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Mixed Reality

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코드

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

https://github.com/tsattler/understanding_apr

공식 코드

Understanding the Limitations of CNN-based Absolute Camera Pose Regression

https://github.com/xiexh20/behave-dataset

공식 코드

BEHAVE: Dataset and Method for Tracking Human Object Interactions

https://github.com/Aizierjiang/mr

Context-Aware Mixed Reality: A Framework for Ubiquitous Interaction

https://github.com/DragonLiu1995/xRIR_code

Hearing Anywhere in Any Environment

https://github.com/HengyiWang/neural-rgbd-torch

Neural RGB-D Surface Reconstruction

https://github.com/MIT-Reality-Hack-2020/DamageCheckAR

Artificial Intelligence Assisted Infrastructure Assessment Using Mixed Reality Systems

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/FastNeRF_High_Fidelity_Neural_Rendering_at_200FPS

FastNeRF: High-Fidelity Neural Rendering at 200FPS

https://github.com/VCL3D/DeepPanoramaLighting

Deep Lighting Environment Map Estimation from Spherical Panoramas

https://github.com/YuhangMing/Object-Guided-Relocalisation

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/ais-lab/d2s

Fast and Lightweight Scene Regressor for Camera Relocalization

https://github.com/apicis/aff-seg

Affordance segmentation of hand-occluded containers from exocentric images

https://github.com/apple/ml-live-pose

BundleFusion: Real-time Globally Consistent 3D Reconstruction using On-the-fly Surface Re-integration

https://github.com/bcv-uniandes/bodiffusion

BoDiffusion: Diffusing Sparse Observations for Full-Body Human Motion Synthesis

https://github.com/cln515/HoloLensRobotNav

Offline and Online calibration of Mobile Robot and SLAM Device for Navigation

https://github.com/edavalosanaya/FastPoseCNN

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/facebookresearch/vkraygs

Hardware-Rasterized Ray-Based Gaussian Splatting

https://github.com/interactivegl/vision6d

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/it3dego/it3dego

HoloLens 2 Research Mode as a Tool for Computer Vision Research

https://github.com/lh641446825/NOCS_2019CVPR

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/mauriceqch/pcc_geo_cnn_samples

Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression

https://github.com/maxpascher/survey-visualizer

Virtual, Augmented, and Mixed Reality for Human-Robot Interaction: A Survey and Virtual Design Element Taxonomy

https://github.com/mli0603/tatoo

Twin-S: A Digital Twin for Skull-base Surgery

https://github.com/pairlab/6pack

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/pedrocruzio/DamageCheckAR

Artificial Intelligence Assisted Infrastructure Assessment Using Mixed Reality Systems

https://github.com/sahithchada/NOCS_PyTorch

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/taeinkwon/CASA

Context-Aware Sequence Alignment using 4D Skeletal Augmentation

https://github.com/wenbowen123/BundleTrack

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/ykzzyk/vision6d

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/zubair-irshad/CenterSnap

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

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