Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

Last update: Nov 23, 2022

Overview

Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

This is the mmdetection implementation of our CVPR2021 paper:

Zhenyu Wang, Yali Li, Ye Guo, Lu Fang, Shengjin Wang. Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection. ArXiv.

This code is based on mmdetection v2.18. Please install the code according to the mmdetection step first.

Owner

GitHub Repository

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Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

Related tags

Overview

Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

Owner

Ladder Variational Autoencoders (LVAE) in PyTorch

🧠 A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation.', ECCV 2016

Neural Network to colorize grayscale images

Source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network

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Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

🕺Full body detection and tracking