2025
ETA: Energy-based Test-time Adaptation for Depth Completion
ICCV 2025poster
We propose a method of adapting pretrained depth completion models to test time data in an unsupervised manner. Depth completion models are (pre)trained to produce dense depth maps from pairs of RGB image and sparse depth maps in ideal capture conditions (source domain), e.g., well-illuminated, high…