https://github.com/hlinchen/gnesf
NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video
Papers with Code 아카이브
3D Scene Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Creating 3D scene either using conventional SFM pipelines or latest deep learning approaches.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/linketic/citygaussian
CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
https://github.com/magicleap/Atlas
https://github.com/rzhevcherkasy/bmvc24-gsim
Mirror-3DGS: Incorporating Mirror Reflections into 3D Gaussian Splatting
https://github.com/stefan-ainetter/HOC-Search
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans
https://github.com/stefan-ainetter/SCANnotateDataset
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans
https://github.com/stefan-ainetter/SCANnotatepp
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans
https://github.com/suryanshkumar/online-joint-depthfusion-and-semantic
https://github.com/wMito/HuSc3D
HuSc3D: Human Sculpture dataset for 3D object reconstruction
https://github.com/yangyucheng000/NeuralRecon
NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video
https://github.com/yijiaguo02/spikegs
SpikeGS: Reconstruct 3D scene via fast-moving bio-inspired sensors
https://github.com/zhipeixu/fakeshield
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.