https://github.com/BIT-DYN/OpenObj
공식 코드OpenObj: Open-Vocabulary Object-Level Neural Radiance Fields with Fine-Grained Understanding
Papers with Code 아카이브
3D Scene Reconstruction
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Creating 3D scene either using conventional SFM pipelines or latest deep learning approaches.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DekuLiuTesla/CityGaussian
공식 코드CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
https://github.com/IntelLabs/baa-ngp
공식 코드BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives
https://github.com/JOP-Lee/READ-Large-Scale-Neural-Scene-Rendering-for-Autonomous-Driving
공식 코드READ: Large-Scale Neural Scene Rendering for Autonomous Driving
https://github.com/Jixuan-Fan/Momentum-GS
공식 코드Momentum-GS: Momentum Gaussian Self-Distillation for High-Quality Large Scene Reconstruction
https://github.com/Jumponthemoon/WeatherEdit
공식 코드WeatherEdit: Controllable Weather Editing with 4D Gaussian Field
https://github.com/Jumponthemoon/WeatherGS
공식 코드WeatherGS: 3D Scene Reconstruction in Adverse Weather Conditions via Gaussian Splatting
https://github.com/Semanticity-Research/ARCH2S
공식 코드https://github.com/UARK-AICV/OpenFusion
공식 코드Open-Fusion: Real-time Open-Vocabulary 3D Mapping and Queryable Scene Representation
https://github.com/USTC3DV/MERFStudio
공식 코드City-on-Web: Real-time Neural Rendering of Large-scale Scenes on the Web
https://github.com/WU-CVGL/BAD-Gaussians
공식 코드https://github.com/WU-CVGL/BAD-NeRF
공식 코드https://github.com/aaltoml/uncertainty-nerf-gs
공식 코드https://github.com/aim-uofa/AdelaiDepth
공식 코드https://github.com/alextrevithick/GRF
공식 코드GRF: Learning a General Radiance Field for 3D Representation and Rendering
https://github.com/astra-vision/SceneRF
공식 코드SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
https://github.com/avinashpaliwal/PanoDreamer
공식 코드PanoDreamer: Optimization-Based Single Image to 360 3D Scene With Diffusion
https://github.com/azhuantou/mixgs
공식 코드Holistic Large-Scale Scene Reconstruction via Mixed Gaussian Splatting
https://github.com/biter0088/pc-nerf
공식 코드https://github.com/cerf-volant425/thermal-nerf
공식 코드Thermal-NeRF: Neural Radiance Fields from an Infrared Camera
https://github.com/charliesong1999/flashdreamer
공식 코드Enhancing Monocular 3D Scene Completion with Diffusion Model
https://github.com/chaytonmin/occ-bev
공식 코드UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving
https://github.com/chaytonmin/uniscene
공식 코드UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving
https://github.com/chtsy/buol
공식 코드https://github.com/cmlab-korea/awesome-3d-low-level-vision
공식 코드R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
https://github.com/cv-rits/MonoScene
공식 코드https://github.com/cvmi-lab/total-decom
공식 코드Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction
https://github.com/eldar/flash3d
공식 코드Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image
https://github.com/esw0116/odgs
공식 코드ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings
https://github.com/facebookresearch/Replica-Dataset
공식 코드https://github.com/fraunhoferhhi/Self-Organizing-Gaussians
공식 코드Compact 3D Scene Representation via Self-Organizing Gaussian Grids
https://github.com/fudan-zvg/Brain3D
공식 코드https://github.com/fudan-zvg/openocc
공식 코드OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation
https://github.com/fudan-zvg/realengine
공식 코드RealEngine: Simulating Autonomous Driving in Realistic Context
https://github.com/ganlab/ostra
공식 코드A One Stop 3D Target Reconstruction and multilevel Segmentation Method
https://github.com/google-research/corenet
공식 코드CoReNet: Coherent 3D scene reconstruction from a single RGB image
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.