The motion of the camera can cause images of pedestrians to be captured at extreme angles. This can lead to very poor pedestrian detection performance when using standard pedestrian detectors. To address this issue, we propose a Rotational Rectification Network (R2N) that can be inserted into any CNN-based pedestrian (or object) detector to adapt it to significant changes in camera rotation.
Keywords: Reinforcement Learning, Robotic Manipulation, Automatic Curriculum
Generation
本文档是卡耐基梅隆大学机器人研究所的技术论文。
Our method yields R-squared correlation of 0.88 for stalk count and a mean absolute error of
2.77mm where average stalk width is 14.354mm. Our approach is 30 times faster for stalk count and 270 times faster for stalk width measurement.
本文档是卡耐基梅隆大学机器人研究所的技术论文。
Looking Forward: A Semantic Mapping System for Scouting with Micro-Aerial Vehicles
Our ultimate goal is to enable MAVs to perform autonomous scouting. In this paper, we describe a semantic mapping system designed to support this goal. The system maintains a 2.5D map describing its belief about the location of semantic classes of interest, using forward-looking cameras and state estimation.
Learning to Model the Tail
We describe an approach to learning from long-tailed, imbalanced datasets that
are prevalent in real-world settings.
Virtual Navigation for Blind People: Building Sequential Representations of the Real-World
We would like to understand if building the same type of sequential representation, prior to navigating in a new location, is helpful for people with visual impairments (VI).
本文档是卡耐基梅隆大学机器人研究所的技术论文。
DROAN - Disparity-space Representation for Obstacle Avoidance
The presented approach enables high speed navigation at low altitudes for MAVs for terrestrial scouting.
本文档是卡耐基梅隆大学机器人研究所的技术论文。
A Generalized Model for Multimodal Perception
We develop a graphical model for fusing object recognition results using two different modalities–computer vision and verbal descriptions. In this paper, we specifically focus
on three types of verbal descriptions, namely, egocentric positions, relative positions using a landmark, and numeric constraints.
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