4 papers
DGSfM: Depth-Guided Scale-Aware Global Structure-from-Motion
Sithu Aung, Viktor Kocur, Yaqing Ding +2
Global Structure-from-Motion (SfM) is an efficient paradigm for recovering camera poses and sparse 3D structure from unordered images. However, its reliance on scale-ambiguous epip…
PLOT: Pseudo-Labeling via Object Tracking for Monocular 3D Object Detection
Seokyeong Lee, Sithu Aung, Junyong Choi +3
Monocular 3D object detection is crucial for scalable perception across fields like autonomous driving, robotics, and surveillance. However, progress is hindered by limited 3D anno…
Depth2Pose: A Pose-Based Benchmark for Monocular Depth Estimation without Ground-Truth Depth
Viktor Kocur, Sithu Aung, Gabrielle Flood +4
Monocular depth estimation has improved significantly in recent years, driven by increasingly powerful models and large-scale training data. Predicted depth is increasingly used as…
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset
Sithu Aung, Min-Cheol Sagong, Junghyun Cho
We address an advanced challenge of predicting pedestrian occupancy as an extension of multi-view pedestrian detection in urban traffic. To support this, we have created a new synt…