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Submission data

Full nameTemporal-AwareDepthFusion
DescriptionA temporal depth fusion approach that combines stereo-derived depth maps across consecutive frames to improve scene reconstruction and localization. The system uses motion-compensated depth aggregation, confidence-based filtering, and inertial guidance to produce stable depth estimates in dynamic and low-light environments. Global optimization is applied to reduce drift and maintain long-term consistency.
ParametersDepth fusion window: 12 frames
Depth confidence threshold: 0.70
Motion compensation iterations: 8
Keyframe overlap ratio: 0.65
Global optimization interval: 50 frames
IMU influence factor: 0.30
Programming language(s)C++, Python, CUDA
HardwareA100
Submission creation date24 Jun, 2026
Last edited24 Jun, 2026

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