There are 2 repositories under pascal-voc topic.
Most popular metrics used to evaluate object detection algorithms.
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
Free to use online tool for labelling photos. https://makesense.ai
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
DeepLab-ResNet rebuilt in TensorFlow
To speedup and simplify image labeling/ annotation process with multiple supported formats.
DeepLabv3+ built in TensorFlow
Label images and video for Computer Vision applications
DeepLabv3 and DeepLabv3+ with pretrained weights for Pascal VOC & Cityscapes
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆20 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
Real-time object detection on Android using the YOLO network with TensorFlow
DeepLab resnet v2 model in pytorch
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
This repository contains the source code of our work on designing efficient CNNs for computer vision
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, PRNet, RESA, LSTR, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help
Convert between visual object detection datasets
DeepLabv3 built in TensorFlow
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
DeepLab-ResNet rebuilt in Pytorch
Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).
How to create custom COCO data set for object detection
DeepLab-LargeFOV implemented in tensorflow
An (re-)implementation of DeepLab v2 (ResNet-101) in TensorFlow for semantic image segmentation on the PASCAL VOC 2012 dataset.
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)
PyTorch Implementation of Stacked U-Nets (SUNets)
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.
Implementation of our Pattern Recognition paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"
The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast" [ICLR 2022].
Tools for converting Label Studio annotations into common dataset formats
Convert VOC format XMLs to COCO format json
PSPNet in Chainer
WIDER FACE annotations converted to the Pascal VOC XML format