An unsupervised person re‐identification approach based on cross‐view distribution alignment
نویسندگان
چکیده
منابع مشابه
Person Reidentification and Recognition in Video
Person recognition has been a challenging research problem for computer vision researchers for many years. A variation of this generic problem is that of identifying the reappearance of the same person in different segments to tag people in a family video. Often we are asked to answer seemingly simple queries such as ‘how many different people are in this video? or ‘find all instances of this p...
متن کاملSubspace Distribution Alignment for Unsupervised Domain Adaptation
We propose a novel method for unsupervised domain adaptation. Traditional machine learning algorithms often fail to generalize to new input distributions, causing reduced accuracy. Domain adaptation attempts to compensate for the performance degradation by transferring and adapting source knowledge to target domain. Existing unsupervised methods project domains into a lower-dimensional space an...
متن کاملLearning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
We address the text-to-text generation problem of sentence-level paraphrasing — a phenomenon distinct from and more difficult than wordor phrase-level paraphrasing. Our approach applies multiple-sequence alignment to sentences gathered from unannotated comparable corpora: it learns a set of paraphrasing patterns represented by word lattice pairs and automatically determines how to apply these p...
متن کاملUnsupervised Person Slot Filling based on Graph Mining
Slot filling aims to extract the values (slot fillers) of specific attributes (slots types) for a given entity (query) from a largescale corpus. Slot filling remains very challenging over the past seven years. We propose a simple yet effective unsupervised approach to extract slot fillers based on the following two observations: (1) a trigger is usually a salient node relative to the query and ...
متن کاملA Multi-staged System for Efficient Visual Person Reidentification
An important field in today’s computer vision is person centric video analysis. The basis of this person centric analysis is the detection and tracking of people in video data. In many cases it is not sufficient to track people when they continuously appear in the camera’s field of view, but to also reacquire a track after a person has left a field of view and reenters it. In this paper, we int...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IET Image Processing
سال: 2021
ISSN: 1751-9659,1751-9667
DOI: 10.1049/ipr2.12256