ARTICLE IN PRESS Image and Vision Computing xxx (2008) xxx–xxx Contents lists available at ScienceDirect Image and Vision Computing

Citations in the corpus

Faceless Person Recognition: Privacy Implications in Social Media (2016, background): “Other related tasks are, for example, face clustering [33, 26], finding important people [34], or associating names in text to faces in images [35, 36].”
VoxCeleb: A Large-Scale Speaker Identification Dataset (2017, background): “This stage is closely related to the tracking pipeline of [34, 35], but optimised to reduce run-time given the very large number of videos to process.”
Beyond frontal faces: Improving Person Recognition using multiple cues (2015, methodology): “In [9, 29, 8], the authors proposed approach to automatically label the characters by using aligned subtitle and script text.”
Person Recognition in Personal Photo Collections (2015, background): “Other related tasks are, for instance, face clustering [9, 33], finding important people [30], or associating names in text to faces in images [13, 14].”
Fisher Vector Faces in the Wild (2013, methodology): “[9] proposed pictorial structures, Dantone et al.”
Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor (2015, unknown): “(e.g. A1 = {d1, d10, d23}) during the time of presence; i.e. (V T1 ,DT1 )→ A.”
Ieee Transactions on Pattern Analysis an Machine Intelligence Structured Learning of Human Interactions in Tv Shows (methodology): “Here, we use the KLT [27], [28] method of Everingham et al. [29] as well as the clique partitioning of [2] to join broken tracks; third, tracks are filtered to remove false positives using a linear classifier similar to that of [3]; and finally, head pose is computed in each frame so (a) (b) Fig.”
Person Recognition in Personal Photo Collections (2017, background): “(1) closed world identification: given a single test image (probe), who is this person among the identities that are among the training identities (gallery set)? (2) Open world recognition [32] (§B, Appendix): given a singe test image (probe), is this person among the training identities (gallery se”
It ’ s in the bag : Stronger supervision for automated face labelling (2015, methodology): “This topic has received plenty of attention in the community and papers have investigated the problem under various assumptions on the available information [2, 3, 5, 4, 6, 8, 9, 12, 17, 18, 20, 22, 24].”
Search-and-replace editing for personal photo collections (2010, methodology): “To match faces, we use the proposed pixel-based face descriptor [11].”
Face recognition in unconstrained videos with matched background similarity (2011, background): “More recently [3, 14] focus on the task of aligning subtitle information with faces appearing in TV shows.”
“Who are you?” - Learning person specific classifiers from video (2009, background): “Indeed, others [2, 9, 12] that have improved on the classification per-”
Cross-Modal Supervision for Learning Active Speaker Detection in Video (2016, methodology): “Traditionally, visual active speaker detection has been done using lip motion detection [1,2,3,4].”
Ava Active Speaker: An Audio-Visual Dataset for Active Speaker Detection (2019, background): “…has multiple applications, such as in interactive systems that identify the speaker and per-sonalize responses [44, 45], in speech transcription, speaker diarization and speech enhancement systems [1, 9, 12, 26, 41, 42], and for tracking storylines and characters in narrative content [10, 14].”