Most popular metrics used to evaluate object detection algorithms. - rafaelpadilla/Object-Detection-Metrics
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch. - facebookresearch/maskrcnn-benchmark
Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework. At FAIR, Detectron has enabled numerous research projects, including: Feature Pyramid ...
Implementations in open-source frameworks publicly available (e.g., pre-trained models and source code published in github) Hereplease find a collection of papers and comments on deep-learning based detection and tracking models. What is the state of the art object detection algorithm in 2018 ?
Welcome to evalsaliency, a Matlab toolbox for evaluating salient object detection algorithms. This toolbox has been utilized to achieve experimental result presented in the following paper: ##Xi Li, Yao Li, Chunhua Shen, Anthony Dick, Anton van den Hengel. Contextual Hypergraph Modeling for Salien...
Weakly-supervised object detection. Contribute to NVlabs/wetectron development by creating an account on GitHub.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. Python Apache-2.0 5,296 0 0 0 Updated Jan 22, 2018 faster-rcnn.pytorch Forked from jwyang/faster-rcnn.pytorch A faster pytorch implementation of faster r-cnn Python MI...
RRC - "Accurate Single Stage Detector Using Recurrent Rolling Convolution" (2017)arXiv:1704.05776,github RUN - "Residual Features and Unified Prediction Network for Single Stage Detection" (2017)arXiv:1707.05031 DSOD - "DSOD: Learning Deeply Supervised Object Detectors from Scratch" (2017)arXiv:1708...
Joint Object Detection and Multi-Object Tracking with Graph Neural Networks [ax2006/ icra21] [pytorch] Microscopy / cell tracking Baxter Algorithms / Viterbi Tracking [tmi14] [matlab] Deepcell: Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning [bio...
PaddleDetection implements varied mainstream object detection algorithms in modular design, and provides wealthy data augmentation methods, network components(such as backbones), loss functions, etc., and integrates abilities of model compression and cross-platform high-performance deployment. After a long...