Papers with Code 아카이브

3D Scene Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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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.

기법

관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.

NeuralRecon

NeuralRecon is a framework for real-time 3D scene reconstruction from a monocular video. Unlike previous methods that estimate single-view depth maps separately on each key-frame and fuse them later, NeuralRecon proposes to directly reconstruct local surfaces represented as sparse TSDF volumes for each video fragment sequentially by a neural network. A learning-based TSDF fusion module based on gated recurrent units is used to guide the network to fuse features from previous fragments. This design allows the network to capture local smoothness prior and global shape prior of 3D surfaces.

NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video

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