We propose a simple dynamic distillation-based approach to facilitate unlabeled images from the novel/base dataset. We impose consistency regularization by calculating predictions …
We conduct a comprehensive study on the transferability of learned representations of different contrastive approaches for linear evaluation, full-network transfer, and few-shot …
Most existing methods in weakly-supervised action localization rely on a Multiple Instance Learning (MIL) framework to predict the start and end frame of each action category in a …
We propose a Generative Adversarial Network with a dual-order attention model to detect and localize copy-move forgeries. In the generator, the firstorder attention is designed to …
It is expensive and time-consuming to annotate both action labels and temporal boundaries of videos. We propose a weakly supervised temporal action localization method that only …
Automatic algorithms for tracking and associating passengers and their divested objects at an airport security screening checkpoint would have great potential for improving …