https://github.com/med-air/endonerf
공식 코드Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery
Papers with Code 아카이브
Neural Rendering
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Given a representation of a 3D scene of some kind (point cloud, mesh, voxels, etc.), the task is to create an algorithm that can produce photorealistic renderings of this scene from an arbitrary viewpoint. Sometimes, the task is accompanied by image/scene appearance manipulation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/megvii-research/AAAI2023-PVD
공식 코드https://github.com/michaelwilliamtang/golden-retriever
공식 코드https://github.com/microsoft/ConfigNet
공식 코드https://github.com/microsoft/renderformer
공식 코드RenderFormer: Transformer-based Neural Rendering of Triangle Meshes with Global Illumination
https://github.com/mirevi/face-synthesizer-jvrb
공식 코드https://github.com/miu200521358/NeuralVoicePuppetryMMD
공식 코드https://github.com/mvkolos/TRANSPR
공식 코드TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer
https://github.com/ndrwmlnk/stroke-rendering
공식 코드https://github.com/nexuslrf/ENVIDR
공식 코드ENVIDR: Implicit Differentiable Renderer with Neural Environment Lighting
https://github.com/nirvanalan/ln3diff
공식 코드LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation
https://github.com/nvlabs/3dgm
공식 코드Memorize What Matters: Emergent Scene Decomposition from Multitraverse
https://github.com/nvlabs/instant-ngp
공식 코드Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/nvlabs/tiny-cuda-nn
공식 코드https://github.com/oneThousand1000/Portrait3D
공식 코드https://github.com/openxrlab/xrfeitoria
공식 코드SynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and Modeling
https://github.com/pjlab-ADG/neuralsim
공식 코드StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Views
https://github.com/pjlab-adg/awesome-knowledge-driven-ad
공식 코드https://github.com/pjlab-adg/oasim
공식 코드OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving
https://github.com/princeton-computational-imaging/neural-scene-graphs
공식 코드https://github.com/princeton-computational-imaging/neural_raytracing
공식 코드Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis
https://github.com/pulangk97/SANeRF
공식 코드https://github.com/qianlim/SCALE
공식 코드SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements
https://github.com/qianmingduowan/Sat2Density
공식 코드Sat2Density: Faithful Density Learning from Satellite-Ground Image Pairs
https://github.com/realcrane/student-splating-scooping
공식 코드https://github.com/redrock303/NeRFLiX_CPVR2023
공식 코드NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXer
https://github.com/renyurui/pirender
공식 코드PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering
https://github.com/ruijiezhu94/ti-face
공식 코드TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces
https://github.com/s3anwu/pbrnerf
공식 코드PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields
https://github.com/saic-violet/bilayer-model
공식 코드Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars
https://github.com/sainingzhang/uc-gs
공식 코드Drone-assisted Road Gaussian Splatting with Cross-view Uncertainty
https://github.com/samuel-cerezo/SLAM-Render
공식 코드SLAM&Render: A Benchmark for the Intersection Between Neural Rendering, Gaussian Splatting and SLAM
https://github.com/seralab/robust-and-accurate-uv-map-based-camouflage-attack
공식 코드https://github.com/shamanDevel/AdaptiveSampling
공식 코드Learning Adaptive Sampling and Reconstruction for Volume Visualization
https://github.com/shawLyu/Occ-SDF-Hybrid
공식 코드https://github.com/shreyvish5678/SR-NeRF-with-Variational-Diffusion-Strategies
공식 코드Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.