https://github.com/facebookresearch/imvotenet
공식 코드ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
Papers with Code 아카이브
3D geometry
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/nerf-det
공식 코드NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection
https://github.com/franco-solis/graphvf-code
공식 코드GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow
https://github.com/google-research/slot-attention-video
공식 코드https://github.com/graphpku/disgnn
공식 코드https://github.com/guangmingw/DOPlearning
공식 코드Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry
https://github.com/haksorus/gsplatloc
공식 코드https://github.com/hancyran/lidar-diffusion
공식 코드Towards Realistic Scene Generation with LiDAR Diffusion Models
https://github.com/harlanhong/cvpr2022-dagan
공식 코드Depth-Aware Generative Adversarial Network for Talking Head Video Generation
https://github.com/hcp16/active_nerf
공식 코드ActiveNeRF: Learning Accurate 3D Geometry by Active Pattern Projection
https://github.com/hirotong/reneus
공식 코드Seeing Through the Glass: Neural 3D Reconstruction of Object Inside a Transparent Container
https://github.com/hongbin98/drivegen
공식 코드https://github.com/hongfz16/avatarclip
공식 코드AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
https://github.com/intelligentgeometry/nelo
공식 코드https://github.com/ivan-tang-3d/any2point
공식 코드Any2Point: Empowering Any-modality Large Models for Efficient 3D Understanding
https://github.com/javrtg/c2p
공식 코드From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
https://github.com/jiangzhongshi/SurfaceNetworks
공식 코드https://github.com/jiaor17/3D-MGP
공식 코드Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
https://github.com/jiaor17/3d-emgp
공식 코드Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
https://github.com/jkulhanek/tetra-nerf
공식 코드Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra
https://github.com/junshutang/Make-It-3D
공식 코드Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
https://github.com/keeganhk/neurogf
공식 코드NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries
https://github.com/lawrence-cj/ARKitTrack
공식 코드ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data
https://github.com/layumi/person-reid-3d
공식 코드Parameter-Efficient Person Re-identification in the 3D Space
https://github.com/leonidk/direct_gmm
공식 코드https://github.com/leoqli/neuralgf
공식 코드NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function
https://github.com/linusnie/diffcd
공식 코드DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting
https://github.com/liren2515/dmap
공식 코드Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates
https://github.com/liz66666/gpa3d
공식 코드https://github.com/llrtt/G-NeRF
공식 코드G-NeRF: Geometry-enhanced Novel View Synthesis from Single-View Images
https://github.com/lppllppl920/sage-slam
공식 코드https://github.com/lsx0101/Interactive-NeRF-Editing
공식 코드https://github.com/lucmos/spectral-unions
공식 코드https://github.com/lukashoel/text2room
공식 코드Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models
https://github.com/lyp-deeplearning/liftfeat
공식 코드https://github.com/lzqsd/TransparentShapeReconstruction
공식 코드Through the Looking Glass: Neural 3D Reconstruction of Transparent Shapes
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.