Multimodal representations and continual learning are two areas closely related to human intelligence. The former considers the learning of shared representation spaces where information from different modalities can be compared and integrated (we focus on cross-modal retrieval between language and visual re...
[continual cross-modal retrieval] Continual learning in cross-modal retrieval(CVPR 2021)[paper] [DER] DER:Dynamically expandable representation for class incremental learning(CVPR 2021)[paper][code] [EFT] Efficient Feature Transformations for Discriminative and Generative Continual Learning(CVPR 2021)[pape...
Continual Learning (CL) involves training a machine learning model in a sequential manner to learn new information while retaining previously learned tasks without the presence of previous training data. Although there has been significant interest in CL, most recent CL approaches in computer vision ha...
Continual Graph Learning: A Survey 2023 Arxiv Towards Label-Efficient Incremental Learning: A Survey 2023 Arxiv Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluation 2023 Arxiv How to Reuse and Compose Knowledge for a Lifetime of...
Artificial neural networks suffer from catastrophic forgetting. Unlike humans, when these networks are trained on something new, they rapidly forget what was learned before. In the brain, a mechanism thought to be important for protecting memories is the
transfer learning for the reuse of knowledge during the learning of new tasks (Section 4.3), reinforcement learning for the autonomous exploration of the environment driven by intrinsic motivation and self-supervision (Section 4.4), and multisensory systems for crossmodal lifelong learning (Section 4.5...
Considering the descriptions of similar products may be very similar, to avoid the situation that one image corresponds to multiple captions affecting the overall eval- uation of cross-modal retrieval, we save one sample for the categories owning more ...
为了解决这个问题,论文提出了一种通过持续语言学习(Continual Language Learning, CLL)来扩展VL-PTMs语言能力的方法,以便在不遭受灾难性遗忘(Catastrophic Forgetting, CF)的情况下,模型能够逐步更新其语言知识。 具体来说,论文的主要目标包括: 提出一种名为CLL-CLIP的模型,该模型基于现有的VL-PTM CLIP,通过可扩展的...
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Cross -modal image-text retrieval (CMITR) has been a high-value research topic for more than a decade. In most of the previous studies, the data for all tasks are trained as a single set. However, in reality, a more likely scenario is that the dataset has multiple tasks and trains th...