Scene Generation
62 papers with code • 5 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Scene Generation
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Libraries
Use these libraries to find Scene Generation models and implementations
Replica
VizDoom
AVD
CoDraw
OSM
GoogleEarth
InstaOrder
3D FRONT HUMAN
Latest papers
GAUDI: A Neural Architect for Immersive 3D Scene Generation
We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera.
Towards Improving the Generation Quality of Autoregressive Slot VAEs
pemami4911/segregate-relate-imagine
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We propose two improvements that strengthen object correlation learning.
Modeling Image Composition for Complex Scene Generation
johndreamer/twfa
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CVPR 2022
Compared to existing CNN-based and Transformer-based generation models that entangled modeling on pixel-level&patch-level and object-level&patch-level respectively, the proposed focal attention predicts the current patch token by only focusing on its highly-related tokens that specified by the spatial layout, thereby achieving disambiguation during training.
Risk-Aware Scene Sampling for Dynamic Assurance of Autonomous Systems
Our samplers of RNS and GBO sampled a higher percentage of high-risk scenes of 83% and 92%, compared to 56%, 66% and 71% of the grid, random and Halton samplers, respectively.
Vehicle trajectory prediction works, but not everywhere
vita-epfl/s-attack
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CVPR 2022
We further show that the generated scenes (i) are realistic since they do exist in the real world, and (ii) can be used to make existing models more robust, yielding 30-40 reductions in the off-road rate.
Compositional Transformers for Scene Generation
dorarad/gansformer
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NeurIPS 2021
We introduce the GANformer2 model, an iterative object-oriented transformer, explored for the task of generative modeling.
Compositional Transformers for Scene Generation
dorarad/gansformer
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NeurIPS 2021
We introduce the GANformer2 model, an iterative object-oriented transformer, explored for the task of generative modeling.
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
amazon-research/indoor-scene-generation-eai
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However, current simulators for Embodied AI (EAI) challenges only provide simulated indoor scenes with a limited number of layouts.
MIGS: Meta Image Generation from Scene Graphs
migs2021/migs
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We propose MIGS (Meta Image Generation from Scene Graphs), a meta-learning based approach for few-shot image generation from graphs that enables adapting the model to different scenes and increases the image quality by training on diverse sets of tasks.
Indoor Scene Generation from a Collection of Semantic-Segmented Depth Images
mingjiayang/sgsdi
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ICCV 2021
Different from existing methods that represent an indoor scene with the type, location, and other properties of objects in the room and learn the scene layout from a collection of complete 3D indoor scenes, our method models each indoor scene as a 3D semantic scene volume and learns a volumetric generative adversarial network (GAN) from a collection of 2. 5D partial observations of 3D scenes.
