https://github.com/pothabattulasantosh/Detection-of-facial-Manipulated-videos
FaceForensics++: Learning to Detect Manipulated Facial Images
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/pranavbajoria93/3D_Reconstruction_3DR2N2
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
https://github.com/pubgeo/dfc2019
https://github.com/purdue-m2/robust_fairness_withNoisy_labels
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/pwc-1/Paper-9/tree/main/5/wavlm
https://github.com/qishanzhang/slsforadd
https://github.com/qizekun/vpp
https://github.com/raphaelsulzer/dgnn
https://github.com/raphaelsulzer/dsr-benchmark
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
https://github.com/raphaelsulzer/dsrv-data
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
https://github.com/raymondwang987/fmnet
NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation
https://github.com/revanurambareesh/multiperson
Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
https://github.com/rmurai0610/mast3r-slam
MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
https://github.com/sahibzadaadil/Lip-Sync-Matters-A-Novel-Multimodal-Forgery-Detector
https://github.com/salykovaa/instant-DexNerf
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/samb-t/unleashing-transformers
https://github.com/sap3d/Sap3D
https://github.com/seongilp/DFE604-2020F-FinalProject
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/seung-lab/Augmentor
https://github.com/seung-lab/DataProvider3
https://github.com/seung-lab/DeepEM
https://github.com/shamanez/Target-Driven-Visual-Navigation-with-Distributed-PPO
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning
https://github.com/shuhongchen/panic3d-anime-reconstruction
PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
https://github.com/sjb3d/descent/tree/main/examples/image_fit
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/skanti/Scan2CAD
https://github.com/skanti/Scan2CAD-Annotation-Webapp
https://github.com/skyworkai/mvgamba
Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction
https://github.com/smu-ivpl/DeepfakeDetection
https://github.com/subhayanmukherjee/autoroi
Highlighting objects of interest in an image by integrating saliency and depth
https://github.com/sunset1995/pytorch-layoutnet
LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image
https://github.com/syb7573330/im2avatar
https://github.com/szymanowiczs/viewset-diffusion
Viewset Diffusion: (0-)Image-Conditioned 3D Generative Models from 2D Data
https://github.com/takhemlata/ssl_anti-spoofing
https://github.com/tencent/flashvdm
TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
https://github.com/tgisaturday/taming-transformers-tpu
https://github.com/thomasslloyd/FitSpatial
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.