Search Results for author:
Found 2 papers, 0 papers with code
Self-Supervised Monocular Depth Estimation in the Dark: Towards Data Distribution Compensation
In this paper, we propose a self-supervised nighttime monocular depth estimation method that does not use any night images during training.
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding
Humans commonly work with multiple objects in daily life and can intuitively transfer manipulation skills to novel objects by understanding object functional regularities.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
