activity
20222026
most citedDiverse Embedding Expansion Network and Low-Light Cross-Modality Benchmark for Visible-Infrared Person Re-identification

13 citations · 45 across the 17 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

AUCH-Net: Action Unit-Based Consistency-Aware Hypergraph Network for Cross-Domain Few-Shot Facial Expression Recognition

Xinhan Qiu, Yan Yan, Rui Zhu +2

Recently, cross-domain few-shot facial expression recognition (CF-FER) has received considerable attention. However, the performance of existing CF-FER methods is still unsatisfact…

cs.CV2025

WarpGAN: Warping-Guided 3D GAN Inversion with Style-Based Novel View Inpainting

Kaitao Huang, Yan Yan, Jing-Hao Xue +1

3D GAN inversion projects a single image into the latent space of a pre-trained 3D GAN to achieve single-shot novel view synthesis, which requires visible regions with high fidelit…

cs.CV2025

FATE: A Prompt-Tuning-Based Semi-Supervised Learning Framework for Extremely Limited Labeled Data

Hezhao Liu, Yang Lu, Mengke Li +4

Semi-supervised learning (SSL) has achieved significant progress by leveraging both labeled data and unlabeled data. Existing SSL methods overlook a common real-world scenario when…

cs.CV20255 cited

Uncertainty-Aware Label Refinement on Hypergraphs for Personalized Federated Facial Expression Recognition

Hu Ding, Yan Yan, Yang Lu +2

Most facial expression recognition (FER) models are trained on large-scale expression data with centralized learning. Unfortunately, collecting a large amount of centralized expres…

cs.CV20255 cited

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations

Ruikang Chen, Yan Yan, Jing-Hao Xue +2

Automatic X-ray prohibited item detection is vital for public safety. Existing deep learning-based methods all assume that the annotations of training X-ray images are correct. How…

cs.CV2024

Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition

Hanyu Guo, Wanchuan Yu, Suzhou Que +3

In recent years, few-shot action recognition has achieved remarkable performance through spatio-temporal relation modeling. Although a wide range of spatial and temporal alignment…