https://github.com/ganlab/ostra
공식 코드A One Stop 3D Target Reconstruction and multilevel Segmentation Method
Papers with Code 아카이브
3D Object Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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Image: Choy et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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/guohaoxiang/complexgen
공식 코드ComplexGen: CAD Reconstruction by B-Rep Chain Complex Generation
https://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/jchibane/if-net
공식 코드Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
https://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
https://github.com/kimren227/extrudenet
공식 코드ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing
https://github.com/korrawe/grasping_field
공식 코드Grasping Field: Learning Implicit Representations for Human Grasps
https://github.com/korrawe/grasping_field_demo
공식 코드Grasping Field: Learning Implicit Representations for Human Grasps
https://github.com/leilimaster/DmifNet
공식 코드DmifNet:3D Shape Reconstruction Based on Dynamic Multi-Branch Information Fusion
https://github.com/liyingcv/long-range-grouping-transformer
공식 코드Long-Range Grouping Transformer for Multi-View 3D Reconstruction
https://github.com/llukmancerkezi/roster
공식 코드https://github.com/manycore-research/faceformer
공식 코드Neural Face Identification in a 2D Wireframe Projection of a Manifold Object
https://github.com/maureenzou/m3-spatial
공식 코드https://github.com/mlzxy/motion-blender-gs
공식 코드Motion Blender Gaussian Splatting for Dynamic Scene Reconstruction
https://github.com/monniert/unicorn
공식 코드Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency
https://github.com/mrsecant/gaussiangrasper
공식 코드GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping
https://github.com/oppo-us-research/spacetimegaussians
공식 코드Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis
https://github.com/safouaneelg/FusionVision
공식 코드https://github.com/sail-sg/numcc
공식 코드NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
https://github.com/samxuxiang/hnc-cad
공식 코드Hierarchical Neural Coding for Controllable CAD Model Generation
https://github.com/singhay/DeepPredictiveMotionTracking
공식 코드Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
https://github.com/stusynakowski/Unsup_Recognition_of_Intent
공식 코드Adding Knowledge to Unsupervised Algorithms for the Recognition of Intent
https://github.com/szymanowiczs/splatter-image
공식 코드https://github.com/tberriel/featsplat
공식 코드Feature Splatting for Better Novel View Synthesis with Low Overlap
https://github.com/ucwxb/nto3d
공식 코드NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
https://github.com/val-iisc/ssl_3d_recon
공식 코드From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks
https://github.com/vast-ai-research/triposr
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.