3 citations · 3 across the 2 of their papers we have counts for
4 papers
Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion
Kamil Adamczewski, Christos Sakaridis, Vaishakh Patil +1
Lidar is a vital sensor for estimating the depth of a scene. Typical spinning lidars emit pulses arranged in several horizontal lines and the monetary cost of the sensor increases…
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior
Vaishakh Patil, Christos Sakaridis, Alexander Liniger +1
Monocular depth estimation is vital for scene understanding and downstream tasks. We focus on the supervised setup, in which ground-truth depth is available only at training time.…
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video
Vaishakh Patil, Wouter Van Gansbeke, Dengxin Dai +1
Autonomous cars need continuously updated depth information. Thus far, depth is mostly estimated independently for a single frame at a time, even if the method starts from video in…
Self-supervised Object Motion and Depth Estimation from Video
Qi Dai, Vaishakh Patil, Simon Hecker +3
We present a self-supervised learning framework to estimate the individual object motion and monocular depth from video. We model the object motion as a 6 degree-of-freedom rigid-b…