10 papers
AGQ: Action-Guided Ultra-Low-Bit Quantization for Vision-Language-Action Models
Xuhong Qiu, Zhuoyu Wu, Qiawei Zheng +3
Vision-language-action (VLA) models enable robots to perform tasks specified through natural-language instructions, but their large weight footprint challenges deployment on memory…
Lightweight Polyp Segmentation via a Gain-Aware Prediction-Space Recursive Controller
Jiachi Zhang, Zhuoyu Wu, Quanjun Wang +2
While lightweight polyp segmentation is highly desirable for low-cost deployment, reported performance gains often stem from upgraded backbone encoders, complex decoders, or heavy…
RIGS-Refiner: Risk-Guided Recursive Refinement in Prediction Space for Colonoscopy Polyp Segmentation
Jiachi Zhang, Zhuoyu Wu, Wenqi Fang
Post-refinement can improve colonoscopy segmentation after host inference, but many designs still rely on extra correction heads or multi-stage pipelines with non-negligible parame…
DepthPolyp: Pseudo-Depth Guided Lightweight Segmentation for Real-Time Colonoscopy
Zhuoyu Wu, Wenhui Ou, Lexi Zhang +5
Accurate polyp segmentation in colonoscopy is essential for early colorectal cancer detection, yet real-world clinical environments pose persistent challenges such as motion blur,…
RoiMAM: Region-of-Interest Medical Attention Model for Efficient Vision-Language Understanding
Jiayan Yang, Zhuoyu Wu, Wenqi Fang
Vision-Language Models (VLMs) facilitate medical visual question answering (MedVQA) by jointly interpreting images and text. However, existing models typically depend on large arch…
RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering
Zhuoyu Wu, Wenhui Ou, Pei-Sze Tan +3
Retrieving procedure-oriented evidence from materials science papers is difficult because key synthesis details are often scattered across long, context-heavy documents and are not…
Improving Infinitely Deep Bayesian Neural Networks with Nesterov's Accelerated Gradient Method
Chenxu Yu, Wenqi Fang
As a representative continuous-depth neural network approach, stochastic differential equation (SDE)-based Bayesian neural networks (BNNs) have attracted considerable attention due…
EndoCaver: Handling Fog, Blur and Glare in Endoscopic Images via Joint Deblurring-Segmentation
Zhuoyu Wu, Wenhui Ou, Pei-Sze Tan +4
Endoscopic image analysis is vital for colorectal cancer screening, yet real-world conditions often suffer from lens fogging, motion blur, and specular highlights, which severely c…
RT-Focuser: A Real-Time Lightweight Model for Edge-side Image Deblurring
Zhuoyu Wu, Wenhui Ou, Qiawei Zheng +6
Motion blur caused by camera or object movement severely degrades image quality and poses challenges for real-time applications such as autonomous driving, UAV perception, and medi…
Constants of motion network revisited
Wenqi Fang, Chao Chen, Yongkui Yang +1
Discovering constants of motion is meaningful in helping understand the dynamical systems, but inevitably needs proficient mathematical skills and keen analytical capabilities. Wit…