Papers with Code 아카이브
3D Shape Modeling
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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Image: Gkioxari et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BoyanJIANG/LoRD
공식 코드LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling
https://github.com/QianliM/CAPE
공식 코드https://github.com/Seed3D/Dora
공식 코드Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
https://github.com/amirhertz/spaghetti
공식 코드SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation
https://github.com/lkeab/gsnet
공식 코드GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision
https://github.com/rowl1ng/3dsketch2shape
공식 코드https://github.com/DreamTechAI/Direct3D-S2
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
https://github.com/IMAC-projects/mesh-deformation
https://github.com/Penguinazor/mse.wem.project
https://github.com/facebookresearch/meshrcnn
https://github.com/facebookresearch/pytorch3d
https://github.com/huang229/auto_tooth_arrangement
https://github.com/koryako/selfcarRaspberryPi
Learning 6-DOF Grasping Interaction via Deep Geometry-aware 3D Representations
https://github.com/theycallmepeter/pytorch3d_PBR
https://github.com/xhxuciedu/3DHand
https://github.com/xingyuansun/pix3d
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.