352 citations · 696 across the 14 of their papers we have counts for
14 papers
Real-World Deep Local Motion Deblurring
Haoying Li, Ziran Zhang, Tingting Jiang +3
Most existing deblurring methods focus on removing global blur caused by camera shake, while they cannot well handle local blur caused by object movements. To fill the vacancy of l…
Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
Zhuowei Li, Zihao Liu, Zhiqiang Hu +5
Medical image segmentation has been widely recognized as a pivot procedure for clinical diagnosis, analysis, and treatment planning. However, the laborious and expensive annotation…
Towards Unified Surgical Skill Assessment
Daochang Liu, Qiyue Li, Tingting Jiang +4
Surgical skills have a great influence on surgical safety and patients' well-being. Traditional assessment of surgical skills involves strenuous manual efforts, which lacks efficie…
Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training
Dingquan Li, Tingting Jiang, Ming Jiang
Video quality assessment (VQA) is an important problem in computer vision. The videos in computer vision applications are usually captured in the wild. We focus on automatically as…
Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation
Ruohua Shi, Wenyao Wang, Zhixuan Li +6
Computer vision technology is widely used in biological and medical data analysis and understanding. However, there are still two major bottlenecks in the field of cell membrane se…
Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field
Daochang Liu, Tingting Jiang, Yizhou Wang +3
Surgical skill assessment is important for surgery training and quality control. Prior works on this task largely focus on basic surgical tasks such as suturing and knot tying perf…
Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion
Daochang Liu, Yuhui Wei, Tingting Jiang +4
Surgical instrument segmentation is a key component in developing context-aware operating rooms. Existing works on this task heavily rely on the supervision of a large amount of la…
Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment
Dingquan Li, Tingting Jiang, Ming Jiang
Currently, most image quality assessment (IQA) models are supervised by the MAE or MSE loss with empirically slow convergence. It is well-known that normalization can facilitate fa…
Robust Medical Instrument Segmentation Challenge 2019
Tobias Ross, Annika Reinke, Peter M. Full +47
Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and robotic-assisted interventions. While numerous methods for detecting, segmenting and tr…
Quality Assessment of In-the-Wild Videos
Dingquan Li, Tingting Jiang, Ming Jiang
Quality assessment of in-the-wild videos is a challenging problem because of the absence of reference videos and shooting distortions. Knowledge of the human visual system can help…
Quality Assessment for Tone-Mapped HDR Images Using Multi-Scale and Multi-Layer Information
Qin He, Dingquan Li, Tingting Jiang +1
Tone mapping operators and multi-exposure fusion methods allow us to enjoy the informative contents of high dynamic range (HDR) images with standard dynamic range devices, but also…
Exploiting High-Level Semantics for No-Reference Image Quality Assessment of Realistic Blur Images
Dingquan Li, Tingting Jiang, Ming Jiang
To guarantee a satisfying Quality of Experience (QoE) for consumers, it is required to measure image quality efficiently and reliably. The neglect of the high-level semantic inform…
Harmonic Adversarial Attack Method
Wen Heng, Shuchang Zhou, Tingting Jiang
Adversarial attacks find perturbations that can fool models into misclassifying images. Previous works had successes in generating noisy/edge-rich adversarial perturbations, at the…
Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification
Daochang Liu, Tingting Jiang
Recognition of surgical gesture is crucial for surgical skill assessment and efficient surgery training. Prior works on this task are based on either variant graphical models such…