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most citedSDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance

9 citations · 14 across the 6 of their papers we have counts for

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cs.CV20231 cited

CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes

Yulei Qin, Xingyu Chen, Yunhang Shen +5

Webly supervised learning has attracted increasing attention for its effectiveness in exploring publicly accessible data at scale without manual annotation. However, most existing…

cs.CV2022

FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning

Yulei Qin, Xingyu Chen, Chao Chen +5

Recently, webly supervised learning (WSL) has been studied to leverage numerous and accessible data from the Internet. Most existing methods focus on learning noise-robust models f…

cs.CV20221 cited

Frequency-Aware Self-Supervised Monocular Depth Estimation

Xingyu Chen, Thomas H. Li, Ruonan Zhang +1

We present two versatile methods to generally enhance self-supervised monocular depth estimation (MDE) models. The high generalizability of our methods is achieved by solving the f…

cs.CV2022

ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement

Dongli Tan, Jiang-Jiang Liu, Xingyu Chen +5

Modeling sparse and dense image matching within a unified functional correspondence model has recently attracted increasing research interest. However, existing efforts mainly focu…

cs.CV20213 cited

Adaptive Feature Alignment for Adversarial Training

Tao Wang, Ruixin Zhang, Xingyu Chen +6

Recent studies reveal that Convolutional Neural Networks (CNNs) are typically vulnerable to adversarial attacks, which pose a threat to security-sensitive applications. Many advers…

cs.CV20219 cited

SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance

Fu-Zhao Ou, Xingyu Chen, Ruixin Zhang +6

In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition perf…