https://github.com/eckertzhang/text2nerf
공식 코드Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields
Papers with Code 아카이브
Scene Generation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/frozenburning/scenedreamer
공식 코드SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collections
https://github.com/fudan-zvg/Brain3D
공식 코드https://github.com/fudan-zvg/wovogen
공식 코드WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation
https://github.com/google-research/google-research/tree/master/persistent-nature
공식 코드Persistent Nature: A Generative Model of Unbounded 3D Worlds
https://github.com/hananshafi/llmblueprint
공식 코드LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
https://github.com/hancyran/lidar-diffusion
공식 코드Towards Realistic Scene Generation with LiDAR Diffusion Models
https://github.com/harrytea/root
공식 코드ROOT: VLM based System for Indoor Scene Understanding and Beyond
https://github.com/heboyong/Generalized-Diffusion-Detector
공식 코드https://github.com/hkust-vgd/neural_scene_decoration
공식 코드https://github.com/horizonrobotics/gump
공식 코드Solving Motion Planning Tasks with a Scalable Generative Model
https://github.com/hubert0527/infinityGAN
공식 코드https://github.com/hyenal/relate
공식 코드RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
https://github.com/hzxie/CityDreamer
공식 코드CityDreamer: Compositional Generative Model of Unbounded 3D Cities
https://github.com/hzxie/CityDreamer4D
공식 코드CityDreamer4D: Compositional Generative Model of Unbounded 4D Cities
https://github.com/hzxie/GaussianCity
공식 코드GaussianCity: Generative Gaussian Splatting for Unbounded 3D City Generation
https://github.com/hzxie/awesome-3d-scene-generation
공식 코드https://github.com/imlixinyang/director3d
공식 코드Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text
https://github.com/jbadiat/supertoroidfitting
공식 코드Supertoroid fitting of objects with holes for robotic grasping and scene generation
https://github.com/johndreamer/twfa
공식 코드https://github.com/josef5838/sg-tailor
공식 코드SG-Tailor: Inter-Object Commonsense Relationship Reasoning for Scene Graph Manipulation
https://github.com/kregmi/cross-view-image-synthesis
공식 코드https://github.com/li-zn-h/simworld
공식 코드SimWorld: A Unified Benchmark for Simulator-Conditioned Scene Generation via World Model
https://github.com/liwrui/scenedreamer360
공식 코드SceneDreamer360: Text-Driven 3D-Consistent Scene Generation with Panoramic Gaussian Splatting
https://github.com/lmd0311/hermes
공식 코드HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation
https://github.com/lzzcd001/MeshDiffusion
공식 코드https://github.com/lzzzzzm/ii-world
공식 코드$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting
https://github.com/marcoamonteiro/pi-GAN
공식 코드pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
https://github.com/megvii-model/FunnelAct
공식 코드https://github.com/megvii-research/NAFNet
공식 코드FSID: Fully Synthetic Image Denoising via Procedural Scene Generation
https://github.com/mengcye/LAION-SG
공식 코드https://github.com/miaoqiaowei/awesome-4d
공식 코드https://github.com/migs2021/migs
공식 코드https://github.com/mingjiayang/sgsdi
공식 코드Indoor Scene Generation from a Collection of Semantic-Segmented Depth Images
https://github.com/nepfaff/steerable-scene-generation
공식 코드Steerable Scene Generation with Post Training and Inference-Time Search
https://github.com/nihalsid/retrieval-fuse
공식 코드RetrievalFuse: Neural 3D Scene Reconstruction with a Database
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.