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A Deployment-Friendly Foundational Framework for Efficient Computational Pathology
Yu Cai, Cheng Jin, Jiabo Ma +25
Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image analysis. Here, we present LitePath, a dep…
Token Merging via Spatiotemporal Information Mining for Surgical Video Understanding
Xixi Jiang, Chen Yang, Dong Zhang +3
Vision Transformer models have shown impressive effectiveness in the surgical video understanding tasks through long-range dependency modeling. However, current methods suffer from…
Towards Customized Knowledge Distillation for Chip-Level Dense Image Predictions
Dong Zhang, Pingcheng Dong, Long Chen +1
It has been revealed that efficient dense image prediction (EDIP) models designed for AI chips, trained using the knowledge distillation (KD) framework, encounter two key challenge…
Cyclic Contrastive Knowledge Transfer for Open-Vocabulary Object Detection
Chuhan Zhang, Chaoyang Zhu, Pingcheng Dong +2
In pursuit of detecting unstinted objects that extend beyond predefined categories, prior arts of open-vocabulary object detection (OVD) typically resort to pretrained vision-langu…
Memory Efficient Transformer Adapter for Dense Predictions
Dong Zhang, Rui Yan, Pingcheng Dong +1
While current Vision Transformer (ViT) adapter methods have shown promising accuracy, their inference speed is implicitly hindered by inefficient memory access operations, e.g., st…