https://github.com/tkz24589/SketchBodyNet
공식 코드SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction
Papers with Code 아카이브
3D Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/tobiasfshr/MOTSFusion
공식 코드https://github.com/tobuta/PolyGlotFake
공식 코드PolyGlotFake: A Novel Multilingual and Multimodal DeepFake Dataset
https://github.com/tqtqliu/et-mvsnet
공식 코드When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo
https://github.com/trailab/uncertainshapepose
공식 코드Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors
https://github.com/tranluan/Nonlinear_Face_3DMM
공식 코드https://github.com/truongkhang/cds-mvsnet
공식 코드Curvature-guided dynamic scale networks for Multi-view Stereo
https://github.com/tub-rip/dvs_mcemvs
공식 코드Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events Fusion
https://github.com/tum-vision/tandem
공식 코드TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
https://github.com/tyraeldlee/diffpmae
공식 코드DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction
https://github.com/ucl-candi/freehand
공식 코드Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker
https://github.com/ucsc-vlaa/microdiffusion
공식 코드https://github.com/ucsdarclab/python-super
공식 코드https://github.com/ucwxb/nto3d
공식 코드NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
https://github.com/v715/DiffDRR
공식 코드https://github.com/val-iisc/3d-lmnet
공식 코드https://github.com/val-iisc/3d-psrnet
공식 코드3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image
https://github.com/val-iisc/capnet
공식 코드CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision
https://github.com/val-iisc/densepcr
공식 코드Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network
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/valeoai/poco
공식 코드https://github.com/valette/frog
공식 코드https://github.com/varunburde/reconstruction_pose_benchmark
공식 코드Comparative Evaluation of 3D Reconstruction Methods for Object Pose Estimation
https://github.com/vast-ai-research/triposr
공식 코드https://github.com/vcbsl/audio-visual-deepfake
공식 코드Contextual Cross-Modal Attention for Audio-Visual Deepfake Detection and Localization
https://github.com/vcg-njust/lrl-gqa
공식 코드No-reference geometry quality assessment for colorless point clouds via list-wise rank learning
https://github.com/vchoutas/smplify-x
공식 코드Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
https://github.com/vibot-lab/pola4all_jei_2023
공식 코드Pola4All: survey of polarimetric applications and an open-source toolkit to analyze polarization
https://github.com/vignywang/awesome-local-feature-matching
공식 코드https://github.com/vinairesearch/lemul
공식 코드https://github.com/vinay-lanka/ObitoNet
공식 코드ObitoNet: Multimodal High-Resolution Point Cloud Reconstruction
https://github.com/vincentfung13/MINE
공식 코드MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis
https://github.com/vinits5/learning3d
공식 코드PCRNet: Point Cloud Registration Network using PointNet Encoding
https://github.com/vinits5/pcrnet
공식 코드PCRNet: Point Cloud Registration Network using PointNet Encoding
https://github.com/vinits5/pcrnet_pytorch
공식 코드PCRNet: Point Cloud Registration Network using PointNet Encoding
https://github.com/vinits5/pointnet-registration-framework
공식 코드One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.