Papers with Code 아카이브

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/una-dinosauria/human-motion-prediction

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On human motion prediction using recurrent neural networks

https://github.com/uzh-rpg/event-based_vision_resources

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Event-based Star Tracking via Multiresolution Progressive Hough Transforms

https://github.com/uzh-rpg/rpg_davis_simulator

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The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM

https://github.com/viorik/ConvLSTM

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Spatio-temporal video autoencoder with differentiable memory

https://github.com/visinf/fldr-vfi

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Efficient Feature Extraction for High-resolution Video Frame Interpolation

https://github.com/wangkaihong/unsup_recycle_gan

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Learning Temporally and Semantically Consistent Unpaired Video-to-video Translation Through Pseudo-Supervision From Synthetic Optical Flow

https://github.com/wenbin-lin/OcclusionFusion

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OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D Reconstruction

https://github.com/wish44165/ReynoldsFlow

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ReynoldsFlow: Exquisite Flow Estimation via Reynolds Transport Theorem

https://github.com/wu-cvgl/inceventgs

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IncEventGS: Pose-Free Gaussian Splatting from a Single Event Camera

https://github.com/xfsun99/ccyclegan-tf2

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Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial Resolution

https://github.com/xiaohao-xu/mac-ego3d

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MAC-Ego3D: Multi-Agent Gaussian Consensus for Real-Time Collaborative Ego-Motion and Photorealistic 3D Reconstruction

https://github.com/xiaohao-xu/slam-under-perturbation

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Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video

https://github.com/xinjie-q/distributed-dvc

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Low-complexity Deep Video Compression with A Distributed Coding Architecture

https://github.com/yan99033/CNN-SVO

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

https://github.com/yanglier/ego-motion-estimation

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Ego-motion Estimation Based on Fusion of Images and Events

https://github.com/yaozhuwa/eva-flow

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Towards Anytime Optical Flow Estimation with Event Cameras

https://github.com/yjzhang96/motion-etr

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Exposure Trajectory Recovery from Motion Blur

https://github.com/yjzhang96/neurmap-deblur

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Neural Maximum A Posteriori Estimation on Unpaired Data for Motion Deblurring

https://github.com/yoyo-nb/thin-plate-spline-motion-model

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Thin-Plate Spline Motion Model for Image Animation

https://github.com/yuan-xiaohan/4d-myocardium-reconstruction-with-decoupled-motion-and-shape-model

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4D Myocardium Reconstruction with Decoupled Motion and Shape Model

https://github.com/yyguo-sjtu/dsd-3d-unsupervised-landmark-detection-based-motion-estimation

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Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images

https://github.com/yzcjtr/GeoNet

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

https://github.com/zhihaohu/pytorchvideocompression

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FVC: A New Framework towards Deep Video Compression in Feature Space

https://gitlab.com/baioc/vtm

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Relying on a rate constraint to reduce Motion Estimation complexity

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