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cs.CV2025

Revisiting Data Challenges of Computational Pathology: A Pack-based Multiple Instance Learning Training Framework

Wenhao Tang, Heng Fang, Ge Wu +2

Computational pathology (CPath) digitizes pathology slides into whole slide images (WSIs), enabling analysis for critical healthcare tasks such as cancer diagnosis and prognosis. H…

cs.CV2025

Visual Instruction Pretraining for Domain-Specific Foundation Models

Yuxuan Li, Yicheng Zhang, Wenhao Tang +4

Modern computer vision is converging on a closed loop in which perception, reasoning and generation mutually reinforce each other. However, this loop remains incomplete: the top-do…

cs.CV2025

DenoDet V2: Phase-Amplitude Cross Denoising for SAR Object Detection

Kang Ni, Minrui Zou, Yuxuan Li +4

One of the primary challenges in Synthetic Aperture Radar (SAR) object detection lies in the pervasive influence of coherent noise. As a common practice, most existing methods, whe…

cs.CV2025

Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology

Wenhao Tang, Rong Qin, Heng Fang +4

Pre-trained encoders for offline feature extraction followed by multiple instance learning (MIL) aggregators have become the dominant paradigm in computational pathology (CPath), b…

cs.CV2025

A Simple Detector with Frame Dynamics is a Strong Tracker

Chenxu Peng, Chenxu Wang, Minrui Zou +5

Infrared object tracking plays a crucial role in Anti-Unmanned Aerial Vehicle (Anti-UAV) applications. Existing trackers often depend on cropped template regions and have limited m…