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ucas-lucky's Projects

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

dvc icon dvc

DVC: An End-to-end Deep Video Compression Framework, CVPR 2019 (Oral)

generative-compression icon generative-compression

TensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression

gnnpapers icon gnnpapers

Must-read papers on graph neural networks (GNN)

gspbox icon gspbox

Graph Signal Processing in Matlab

guidenet icon guidenet

Implementation for our paper 'Learning Guided Convolutional Network for Depth Completion'

models icon models

Models and examples built with TensorFlow

prednet icon prednet

Code and models accompanying "Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning"

pytorch-sepconv icon pytorch-sepconv

an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

sfmlearner icon sfmlearner

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

slam icon slam

learning SLAM,curse,paper and others

tensorflow-2.x-tutorials icon tensorflow-2.x-tutorials

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码,实战教程。

vid2vid icon vid2vid

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

video-compression-motion-estimation-block-video-encoder icon video-compression-motion-estimation-block-video-encoder

This repository is about video compression, and more specifically about the motion estimation block (ME block) of a video encoder. It is a research project for developing an efficient motion estimation algorithm, so that the video compression technology can keep pace with the high frame rate videos and high resolution videos.

videocoseg_msg icon videocoseg_msg

The Matlab code for Video Co-saliency via Multi-state Selection Graph

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