https://github.com/jiayi-wu-umd/marvis
공식 코드MARVIS: Motion & Geometry Aware Real and Virtual Image Segmentation
Papers with Code 아카이브
3D Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 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/jieqianyu/sgn
공식 코드Camera-based 3D Semantic Scene Completion with Sparse Guidance Network
https://github.com/jinec98/mae3d
공식 코드Masked Autoencoders in 3D Point Cloud Representation Learning
https://github.com/jiutongbro/multiview_inpaint
공식 코드Generative Object Insertion in Gaussian Splatting with a Multi-View Diffusion Model
https://github.com/jkulhanek/tetra-nerf
공식 코드Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra
https://github.com/jmpu/webconf21-deepfakes-in-the-wild
공식 코드https://github.com/joaxkal/lumigauss
공식 코드https://github.com/johanye/vf-net
공식 코드https://github.com/jokester-zzz/ssa-sc
공식 코드Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds
https://github.com/json87/spheresfm
공식 코드3D Reconstruction of Spherical Images based on Incremental Structure from Motion
https://github.com/junshengzhou/3dattriflow
공식 코드3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow
https://github.com/junyuandeng/dm-calib
공식 코드Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration
https://github.com/justanhduc/graphx-conv
공식 코드GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
https://github.com/justimyhxu/grm
공식 코드GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation
https://github.com/jwubz123/DIG3D
공식 코드LeanGaussian: Breaking Pixel or Point Cloud Correspondence in Modeling 3D Gaussians
https://github.com/jwubz123/UNIG
공식 코드UniGS: Modeling Unitary 3D Gaussians for Novel View Synthesis from Sparse-view Images
https://github.com/jytime/Deep-SfM-Revisited
공식 코드https://github.com/jzhangbs/Vis-MVSNet
공식 코드https://github.com/jzr99/Geo4D
공식 코드Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstruction
https://github.com/kacperkan/conerf
공식 코드https://github.com/kaiekubjas/3d-genome-reconstruction-from-partially-phased-hic-data
공식 코드https://github.com/kailaisun/indoor-depth-completion
공식 코드A Two-Stage Masked Autoencoder Based Network for Indoor Depth Completion
https://github.com/kaist-visual-ai-group/odc
공식 코드https://github.com/kalyo-zjl/WM3DR
공식 코드https://github.com/kbatsos/real-time-stereo
공식 코드https://github.com/kcshum/pose-conditioned-NeRF-object-fusion
공식 코드Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates
https://github.com/khainb/ebsw
공식 코드https://github.com/kidleyh/smw-gs
공식 코드Micro-macro Gaussian Splatting with Enhanced Scalability for Unconstrained Scene Reconstruction
https://github.com/kikohs/freak
공식 코드https://github.com/kshitijkarnawat/structure-from-motion
공식 코드https://github.com/kuangzijian/drifu-for-animals
공식 코드https://github.com/kxhit/EscherNet
공식 코드https://github.com/kyleolsz/TB-Networks
공식 코드https://github.com/l8cv/busterx
공식 코드BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation
https://github.com/lab4d-org/lab4d
공식 코드https://github.com/laiyingxin2/dadf
공식 코드Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.