Visual Social Relationship Recognition
نویسندگان
چکیده
منابع مشابه
Exploiting Competition Relationship for Robust Visual Recognition
Joint learning of similar tasks has been a popular trend in visual recognition and proven to be beneficial. Between-task similarity often provides useful cues, such as feature sharing, for learning visual classifiers. By contrast, the competition relationship between visual recognition tasks (e.g., content independent writer identification and handwriting recognition) remains largely under-expl...
متن کاملMachine learning based Visual Evoked Potential (VEP) Signals Recognition
Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...
متن کاملVisual Recognition by Exploiting Latent Social Links in Image Collections
Social network study has become an important topic in many research fields. Early works on social network analysis focus on real world social interactions in either human society or animal world. With the explosion of Internet data, social network researchers start to pay more attention to the tremendous amount of online social network data. There are ample space for exploring social network re...
متن کاملView dependencies in the visual recognition of social interactions
Recognizing social interactions, e.g., two people shaking hands, is important for obtaining information about other people and the surrounding social environment. Despite the visual complexity of social interactions, humans have often little difficulties to visually recognize social interactions. What is the visual representation of social interactions and the bodily visual cues that promote th...
متن کاملa computational visual neuroscience model for object recognition
in this study with the inspirations from both neuroscience and computer science, a combinatorial framework for object recognition was proposed having benefited from the advantages of both biologically-inspired hmax_s architecture model for feature extraction and extreme learning machine (elm) as a classifier. hmax model is a feed-forward hierarchical structure resembling the ventral pathway in ...
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: International Journal of Computer Vision
سال: 2020
ISSN: 0920-5691,1573-1405
DOI: 10.1007/s11263-020-01295-1