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20242026
most citedSemi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey

51 citations · 52 across the 5 of their papers we have counts for

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cs.CV2026

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2024★ 51 cited

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…

cs.CV2024

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…