8 citations · 8 across the 8 of their papers we have counts for
9 papers
SurgSkill-Bench: A Benchmark for Multimodal Surgical Skill Assessment
Chaohui Dang, Zheheng Jiang, James Glasbey +3
Objective assessment of surgical technical skill is important for surgical training and structured feedback, but current workflows remain dependent on labor-intensive expert review…
Rarity-Aware Discrete Diffusion with Spatially Consistent Decoding for Photo-Realistic Image Super-Resolution
Ao Li, Yapeng Du, Yi Xin +5
Continuous diffusion models have become the dominant paradigm for photo-realistic image Super-Resolution (SR), but they typically formulate reconstruction as continuous signal-leve…
Real-Time Underwater Image Enhancement via Frequency-Guided Dual-Path Attention
Leshen Zhang, Ao Li, Ce Zhu
Real-time underwater image enhancement (UIE) is crucial for mobile underwater photography and autonomous robotic systems, where practical deployment typically requires low latency…
Hi-GaTA: Hierarchical Gated Temporal Aggregation Adapter for Surgical Video Report Generation
Kedi Sun, Chaohui Dang, Yue Feng +3
Automated, clinician-grade assessment reports for surgical procedures could reduce documentation burden and provide objective feedback, yet remain challenging due to the difficulty…
DRNet: All-in-One Image Restoration via Prior-Guided Dynamic Reparameterization
Ao Li, Xiaoning Liu, Sheng Li +5
All-in-one image restoration aims to handle diverse degradations within a single model. However, existing methods often suffer from three key limitations: 1) per-input computationa…
Deep Learning Empowered Super-Resolution: A Comprehensive Survey and Future Prospects
Le Zhang, Ao Li, Qibin Hou +2
Super-resolution (SR) has garnered significant attention within the computer vision community, driven by advances in deep learning (DL) techniques and the growing demand for high-q…
MobileIE: An Extremely Lightweight and Effective ConvNet for Real-Time Image Enhancement on Mobile Devices
Hailong Yan, Ao Li, Xiangtao Zhang +4
Recent advancements in deep neural networks have driven significant progress in image enhancement (IE). However, deploying deep learning models on resource-constrained platforms, s…
Towards Open-Vocabulary Video Semantic Segmentation
Xinhao Li, Yun Liu, Guolei Sun +3
Semantic segmentation in videos has been a focal point of recent research. However, existing models encounter challenges when faced with unfamiliar categories. To address this, we…
Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotations
Cheng Lei, Jie Fan, Xinran Li +4
Camouflaged Object Segmentation (COS) faces significant challenges due to the scarcity of annotated data, where meticulous pixel-level annotation is both labor-intensive and costly…