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Motion Estimation

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Motion Estimation is used to determine the block-wise or pixel-wise motion vectors between two frames.

Source: MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/mli-lab/mri_motionttt

MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI

https://github.com/mrchanwoo/DeepVO-Keras

DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks

https://github.com/muskie82/CNN-DSO

CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth Prediction

https://github.com/nageshpindi/human-motion-prediction-master

On human motion prediction using recurrent neural networks

https://github.com/ning22/Motion-Compensated-Dynamic-MRI-Reconstruction-with-Local-Affine-Optical-Flow-Estimation

Motion Compensated Dynamic MRI Reconstruction with Local Affine Optical Flow Estimation

https://github.com/ostadabbas/infant-respiration-estimation

DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks

https://github.com/prgumd/EVDodge

EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras

https://github.com/qrzyang/pseudo-stereo

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/raunaks13/GeoNet-PyTorch

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

https://github.com/renmengqisheng/stereo_multifisheye

ROVO: Robust Omnidirectional Visual Odometry for Wide-baseline Wide-FOV Camera Systems

https://github.com/rnlee1998/SRD

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/robot-love/depth_from_video_in_the_wild

Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

https://github.com/rvimlab/homography_imitation_learning

Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion Extraction

https://github.com/samyakjain0112/Video-denoising_tensorflow-core-api-2.0

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

https://github.com/swy666/rppg-doha

DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks

https://github.com/tensorflow/models/tree/master/research/struct2depth

Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

https://github.com/terbed/Deep-rPPG

DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks

https://github.com/tudelft-iv/voteflow

Scalable Scene Flow from Point Clouds in the Real World

https://github.com/tudelft/filled-disparity-monodepth

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/uditsharma29/flynet-cann

A Hybrid Compact Neural Architecture for Visual Place Recognition

https://github.com/wooramkang/FITVNet

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

https://github.com/wuchangsheng951/repaired_fastdvdnet

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

https://github.com/xueliancheng/slt-net

Implicit Motion Handling for Video Camouflaged Object Detection

https://github.com/yijie0710/GeoNet_pytorch

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

https://github.com/zad1206/simtrack-mindspore

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving

https://gitlab.com/VladyslavUsenko/basalt-headers

The Double Sphere Camera Model

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.