Pinned Repositories
AdaIN-style
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
AdaptSegNet
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Algorithm-DIY
整理一下各种算法
AnyNet
Anytime Stereo Image Depth Estimation on Mobile Devices (ICRA 2019)
automl
Google Brain AutoML
awesome-depth
A curated list of publication for depth estimation
BridgeDepthFlow
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
BRNet
(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
bts
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
caffe
Caffe: a fast open framework for deep learning.
MinZhangm's Repositories
MinZhangm/Algorithm-DIY
整理一下各种算法
MinZhangm/automl
Google Brain AutoML
MinZhangm/awesome-depth
A curated list of publication for depth estimation
MinZhangm/BridgeDepthFlow
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
MinZhangm/BRNet
(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
MinZhangm/bts
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
MinZhangm/caffe
Caffe: a fast open framework for deep learning.
MinZhangm/Revisiting_Single_Depth_Estimation
official implementation of "Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries"
MinZhangm/connecting_the_dots
This repository contains the code for the paper "Connecting the Dots: Learning Representations for Active Monocular Depth Estimation" https://avg.is.tuebingen.mpg.de/publications/riegler2019cvpr
MinZhangm/cvpr2019
cvpr2019 papers，极市团队整理
MinZhangm/DAIN
Depth-Aware Video Frame Interpolation (CVPR 2019)
MinZhangm/DANet
Dual Attention Network for Scene Segmentation (CVPR2019)
MinZhangm/DCL
Destruction and Construction Learning for Fine-grained Image Recognition
MinZhangm/DeepLiDAR
Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image
MinZhangm/DenseTorch
An easy-to-use wrapper for work with dense per-pixel tasks in PyTorch (including multi-task learning)
MinZhangm/Depth-Estimation
paper list
MinZhangm/DiverseDepth
The code and data of DiverseDepth
MinZhangm/DMRA
Code and Dataset for ICCV 2019 paper. "Depth-induced Multi-scale Recurrent Attention Network for Saliency Detection".
MinZhangm/Git-learning-demo
MinZhangm/IIC
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
MinZhangm/mannequinchallenge
Inference code and trained models for "Learning the Depths of Moving People by Watching Frozen People."
MinZhangm/mmdetection
Open MMLab Detection Toolbox and Benchmark
MinZhangm/models
Models and examples built with TensorFlow
MinZhangm/RNN_depth_pose
Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth
MinZhangm/rvos
RVOS: End-to-End Recurrent Network for Video Object Segmentation
MinZhangm/SARPN
Structure-Aware Residual Pyramid Network for Monocular Depth Estimation IJCAI 2019
MinZhangm/SharpNet
Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation
MinZhangm/Sparse-Depth-Completion
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. 1st place on KITTI. (MVA 2019 Conference)
MinZhangm/VMZ
VMZ: Model Zoo for Video Modeling
MinZhangm/VNL_Monocular_Depth_Prediction
Monocular Depth Prediction