Papers with Code 아카이브
Object Reconstruction
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dqj5182/contho_release
공식 코드Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer
https://github.com/fabiopoiesi/4dm
공식 코드Multi-view data capture for dynamic object reconstruction using handheld augmented reality mobiles
https://github.com/facebookresearch/assemblyhands-toolkit
공식 코드Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
https://github.com/facebookresearch/phosa
공식 코드Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
https://github.com/facebookresearch/pifuhd
공식 코드PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
https://github.com/fanhqme/PointSetGeneration
공식 코드A Point Set Generation Network for 3D Object Reconstruction from a Single Image
https://github.com/faridyagubbayli/LegoFormer
공식 코드LegoFormer: Transformers for Block-by-Block Multi-view 3D Reconstruction
https://github.com/filaPro/cad-recode
공식 코드https://github.com/ganlab/ostra
공식 코드A One Stop 3D Target Reconstruction and multilevel Segmentation Method
https://github.com/garyzhu1996/umiformer
공식 코드UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction
https://github.com/gmum/LoCondA
공식 코드Modeling 3D Surface Manifolds with a Locally Conditioned Atlas
https://github.com/google-research/cad-estate
공식 코드https://github.com/google-research/corenet
공식 코드CoReNet: Coherent 3D scene reconstruction from a single RGB image
https://github.com/guohaoxiang/complexgen
공식 코드ComplexGen: CAD Reconstruction by B-Rep Chain Complex Generation
https://github.com/haimsaw/OReX
공식 코드OReX: Object Reconstruction from Planar Cross-sections Using Neural Fields
https://github.com/haoz19/limr
공식 코드https://github.com/hassony2/homan
공식 코드Towards unconstrained joint hand-object reconstruction from RGB videos
https://github.com/hitsz-nrsl/activeimplicitrecon
공식 코드Active Implicit Object Reconstruction using Uncertainty-guided Next-Best-View Optimization
https://github.com/hkust-vgd/rfnet-4d
공식 코드https://github.com/hongsukchoi/handnerf_release
공식 코드HandNeRF: Learning to Reconstruct Hand-Object Interaction Scene from a Single RGB Image
https://github.com/hq0709/Depth-NeuS
공식 코드https://github.com/huntorochi/HoGS
공식 코드HoGS: Unified Near and Far Object Reconstruction via Homogeneous Gaussian Splatting
https://github.com/huochf/StackFLOW
공식 코드StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset
https://github.com/huochf/WildHOI
공식 코드https://github.com/hzxie/Pix2Vox
공식 코드Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images
https://github.com/hzxie/Stereo-3D-Reconstruction
공식 코드https://github.com/irvingvasquez/nbv-regression-dataset
공식 코드Next-best-view Regression using a 3D Convolutional Neural Network
https://github.com/jackd/template_ffd
공식 코드Learning Free-Form Deformations for 3D Object Reconstruction
https://github.com/jarrome/imt_mapping
공식 코드An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions
https://github.com/jchibane/if-net
공식 코드Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
https://github.com/jiajunzhang16/ins-hoi
공식 코드https://github.com/junxuan-li/scps-nir
공식 코드Self-calibrating Photometric Stereo by Neural Inverse Rendering
https://github.com/junzhezhang/mesh-inversion
공식 코드https://github.com/jwubz123/DIG3D
공식 코드LeanGaussian: Breaking Pixel or Point Cloud Correspondence in Modeling 3D Gaussians
https://github.com/kerrj/rsrd
공식 코드Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.