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20192024
most citedVideo Cloze Procedure for Self-Supervised Spatio-Temporal Learning

24 citations · 116 across the 19 of their papers we have counts for

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26 papers · 1 filter

cs.CV2024

DANCE: Dual-View Distribution Alignment for Dataset Condensation

Hansong Zhang, Shikun Li, Fanzhao Lin +3

Dataset condensation addresses the problem of data burden by learning a small synthetic training set that preserves essential knowledge from the larger real training set. To date,…

cs.CV20231 cited

Towards Robust Real-Time Scene Text Detection: From Semantic to Instance Representation Learning

Xugong Qin, Pengyuan Lyu, Chengquan Zhang +5

Due to the flexible representation of arbitrary-shaped scene text and simple pipeline, bottom-up segmentation-based methods begin to be mainstream in real-time scene text detection…

cs.CV2023

Masked and Permuted Implicit Context Learning for Scene Text Recognition

Xiaomeng Yang, Zhi Qiao, Jin Wei +2

Scene Text Recognition (STR) is difficult because of the variations in text styles, shapes, and backgrounds. Though the integration of linguistic information enhances models' perfo…

cs.CV2022

Beyond Instance Discrimination: Relation-aware Contrastive Self-supervised Learning

Yifei Zhang, Chang Liu, Yu Zhou +3

Contrastive self-supervised learning (CSL) based on instance discrimination typically attracts positive samples while repelling negatives to learn representations with pre-defined…

cs.CV2022

UNITS: Unsupervised Intermediate Training Stage for Scene Text Detection

Youhui Guo, Yu Zhou, Xugong Qin +2

Recent scene text detection methods are almost based on deep learning and data-driven. Synthetic data is commonly adopted for pre-training due to expensive annotation cost. However…

cs.CV20214 cited

Dense Semantic Contrast for Self-Supervised Visual Representation Learning

Xiaoni Li, Yu Zhou, Yifei Zhang +5

Self-supervised representation learning for visual pre-training has achieved remarkable success with sample (instance or pixel) discrimination and semantics discovery of instance,…