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Temporal Transformer Networks with Self-Supervision for Action Recognition
The temporal sequence self-supervision module we employ unprecedentedly adopts the streamlined strategy of "random batch random channel" to reverse the sequence of video frames, allowing robust extractions of motion information representation from inversed temporal dimensions and improving the generalization capability of the model.
Object-aware Feature Aggregation for Video Object Detection
As a consequence, augmenting features with such prior knowledge can effectively improve the classification and localization performance.
Co-Saliency Spatio-Temporal Interaction Network for Person Re-Identification in Videos
Person re-identification aims at identifying a certain pedestrian across non-overlapping camera networks.
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