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Object Reconstruction

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/kimren227/extrudenet

공식 코드

ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing

https://github.com/korrawe/grasping_field

공식 코드

Grasping Field: Learning Implicit Representations for Human Grasps

https://github.com/korrawe/grasping_field_demo

공식 코드

Grasping Field: Learning Implicit Representations for Human Grasps

https://github.com/kyleleey/rico

공식 코드

RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction

https://github.com/leilimaster/DmifNet

공식 코드

DmifNet:3D Shape Reconstruction Based on Dynamic Multi-Branch Information Fusion

https://github.com/lihaoy-ux/dqo-map

공식 코드

DQO-MAP: Dual Quadrics Multi-Object mapping with Gaussian Splatting

https://github.com/liyingcv/long-range-grouping-transformer

공식 코드

Long-Range Grouping Transformer for Multi-View 3D Reconstruction

https://github.com/llukmancerkezi/roster

공식 코드

Sparse 3D Reconstruction via Object-Centric Ray Sampling

https://github.com/manycore-research/faceformer

공식 코드

Neural Face Identification in a 2D Wireframe Projection of a Manifold Object

https://github.com/maureenzou/m3-spatial

공식 코드

M3: 3D-Spatial MultiModal Memory

https://github.com/mlzxy/motion-blender-gs

공식 코드

Motion Blender Gaussian Splatting for Dynamic Scene Reconstruction

https://github.com/monniert/unicorn

공식 코드

Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency

https://github.com/mrsecant/gaussiangrasper

공식 코드

GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping

https://github.com/oppo-us-research/spacetimegaussians

공식 코드

Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis

https://github.com/psc0628/dm-osvp

공식 코드

Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning

https://github.com/qianyiwu/objectsdf_plus

공식 코드

ObjectSDF++: Improved Object-Compositional Neural Implicit Surfaces

https://github.com/renato145/3D-ORGAN

공식 코드

3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network

https://github.com/renezurbruegg/icg_benchmark

공식 코드

ICGNet: A Unified Approach for Instance-Centric Grasping

https://github.com/ruili3/Know-Your-Neighbors

공식 코드

Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning

https://github.com/safouaneelg/FusionVision

공식 코드

FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything

https://github.com/saifkhichi96/shape25d

공식 코드

Shape2.5D: A Dataset of Texture-less Surfaces for Depth and Normals Estimation

https://github.com/sail-sg/numcc

공식 코드

NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF

https://github.com/samxuxiang/hnc-cad

공식 코드

Hierarchical Neural Coding for Controllable CAD Model Generation

https://github.com/singhay/DeepPredictiveMotionTracking

공식 코드

Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging

https://github.com/stusynakowski/Unsup_Recognition_of_Intent

공식 코드

Adding Knowledge to Unsupervised Algorithms for the Recognition of Intent

https://github.com/szymanowiczs/splatter-image

공식 코드

Splatter Image: Ultra-Fast Single-View 3D Reconstruction

https://github.com/tberriel/featsplat

공식 코드

Feature Splatting for Better Novel View Synthesis with Low Overlap

https://github.com/tiev-tongji/convexhull-based-algebraic-constraint

공식 코드

Convex Hull-based Algebraic Constraint for Visual Quadric SLAM

https://github.com/tumftm/caliv

공식 코드

CaLiV: LiDAR-to-Vehicle Calibration of Arbitrary Sensor Setups via Object Reconstruction

https://github.com/ucwxb/nto3d

공식 코드

NTO3D: Neural Target Object 3D Reconstruction with Segment Anything

https://github.com/unclemedm/instpifu

공식 코드

Towards High-Fidelity Single-view Holistic Reconstruction of Indoor Scenes

https://github.com/val-iisc/ssl_3d_recon

공식 코드

From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks

https://github.com/varunburde/reconstruction_pose_benchmark

공식 코드

Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimation

https://github.com/vast-ai-research/triposr

공식 코드

TripoSR: Fast 3D Object Reconstruction from a Single Image

https://github.com/vganapati/led_pvae

공식 코드

Data-Driven Computational Imaging for Scientific Discovery

https://github.com/vinairesearch/lemul

공식 코드

Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.