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Found 5 papers, 1 papers with code
LANe: Lighting-Aware Neural Fields for Compositional Scene Synthesis
Specifically, we learn a scene representation that disentangles the static background and transient elements into a world-NeRF and class-specific object-NeRFs to allow compositional synthesis of multiple objects in the scene.
CLONeR: Camera-Lidar Fusion for Occupancy Grid-aided Neural Representations
Recent advances in neural radiance fields (NeRFs) achieve state-of-the-art novel view synthesis and facilitate dense estimation of scene properties.
Shadow Transfer: Single Image Relighting For Urban Road Scenes
There have been impressive advances in the realm of image to image translation in transferring previously unseen visual effects into a dataset, specifically in day to night translation.
Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation
This domain shift is especially exaggerated between synthetic and real datasets.
Modeling Camera Effects to Improve Visual Learning from Synthetic Data
Recent work has focused on generating synthetic imagery to increase the size and variability of training data for learning visual tasks in urban scenes.
