8 accepted papers
A compact reconfigurable terrestrial-aerial robot that is capable of executing seamless transitions between three motion modes—rolling, crawling, and flying—via foldable mechanisms is presented in this letter. The rolling and crawling modes are facilitated by two passive gear-driven, foldable wheel-
Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Network (CNN) based semantic segmentation approaches have achieved impressive results by using large amounts of labeled train…
Many emerging applications of intelligent robots need to explore and understand new environments, where it is desirable to detect objects of novel categories on the fly with minimum online efforts. This is an object detection on demand (ODOD) task. It is challenging, because it is impossible to anno…
Given multiple datasets with different label spaces, the goal of this work is to train a single object detector predicting over the union of all the label spaces. The practical benefits of such an object detector are obvious and significant---application-relevant categories can be picked and merged…
Heatmap regression-based models have significantly advanced the progress of facial landmark detection. However, the lack of structural constraints always generates inaccurate heatmaps resulting in poor landmark detection performance. While hierarchical structure modeling methods have been proposed t…
Recognizing the attributes of objects and their parts is central to many computer vision applications. Although great progress has been made to apply object-level recognition, recognizing the attributes of parts remains less applicable since the training data for part attributes recognition is usual…
Multi-task learning has been widely adopted in many computer vision tasks to improve overall computation efficiency or boost the performance of individual tasks, under the assumption that those tasks are correlated and complementary to each other. However, the relationships between the tasks are com…
In this work, we present a novel and effective framework to facilitate object detection with the instance-level segmentation information that is only supervised by bounding box annotation. Starting from the joint object detection and instance segmentation network, we propose to recursively estimate…