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Found 6 papers, 0 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.
SIMBAR: Single Image-Based Scene Relighting For Effective Data Augmentation For Automated Driving Vision Tasks
To the best of our knowledge, there is no prior work on scene relighting leveraging explicit geometric representations from a single image.
Deflating Dataset Bias Using Synthetic Data Augmentation
Deep Learning has seen an unprecedented increase in vision applications since the publication of large-scale object recognition datasets and introduction of scalable compute hardware.
On the Role of Receptive Field in Unsupervised Sim-to-Real Image Translation
Generative Adversarial Networks (GANs) are now widely used for photo-realistic image synthesis.
Context-Aware Pedestrian Motion Prediction In Urban Intersections
This paper presents a novel context-based approach for pedestrian motion prediction in crowded, urban intersections, with the additional flexibility of prediction in similar, but new, environments.
A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries
This paper presents a novel framework for accurate pedestrian intent prediction at intersections.
