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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

ClusIR: Towards Cluster-Guided All-in-One Image Restoration

Shengkai Hu, Jiaqi Ma, Xu Zhang +3

ClusIR introduces a cluster-guided framework that learns degradation semantics via clustering and uses these cues to adaptively restore images across spatial and frequency domains.

cs.CV2026

Cross-Slice Knowledge Transfer via Masked Multi-Modal Heterogeneous Graph Contrastive Learning for Spatial Gene Expression Inference

Zhiceng Shi, Changmiao Wang, Jun Wan +1

While spatial transcriptomics (ST) has advanced our understanding of gene expression in tissue context, its high experimental cost limits its large-scale application. Predicting ST…

cs.CV2026

SpaCRD: Multimodal Deep Fusion of Histology and Spatial Transcriptomics for Cancer Region Detection

Shuailin Xue, Jun Wan, Lihua Zhang +1

Accurate detection of cancer tissue regions (CTR) enables deeper analysis of the tumor microenvironment and offers crucial insights into treatment response. Traditional CTR detecti…

cs.CV2026

Supervision-by-Hallucination-and-Transfer: A Weakly-Supervised Approach for Robust and Precise Facial Landmark Detection

Jun Wan, Yuanzhi Yao, Zhihui Lai +3

High-precision facial landmark detection (FLD) relies on high-resolution deep feature representations. However, low-resolution face images or the compression (via pooling or stride…

cs.CV2026

FGTBT: Frequency-Guided Task-Balancing Transformer for Unified Facial Landmark Detection

Jun Wan, Xinyu Xiong, Ning Chen +3

Recently, deep learning based facial landmark detection (FLD) methods have achieved considerable success. However, in challenging scenarios such as large pose variations, illuminat…