ShuweiShao's repositories
AF-SfMLearner
[MedIA2022 & ICRA2021] Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescue
URCDC-Depth
[TMM2023] URCDC-Depth: Uncertainty Rectified Cross-Distillation with CutFlip for Monocular Depth Estimation
MonoDiffusion
[Arxiv2023] MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model
AA-RMVSNet
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
CNMNet
ECCV 2020
Conformer
Official code for Conformer: Local Features Coupling Global Representations for Visual Recognition
DeepLiDAR
Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image
colmap
COLMAP - Structure-from-Motion and Multi-View Stereo
depth-refinement-and-normal-estimation
A graph-based framework to refine a noisy and possibly incomplete depth map and estimate the corresponding normal map.
GLPDepth
GLPDepth PyTorch Implementation: Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth
IMU-study
对常见IMU芯片的原理、驱动和数据融合算法整理,以区分某度、某坛上面碎片化严重到影响入坑的乱象
MaGNet
(CVPR 2022 - oral) Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
manydepth
[CVPR 2021] Self-supervised depth estimation from short sequences
Monocular-Depth-Estimation-Toolbox
Monocular Depth Estimation Toolbox based on MMSegmentation.
monodepth2
[ICCV 2019] Monocular depth estimation from a single image
nerf-pytorch
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
NerfingMVS
[ICCV2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
ObjCAViT
Official implementation of the paper "ObjCAViT: Improving Monocular Depth Estimation Using Natural Language Models And Image-Object Cross-Attention"
SceneRF
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
surface-normal
This is a tool.code for CVPR2019 paper 1899: Deep Surface Normal Guided Depth Prediction for Outdoor Secene from Sparce Lidar Data and Single Color Image.
Unsupervised-Segmentation
A high performance impermentation of Unsupervised Image Segmentation by Backpropagation - Asako Kanezaki