Despite much recent progress in video-based person re-identification (re-ID), the current
state-of-the-art still suffers from common real-world challenges such as appearance …

We present the global deep video representation learning to video-based person
reidentification (re-ID) that aggregates local 3-D features across the entire video extent …

Video-based person re-identification (re-ID) aims at matching the same person across video
clips. Efficiently exploiting multi-scale fine-grained features while building the structural …

Video-based person re-identification matches video clips of people across non-overlapping
cameras. Most existing methods tackle this problem by encoding each video frame in its …

Video-based person re-identification (reID) aims to retrieve person videos with the same
identity as a query person across multiple cameras. Spatial and temporal distractors in …

Video-based person re-identification aims to associate the video clips of the same person
across multiple non-overlapping cameras. Spatial-temporal representations can provide …

Video-based person re-identification (Re-ID) aims at matching video sequences of
pedestrians across non-overlapping cameras. It is a practical yet challenging task of how to …

While video-based person re-identification (Re-ID) has drawn increasing attention and
made great progress in recent years, it is still very challenging to effectively overcome the …

Video-based person re-identification (reID) aims at matching the same person across video
clips. It is a challenging task due to the existence of redundancy among frames, newly …

Video-based person re-identification aims to match pedestrians with the consecutive video
sequences. While a rich line of work focuses solely on extracting the motion features from …