51 citations · 52 across the 5 of their papers we have counts for
6 papers
Attention Retention for Continual Learning with Vision Transformers
Yue Lu, Xiangyu Zhou, Shizhou Zhang +3
Continual learning (CL) empowers AI systems to progressively acquire knowledge from non-stationary data streams. However, catastrophic forgetting remains a critical challenge. In t…
Multi-level Collaborative Distillation Meets Global Workspace Model: A Unified Framework for OCIL
Shibin Su, Guoqiang Liang, De Cheng +2
Online Class-Incremental Learning (OCIL) enables models to learn continuously from non-i.i.d. data streams. Since samples of the data streams can be seen only once, it is more suit…
Frequency-Guided Spatial Adaptation for Camouflaged Object Detection
Shizhou Zhang, Dexuan Kong, Yinghui Xing +5
Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that e…
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning
Yukun Li, Guansong Pang, Wei Suo +6
This paper explores the problem of continual learning (CL) of vision-language models (VLMs) in open domains, where the models need to perform continual updating and inference on a…
Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey
Lingyan Ran, Yali Li, Guoqiang Liang +1
Semantic segmentation is an important and popular research area in computer vision that focuses on classifying pixels in an image based on their semantics. However, supervised deep…
DMAT: A Dynamic Mask-Aware Transformer for Human De-occlusion
Guoqiang Liang, Jiahao Hu, Qingyue Wang +1
Human de-occlusion, which aims to infer the appearance of invisible human parts from an occluded image, has great value in many human-related tasks, such as person re-id, and inten…