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20182022
most citedDER: Dynamically Expandable Representation for Class Incremental Learning

42 citations · 77 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV20222 cited

Generative Negative Text Replay for Continual Vision-Language Pretraining

Shipeng Yan, Lanqing Hong, Hang Xu +4

Vision-language pre-training (VLP) has attracted increasing attention recently. With a large amount of image-text pairs, VLP models trained with contrastive loss have achieved impr…

cs.CV2022

Budget-aware Few-shot Learning via Graph Convolutional Network

Shipeng Yan, Songyang Zhang, Xuming He

This paper tackles the problem of few-shot learning, which aims to learn new visual concepts from a few examples. A common problem setting in few-shot classification assumes random…

cs.CV20211 cited

An EM Framework for Online Incremental Learning of Semantic Segmentation

Shipeng Yan, Jiale Zhou, Jiangwei Xie +2

Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting. However, it remains challenging to acq…

cs.CV202142 cited

DER: Dynamically Expandable Representation for Class Incremental Learning

Shipeng Yan, Jiangwei Xie, Xuming He

We address the problem of class incremental learning, which is a core step towards achieving adaptive vision intelligence. In particular, we consider the task setting of incrementa…

cs.CV202124 cited

Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

Songyang Zhang, Zeming Li, Shipeng Yan +2

Despite the recent success of deep neural networks, it remains challenging to effectively model the long-tail class distribution in visual recognition tasks. To address this proble…

cs.CV20188 cited

FOTS: Fast Oriented Text Spotting with a Unified Network

Xuebo Liu, Ding Liang, Shi Yan +3

Incidental scene text spotting is considered one of the most difficult and valuable challenges in the document analysis community. Most existing methods treat text detection and re…