In this paper, we introduce a challenging yet practical setting for person re-identification
(ReID) task, named lifelong person re-identification (LReID), which aims to continuously …

Deep models have shown to be vulnerable to catastrophic forgetting, a phenomenon that
the recognition performance on old data degrades when a pre-trained model is fine-tuned …

Temporal sentence grounding aims to localize a target segment in an untrimmed video
semantically according to a given sentence query. Most previous works focus on learning …

For a long time, the local descriptors learning benefited from the use of L2 normalization,
which projects the descriptor space onto the hypersphere. However, there is no free lunch in …

Over the past decade, deep learning models have exhibited considerable advancements,
reaching or even exceeding human-level performance in a range of visual perception tasks …

Place recognition is a fundamental component of robotics, and has seen tremendous
improvements through the use of deep learning models in recent years. Networks can …

Given that the meaning of an image is rarely self-evident using traditional keyword and/or
content-based descriptions, the general goal of this study is to convert, with minimal human …

Continual learning is a research field of artificial neural networks to simulate human lifelong
learning ability. Although a surge of investigations has achieved considerable performance …

Weakly-Supervised Object Detection (WSOD) and Localization (WSOL), ie, detecting
multiple and single instances with bounding boxes in an image using image-level labels …

Referring image segmentation (RIS) is a fundamental vision-language task that intends to
segment a desired object from an image based on a given natural language expression …