Papers with Code 아카이브
Scene Generation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Layout-Generation/layout-generation/tree/master/LayoutVAE
LayoutVAE: Stochastic Scene Layout Generation From a Label Set
https://github.com/MindSpore-scientific-2/code-2/tree/main/Super-Resolution-for-Root-Imaging
ROOT: VLM based System for Indoor Scene Understanding and Beyond
https://github.com/MindSpore-scientific-2/code-5/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
https://github.com/MindSpore-scientific/code-1/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
https://github.com/MindSpore-scientific/code-10/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
https://github.com/MindSpore-scientific/code-10/tree/main/Super-Resolution-for-Root-Imaging
ROOT: VLM based System for Indoor Scene Understanding and Beyond
https://github.com/Touyuki/Cover_generation
Specifying Object Attributes and Relations in Interactive Scene Generation
https://github.com/arlo0o/uniscene-unified-occupancy-centric-driving-scene-generation
UniScene: Unified Occupancy-centric Driving Scene Generation
https://github.com/chenguolin/InstructScene
CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic Furniture Embedding
https://github.com/e96031413/AA-YOLO
https://github.com/e96031413/PyTorch_YOLOv4-tiny
https://github.com/findaheng/Scenic
Scenic: A Language for Scenario Specification and Scene Generation
https://github.com/gpt4vision/OvSGTR
What Makes a Scene ? Scene Graph-based Evaluation and Feedback for Controllable Generation
https://github.com/jinyangyuan/genesis
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
https://github.com/kampta/DeepLayout
LayoutVAE: Stochastic Scene Layout Generation From a Label Set
https://github.com/liorfrenkel1992/SB-GAN
https://github.com/lizuoyue/sat2scene
Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion
https://github.com/lucidrains/pi-GAN-pytorch
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
https://github.com/lucidrains/transganformer
https://github.com/mees/AIS-Alexa-Robot
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
https://github.com/mees/pickAndPlace-PR2
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
https://github.com/nekitmm/FunnelAct_Pytorch
https://github.com/nv-tlabs/atiss
https://github.com/roeiherz/AG2Video
Learning Canonical Representations for Scene Graph to Image Generation
https://github.com/shuuchen/frelu.pytorch
https://github.com/singhgautam/sysbinder
https://github.com/urbanarchitect/urbanarchitect
Urban Architect: Steerable 3D Urban Scene Generation with Layout Prior
https://github.com/vita-epfl/s-attack
https://github.com/wzzheng/doe
https://github.com/yangling0818/sgdiff
https://github.com/yangyucheng000/University/tree/main/model-2/funnel
https://github.com/ymxlzgy/echoscene
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion
https://github.com/yzhou359/MakeItTalk
SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation
https://github.com/zyf12389/LayoutGAN-Alpha
LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.