https://github.com/Gaozhongpai/PaiConvMesh
공식 코드Learning Local Neighboring Structure for Robust 3D Shape Representation
Papers with Code 아카이브
3D Shape Representation
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Image: MeshNet
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/LMescheder/Occupancy-Networks
공식 코드Occupancy Networks: Learning 3D Reconstruction in Function Space
https://github.com/Regenerator/dpf-nets
공식 코드Discrete Point Flow Networks for Efficient Point Cloud Generation
https://github.com/TheoDEPRELLE/AtlasNetV2
공식 코드Learning elementary structures for 3D shape generation and matching
https://github.com/TrepangCat/3D_Semantic_Subspace_Traverser
공식 코드3D Semantic Subspace Traverser: Empowering 3D Generative Model with Shape Editing Capability
https://github.com/ZENGYIMING-EAMON/CorrNet3D
공식 코드CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
https://github.com/ZhengZerong/DeepImplicitTemplates
공식 코드https://github.com/cangumeli/ROCA
공식 코드ROCA: Robust CAD Model Retrieval and Alignment from a Single Image
https://github.com/computational-imaging/ACORN
공식 코드ACORN: Adaptive Coordinate Networks for Neural Scene Representation
https://github.com/cvlab-epfl/partsdf
공식 코드https://github.com/czq142857/BSP-NET-original
공식 코드BSP-Net: Generating Compact Meshes via Binary Space Partitioning
https://github.com/czq142857/implicit-decoder
공식 코드https://github.com/dvirginz/dpc
공식 코드DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction
https://github.com/gbouritsas/Neural3DMM
공식 코드https://github.com/google-research-datasets/Objectron
공식 코드Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations
https://github.com/haidongz-usc/Curriculum-DeepSDF
공식 코드https://github.com/lioryariv/idr
공식 코드Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
https://github.com/lity20/dccdif
공식 코드Learning Deep Implicit Functions for 3D Shapes with Dynamic Code Clouds
https://github.com/liuzhengzhe/exim
공식 코드EXIM: A Hybrid Explicit-Implicit Representation for Text-Guided 3D Shape Generation
https://github.com/lkeab/gsnet
공식 코드GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision
https://github.com/myavartanoo/3DIAS_PyTorch
공식 코드3DIAS: 3D Shape Reconstruction with Implicit Algebraic Surfaces
https://github.com/myavartanoo/PolyNet_PyTorch
공식 코드PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation
https://github.com/naughtyzz/3d_facial_shape_attribute_translation_ssgmap
공식 코드https://github.com/niladridutt/Diffusion-3D-Features
공식 코드Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features
https://github.com/nitinagarwal/QuadricLoss
공식 코드https://github.com/openspaceai/se-ornet
공식 코드https://github.com/riccardomarin/Diff-FMaps
공식 코드https://github.com/rowl1ng/3dsketch2shape
공식 코드https://github.com/tensorflow/graphics/tree/master/tensorflow_graphics/projects/local_implicit_grid
공식 코드https://github.com/u2ni/ICLR2021
공식 코드On the Effectiveness of Weight-Encoded Neural Implicit 3D Shapes
https://github.com/vlar-group/raydf
공식 코드RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency
https://github.com/vuenc/slice-to-shape
공식 코드On the Localization of Ultrasound Image Slices within Point Distribution Models
https://github.com/weixmath/cvr
공식 코드Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views
https://github.com/zhengxinyang/sdf-stylegan
공식 코드SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation
https://github.com/1zb/3dshape2vecset
3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models
https://github.com/AliBahri94/SVWA_TTA
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.