125 citations · 543 across the 31 of their papers we have counts for
10 papers · 1 filter
Planning Paths Through Unknown Space by Imagining What Lies Therein
Yutao Han, Jacopo Banfi, Mark Campbell
This paper presents a novel framework for planning paths in maps containing unknown spaces, such as from occlusions. Our approach takes as input a semantically-annotated point clou…
Mixed-Integer Linear Programming Models for Multi-Robot Non-Adversarial Search
Beatriz A. Asfora, Jacopo Banfi, Mark Campbell
In this letter, we consider the Multi-Robot Efficient Search Path Planning (MESPP) problem, where a team of robots is deployed in a graph-represented environment to capture a movin…
Wasserstein Distances for Stereo Disparity Estimation
Divyansh Garg, Yan Wang, Bharath Hariharan +3
Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values. This leads to inaccurate results when the true depth or dispar…
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
Yan Wang, Xiangyu Chen, Yurong You +5
In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike. While deep networks are great…
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
Rui Qian, Divyansh Garg, Yan Wang +6
Reliable and accurate 3D object detection is a necessity for safe autonomous driving. Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment, they…
DeepSemanticHPPC: Hypothesis-based Planning over Uncertain Semantic Point Clouds
Yutao Han, Hubert Lin, Jacopo Banfi +2
Planning in unstructured environments is challenging -- it relies on sensing, perception, scene reconstruction, and reasoning about various uncertainties. We propose DeepSemanticHP…
Interactive Natural Language-based Person Search
Vikram Shree, Wei-Lun Chao, Mark Campbell
In this work, we consider the problem of searching people in an unconstrained environment, with natural language descriptions. Specifically, we study how to systematically design a…
Revisiting Meta-Learning as Supervised Learning
Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan +2
Recent years have witnessed an abundance of new publications and approaches on meta-learning. This community-wide enthusiasm has sparked great insights but has also created a pleth…
Pedestrian Motion Model Using Non-Parametric Trajectory Clustering and Discrete Transition Points
Yutao Han, Rina Tse, Mark Campbell
This paper presents a pedestrian motion model that includes both low level trajectory patterns, and high level discrete transitions. The inclusion of both levels creates a more gen…
An Empirical Study of Person Re-Identification with Attributes
Vikram Shree, Wei-Lun Chao, Mark Campbell
Person re-identification aims to identify a person from an image collection, given one image of that person as the query. There is, however, a plethora of real-life scenarios where…