Online Lifelong Generalized Zero-Shot Learning

Abstract

Methods proposed in the literature for zero-shot learning (ZSL) are typically suitable for offline learning and cannot continually learn from sequential streaming data. The sequential data comes in the form of tasks during training. Recently, a few attempts have been made to handle this issue and develop continual ZSL (CZSL) methods. However, these CZSL methods require clear task-boundary information between the tasks during training, which is not practically possible. This paper proposes a task-free (i.e., task-agnostic) CZSL method, which does not require any task information during continual learning. The proposed task-free CZSL method employs a variational autoencoder (VAE) for performing ZSL. To develop the CZSL method, we combine the concept of experience replay with knowledge distillation and regularization. Here, knowledge distillation is performed using the training sample's dark knowledge, which essentially helps overcome the catastrophic forgetting issue. Further, it is enabled for task-free learning using short-term memory. Finally, a classifier is trained on the synthetic features generated at the latent space of the VAE. Moreover, the experiments are conducted in a challenging and practical ZSL setup, i.e., generalized ZSL (GZSL). These experiments are conducted for two kinds of single-head continual learning settings: (i) mild setting-: task-boundary is known only during training but not during testing; (ii) strict setting-: task-boundary is not known at training, as well as testing. Experimental results on five benchmark datasets exhibit the validity of the approach for CZSL.

References in corpus (15)

• Overcoming catastrophic forgetting in neural networks
• Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
• Label-Embedding for Image Classification
• Zero-Shot Learning by Convex Combination of Semantic Embeddings
• Evaluation of Output Embeddings for Fine-Grained Image Classification
• On Tiny Episodic Memories in Continual Learning
• Continual Learning with Deep Generative Replay
• Leveraging the Invariant Side of Generative Zero-Shot Learning
• Dark Experience for General Continual Learning: a Strong, Simple Baseline
• Episode-based Prototype Generating Network for Zero-Shot Learning
• Learning a Deep Embedding Model for Zero-Shot Learning
• Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning
• Generalized Continual Zero-Shot Learning
• Generative Replay-based Continual Zero-Shot Learning
• Generative Dual Adversarial Network for Generalized Zero-shot Learning