ling-zzZ

ling-zzZ

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AcfNet

This is an implementation for our paper "Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching"

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ActiveStereoNet

Customized Implementation of ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems

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AnyNet

Anytime Stereo Image Depth Estimation on Mobile Devices (ICRA 2019)

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apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

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CCNet

CCNet: Criss-Cross Attention for Semantic Segmentation (ICCV 2019).

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CMANet

A high-resolution and high-accuracy monocular network

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CSPN

Convolutional Spatial Propagation Network

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cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection

code and model of Pyramid Feature Selective Network for Saliency detection

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DAFStereoNets

Domain-invariant Matching Space Stereo Networks (MS-Nets)

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DeepPruner

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch (ICCV 2019)

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Dive-into-DL-PyTorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

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DPT-season-depth

DPT refined on season dataset

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EfficientDet.Pytorch

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

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fast-depth

ICRA 2019 "FastDepth: Fast Monocular Depth Estimation on Embedded Systems"

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hd3

Code for Hierarchical Discrete Distribution Decomposition for Match Density Estimation (CVPR 2019)

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high-res-stereo

Hierarchical Deep Stereo Matching on High Resolution Images, CVPR 2019.

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IRS

IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation

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layout-parser

A unified toolkit for Deep Learning Based Document Image Analysis

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Learning2AdaptForStereo

Code for: "Learning To Adapt For Stereo" accepted at CVPR2019

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libSGM

Stereo Semi Global Matching by cuda

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PyTorch-Pyramid-Feature-Attention-Network-for-Saliency-Detection

PyTorch implementation of the CVPR 2019 paper “Pyramid Feature Attention Network for Saliency Detection”

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Real-time-self-adaptive-deep-stereo

Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)

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stereo-from-mono

[ECCV 2020] Learning stereo from single images using monocular depth estimation networks

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StereoDataset

An indoor real scene stereo dataset. It contains 2000 pairs of images with high accuracy disparity maps. We hope it can improve the the generalization performance of deep stereo matching networks.

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vid2vid

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

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