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20202025
most citedMedical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning

14 citations · 21 across the 3 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

InstaFace: Identity-Preserving Facial Editing with Single Image Inference

MD Wahiduzzaman Khan, Mingshan Jia, Xiaolin Zhang +3

Facial appearance editing is crucial for digital avatars, AR/VR, and personalized content creation, driving realistic user experiences. However, preserving identity with generative…

cs.CV202114 cited

Medical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning

Hongxu Yang, Caifeng Shan, R. Arthur Bouwman +3

Medical instrument segmentation in 3D ultrasound is essential for image-guided intervention. However, to train a successful deep neural network for instrument segmentation, a large…

cs.CV2021

Face Sketch Synthesis via Semantic-Driven Generative Adversarial Network

Xingqun Qi, Muyi Sun, Weining Wang +3

Face sketch synthesis has made significant progress with the development of deep neural networks in these years. The delicate depiction of sketch portraits facilitates a wide range…

cs.CV2020

Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition

Yi-Fan Song, Zhang Zhang, Caifeng Shan +1

One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA…

cs.CV2020

Richly Activated Graph Convolutional Network for Robust Skeleton-based Action Recognition

Yi-Fan Song, Zhang Zhang, Caifeng Shan +1

Current methods for skeleton-based human action recognition usually work with complete skeletons. However, in real scenarios, it is inevitable to capture incomplete or noisy skelet…

cs.CV2020

CANet: Context Aware Network for 3D Brain Glioma Segmentation

Zhihua Liu, Lei Tong, Long Chen +7

Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning. Based on deep neural networks, previous studies have…