learning Chained Deep Features and Classifiers for Cascade in Object Detection

• keykwords: CC-Net
• intro: chained cascade network (CC-Net). 81.1% mAP on PASCAL VOC 2007

DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling

Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries

Spatial Memory for Context Reasoning in Object Detection

Accurate Single Stage Detector Using Recurrent Rolling Convolution

Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection

LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems

• intro: Embedded Vision Workshop in CVPR. UC San Diego & Qualcomm Inc

Point Linking Network for Object Detection

Perceptual Generative Adversarial Networks for Small Object Detection

Few-shot Object Detection

Yes-Net: An effective Detector Based on Global Information

SMC Faster R-CNN: Toward a scene-specialized multi-object detector

Towards lightweight convolutional neural networks for object detection

RON: Reverse Connection with Objectness Prior Networks for Object Detection

Mimicking Very Efficient Network for Object Detection

Residual Features and Unified Prediction Network for Single Stage Detection

Deformable Part-based Fully Convolutional Network for Object Detection

• intro: BMVC 2017 (oral). Sorbonne Universités & CEDRIC

Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors

Recurrent Scale Approximation for Object Detection in CNN

DSOD

DSOD: Learning Deeply Supervised Object Detectors from Scratch

Learning Object Detectors from Scratch with Gated Recurrent Feature Pyramids

RetinaNet

Focal Loss for Dense Object Detection

• intro: ICCV 2017 Best student paper award. Facebook AI Research
• keywords: RetinaNet

CoupleNet: Coupling Global Structure with Local Parts for Object Detection

Incremental Learning of Object Detectors without Catastrophic Forgetting

Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection

StairNet: Top-Down Semantic Aggregation for Accurate One Shot Detection

Dynamic Zoom-in Network for Fast Object Detection in Large Images

Zero-Annotation Object Detection with Web Knowledge Transfer

• intro: NTU, Singapore & Amazon
• keywords: multi-instance multi-label domain adaption learning framework

MegDet

MegDet: A Large Mini-Batch Object Detector

• intro: Peking University & Tsinghua University & Megvii Inc

Receptive Field Block Net for Accurate and Fast Object Detection

An Analysis of Scale Invariance in Object Detection - SNIP

Feature Selective Networks for Object Detection

Learning a Rotation Invariant Detector with Rotatable Bounding Box

Scalable Object Detection for Stylized Objects

Learning Object Detectors from Scratch with Gated Recurrent Feature Pyramids

Deep Regionlets for Object Detection

• keywords: region selection network, gating network

Training and Testing Object Detectors with Virtual Images

Large-Scale Object Discovery and Detector Adaptation from Unlabeled Video

• keywords: object mining, object tracking, unsupervised object discovery by appearance-based clustering, self-supervised detector adaptation

Spot the Difference by Object Detection

Localization-Aware Active Learning for Object Detection

Object Detection with Mask-based Feature Encoding

LSTD: A Low-Shot Transfer Detector for Object Detection

Domain Adaptive Faster R-CNN for Object Detection in the Wild

Pseudo Mask Augmented Object Detection

Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

Learning Region Features for Object Detection

Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection

• intro: Singapore Management University & Zhejiang University

Object Detection for Comics using Manga109 Annotations

• intro: University of Tokyo & National Institute of Informatics, Japan

Task-Driven Super Resolution: Object Detection in Low-resolution Images

Transferring Common-Sense Knowledge for Object Detection

Multi-scale Location-aware Kernel Representation for Object Detection

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

• intro: National University of Defense Technology

Robust Physical Adversarial Attack on Faster R-CNN Object Detector

RefineNet

Single-Shot Refinement Neural Network for Object Detection

DetNet

DetNet: A Backbone network for Object Detection

SSOD

Self-supervisory Signals for Object Discovery and Detection

3D Object Detection

LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDARs

ZSD

Zero-Shot Detection

• intro: Australian National University
• keywords: YOLO

Zero-Shot Object Detection

Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts

Zero-Shot Object Detection by Hybrid Region Embedding

OSD

One-Shot Object Detection

RepMet: Representative-based metric learning for classification and one-shot object detection

2018

MetaAnchor: Learning to Detect Objects with Customized Anchors

Relation Network for Object Detection

Quantization Mimic: Towards Very Tiny CNN for Object Detection

• Tsinghua University1 & The Chinese University of Hong Kong2 &SenseTime3

Learning Rich Features for Image Manipulation Detection

SNIPER: Efficient Multi-Scale Training

Soft Sampling for Robust Object Detection

• intro: the robustness of object detection under the presence of missing annotations

Cost-effective Object Detection: Active Sample Mining with Switchable Selection Criteria