https://github.com/yhw-yhw/PVAMVSNet
공식 코드Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
Papers with Code 아카이브
3D Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 7
- 평가표
- 10
- 보존된 평가 기록
- 44
3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.
Image: Gwak et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yhw-yhw/mover
공식 코드Human-Aware Object Placement for Visual Environment Reconstruction
https://github.com/yinboc/liif
공식 코드Learning Continuous Image Representation with Local Implicit Image Function
https://github.com/yixin26/SVR-SP
공식 코드Neural Implicit 3D Shapes from Single Images with Spatial Patterns
https://github.com/yjcaimeow/SISNet
공식 코드Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
https://github.com/yjjfish/multi-cali-anything
공식 코드https://github.com/yoctta/multiple-attention
공식 코드https://github.com/yongyizang/SingFake
공식 코드https://github.com/youmi-zym/go-slam
공식 코드GO-SLAM: Global Optimization for Consistent 3D Instant Reconstruction
https://github.com/ysus33/rgb-d_plenoxel_mapping_tracking
공식 코드https://github.com/yu-frank/PerspectiveCropLayers
공식 코드PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers
https://github.com/yuanhaoguo/circular-camera-calibration
공식 코드Probabilistic Inference for Camera Calibration in Light Microscopy under Circular Motion
https://github.com/yueyin27/refref
공식 코드RefRef: A Synthetic Dataset and Benchmark for Reconstructing Refractive and Reflective Objects
https://github.com/yunjinli/SADG-SegmentAnyDynamicGaussian
공식 코드https://github.com/yunyikristy/global_local
공식 코드https://github.com/yuruntian/HyNet
공식 코드HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss
https://github.com/yym-sia/lingmi-mr
공식 코드A geometry-aware deep network for depth estimation in monocular endoscopy
https://github.com/yzyouzhang/asvspoof2021_air
공식 코드UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
https://github.com/za-cheng/PM-PMVS
공식 코드Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance
https://github.com/za-cheng/wildlight
공식 코드https://github.com/zc-alexfan/arctic
공식 코드ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation
https://github.com/zc-alexfan/hold
공식 코드HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video
https://github.com/zcq15/acdnet
공식 코드ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth Estimation
https://github.com/zerchen/gSDF
공식 코드gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction
https://github.com/zhangyp15/occformer
공식 코드OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
https://github.com/zhaofang0627/anchorudf
공식 코드https://github.com/zhen6618/eprecon
공식 코드EPRecon: An Efficient Framework for Real-Time Panoptic 3D Reconstruction from Monocular Video
https://github.com/zhengdiyu/arbitrary-hands-3d-reconstruction
공식 코드ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction
https://github.com/zhenglab/ffdbackbone
공식 코드https://github.com/zhengxi-git/phase-slam
공식 코드https://github.com/zhenpeiyang/hm3d-abo
공식 코드HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D Reconstruction
https://github.com/zhihaohaoran/GPGS
공식 코드https://github.com/zhirui-gao/PartGS
공식 코드PartGS:Learning Part-aware 3D Representations by Fusing 2D Gaussians and Superquadrics
https://github.com/zhirui-gao/curve-gaussian
공식 코드Curve-Aware Gaussian Splatting for 3D Parametric Curve Reconstruction
https://github.com/zhou13/symmetrynet
공식 코드Learning to Detect 3D Reflection Symmetry for Single-View Reconstruction
https://github.com/zhu00121/universal-representation-dynamics-of-deepfake-speech
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.