549 citations · 1.5k across the 32 of their papers we have counts for
8 papers · 1 filter
Piecewise Planar Hulls for Semi-Supervised Learning of 3D Shape and Pose from 2D Images
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
We study the problem of estimating 3D shape and pose of an object in terms of keypoints, from a single 2D image. The shape and pose are learned directly from images collected by ca…
Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields
Soomin Lee, Le Chen, Jiahao Wang +3
In this paper, we tackle the problem of active robotic 3D reconstruction of an object. In particular, we study how a mobile robot with an arm-held camera can select a favorable num…
Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds
Ayoub Raji, Alexander Liniger, Andrea Giove +6
This paper presents a multi-layer motion planning and control architecture for autonomous racing, capable of avoiding static obstacles, performing active overtakes, and reaching ve…
Deep Gradient Learning for Efficient Camouflaged Object Detection
Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou +3
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branc…
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
Jose L. Vazquez, Alexander Liniger, Wilko Schwarting +2
In most classical Autonomous Vehicle (AV) stacks, the prediction and planning layers are separated, limiting the planner to react to predictions that are not informed by the planne…
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.…