Polarization parameters and polarizing filters in real-time ray tracing with DXR and the Stokes-Mueller calculus

Models and examples built with TensorFlow

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

Infrared and visible image fusion via gradient transfer and total variation minimization

NestFuse (IEEE TIM 2020, Highly Cited Paper)- Pytorch >= 0.4.1

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

基于Pytorch的DDCGAN非官方复现。

Recursive-Cascaded-Networks TF2.0 migration version

Implementation of the FIRe-GAN model, a GAN-based method for the fusion of visible-infrared images.

[CVPR 2022 Oral] Official implementation for "Discrete Cosine Transform Network for Guided Depth Map Super-Resolution."

Source Code for paper "Infrared and Visible Image Fusion via Parallel Scene and Texture Learning".

Official Implementation of Fast End-to-End Trainable Guided Filter, CVPR 2018

Research on indoor localization

一个以传感器为基础，基于github上著名框架AChartEngine制作的一个实时获取、绘制传感器数据的应用

Code for the paper 'Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification'.

WiFi fingerprinting-based Indoor Localization, an android application.

Extended Kalman Filter and Deep Learning to detect vehicles from RGB and LiDAR data (Sensor Fusion and Tracking project of the Udacity Self-Driving Car Engineer Nanodegree Program)

用基于策略梯度得强化学习方法训练AI玩王者荣耀

Latex code for making neural networks diagrams

Python tools for working with KITTI data.

Convert KITTI dataset to ROS bag file the easy way!

Nerual Network of Stochastic Computing for MNIST Recognition

[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

Unsupervised Data Augmentation (UDA)

CVPR 2022 | Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection.

Learning a Deep Multi-scale Feature Ensemble and an Edge-attention Guidance for Image Fusion

《Pytorch模型训练实用教程》中配套代码