https://github.com/daniilidis-group/EvAC3D
공식 코드EvAC3D: From Event-based Apparent Contours to 3D Models via Continuous Visual Hulls
Papers with Code 아카이브
3D Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/danmohaha/celeb-deepfakeforensics
공식 코드Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/darglein/NeAT
공식 코드https://github.com/darioizzo/geodesynets
공식 코드Geodesy of irregular small bodies via neural density fields: geodesyNets
https://github.com/darylperalta/Houses3K
공식 코드https://github.com/darylperalta/ScanRL
공식 코드https://github.com/dash-lab/fakeavceleb
공식 코드FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
https://github.com/david-stojanovski/e-pix2vox-reconstruction
공식 코드Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D echo views
https://github.com/davidcombei/ai4t
공식 코드Unmasking real-world audio deepfakes: A data-centric approach
https://github.com/daviddmc/svort
공식 코드SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI
https://github.com/davide-coccomini/Combining-EfficientNet-and-Vision-Transformers-for-Video-Deepfake-Detection
공식 코드Combining EfficientNet and Vision Transformers for Video Deepfake Detection
https://github.com/davide-coccomini/Combining-EfficientNet-and-Vision-Transformersfor-Video-Deepfake-Detection
공식 코드Combining EfficientNet and Vision Transformers for Video Deepfake Detection
https://github.com/davide-coccomini/Cross-Forgery-Analysis-of-Vision-Transformers-and-CNNs-for-Deepfake-Image-Detection
공식 코드Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection
https://github.com/davide-coccomini/adversarial-magnification-to-deceive-deepfake-detection-through-super-resolution
공식 코드Adversarial Magnification to Deceive Deepfake Detection through Super Resolution
https://github.com/davide-coccomini/deepfake-detection-without-deepfakes-generalization-via-synthetic-frequency-patterns-injection
공식 코드Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection
https://github.com/davide-coccomini/mintime-multi-identity-size-invariant-timesformer-for-video-deepfake-detection
공식 코드MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection
https://github.com/davidstotko/physics-guided-shape-from-template
공식 코드Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models
https://github.com/davzha/DESP
공식 코드Set Prediction without Imposing Structure as Conditional Density Estimation
https://github.com/dawning77/nerrf
공식 코드https://github.com/dcharatan/pixelsplat
공식 코드pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction
https://github.com/deepfakeil/dfil
공식 코드DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
https://github.com/deezer/deepfake-detector
공식 코드https://github.com/deguchihiroyuki/e2gs
공식 코드https://github.com/densoitlab/fed3dgs
공식 코드Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning
https://github.com/desaixie/zeroverse
공식 코드LRM-Zero: Training Large Reconstruction Models with Synthesized Data
https://github.com/devlearning-gt/3DShapeGen
공식 코드https://github.com/dflip3k/dflip-3k
공식 코드Linguistic Profiling of Deepfakes: An Open Database for Next-Generation Deepfake Detection
https://github.com/diegovalsesia/xmfnet
공식 코드Cross-modal Learning for Image-Guided Point Cloud Shape Completion
https://github.com/dimtziwnas/InHandScanningICCV15_Reconstruction
공식 코드https://github.com/dineshsrivasthav/adaptive_meta_learning_with_multi_agent_framework
공식 코드https://github.com/dkulon/hand-reconstruction
공식 코드https://github.com/dnn-security/gan-watermark
공식 코드PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generators
https://github.com/dogyoonlee/dp-nerf
공식 코드DP-NeRF: Deblurred Neural Radiance Field with Physical Scene Priors
https://github.com/dominickrei/limited-data-vits
공식 코드Limited Data, Unlimited Potential: A Study on ViTs Augmented by Masked Autoencoders
https://github.com/donydchen/mvsplat
공식 코드MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images
https://github.com/donydchen/mvsplat360
공식 코드MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.