Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
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Updated
Jul 5, 2023 - Python
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…
This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.
Experiments on unsupervised point cloud reconstruction.
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
Implementation of a 3D Face Generative Model
Tensorflow implementation of Semi-supervised Sequence Learning (https://arxiv.org/abs/1511.01432)
由时间空间成对组成的轨迹序列,通过循环神经网络lstm,自编码器auto-encode,时空密度聚类st-dbscan做异常检测
Custom PyTorch model (VGG-16 Auto-Encoder) and custom criterion (Local Aggregation) for image clustering. The repo contains elaborated creation of fungi image data using factory method.
Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)
Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'
Learning Embedding of 3D models with Quadric Loss
2020 Spring Fudan University Machine Learning Course HW by prof. Chen Qin. 复旦大学大数据学院2020年春季课程-人工智能与机器学习(DATA620006)
Modern Deep Network Toolkits for Tensorflow-Keras. This is a extension for newest tensorflow 1.x.
A simple document and image search engine implemented in keras
Implementation of Consistency-based anomaly detection (ConAD)
A simple, easy-to-use and flexible auto-encoder neural network implementation for Keras
Evaluation of the Single-Image Camera-to-Robot Pose Estimation deep learning research by NVIDIA on the Jaco Gen 2 6DoF KG-3 Robot Arm from Kinova Robotics.
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