Boundless: Generating Photorealistic Synthetic Data for Object Detection in Urban Streetscapes
We introduce Boundless, a photo-realistic synthetic data generation system for enabling highly accurate object detection in dense urban streetscapes. Boundless can replace massive real-world data collection and manual ground-truth object annotation (labeling) with an automated and configurable process. Boundless is based on the Unreal Engine 5 (UE5) City Sample project with improvements enabling accurate collection of 3D bounding boxes across different lighting and scene variability conditions. We evaluate the performance of object detection models trained on the dataset generated by Boundless when used for inference on a real-world dataset acquired from medium-altitude cameras. We compare the performance of the Boundless-trained model against the CARLA-trained model and observe an improvement of 7.8 mAP. The results we achieved support the premise that synthetic data generation is a credible methodology for training/fine-tuning scalable object detection models for urban scenes.
Code (1)
Tasks
Objectobject-detectionObject DetectionSynthetic Data GenerationSimilar Papers 제목 키워드 기반
Comparing Photorealism in Game Engines for Synthetic Maritime Computer Vision Datasets
Computer vision for real-world applications faces data acquisition challenges, including accessibility, high costs, difficulty in obtaining diversity in scenarios or environmental conditions. Synthetic data usage has sur…
DiversityObject RecognitionUnityFaster Superword Tokenization
Byte Pair Encoding (BPE) is a widely used tokenization algorithm, whose tokens cannot extend across pre-tokenization boundaries, functionally limiting it to representing at most full words. The BoundlessBPE and SuperBPE …
UrbanGIRAFFE: Representing Urban Scenes as Compositional Generative Neural Feature Fields
Generating photorealistic images with controllable camera pose and scene contents is essential for many applications including AR/VR and simulation. Despite the fact that rapid progress has been made in 3D-aware generati…
3D-Aware Image SynthesisImage GenerationObjectDetection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data
We show a straightforward and useful methodology for performing instance segmentation using synthetic data. We apply this methodology on a basic case and derived insights through quantitative analysis. We created a new p…
Instance SegmentationObject DetectionSegmentationSemantic SegmentationHigh Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images
Generating photorealistic images of human faces at scale remains a prohibitively difficult task using computer graphics approaches. This is because these require the simulation of light to be photorealistic, which in tur…
Domain AdaptationVocal Bursts Intensity Prediction