4 accepted papers
Pseudo-labeling is a cornerstone of Unsupervised Domain Adaptation (UDA), yet the scarcity of High-Confidence Pseudo-Labeled Target Domain Samples (hcpl-tds) often leads to inaccurate cross-domain statistical alignment, causing DA failures. To address this challenge, we propose Noise Optimized Condi
Motion planning in unknown environments suffers from the limited sensing range of cameras and occlusions. Therefore, perception awareness (PA) should be fully considered to ensure flight safety. Specifically, the unknown part of the planned trajectory should be sensed in advance (visibility constrai
We propose an online tracking algorithm in which the object tracking is achieved by using subspace learning and non-negative matrix factorization (NMF) under the partile filtering framework. The object appearance is modeled by a non-negative combination of non-negative components learned from exampl…
In this paper, we cast tracking as a novel multi-task learning problem and exploit various types of visual features. We use an on-line feature selection mechanism based on the two-class variance ratio measure, applied to log likelihood distributions computed with respect to a given feature from samp…