12 citations · 31 across the 16 of their papers we have counts for
17 papers
Optimised ProPainter for Video Diminished Reality Inpainting
Pengze Li, Lihao Liu, Carola-Bibiane Schönlieb +1
In this paper, part of the DREAMING Challenge - Diminished Reality for Emerging Applications in Medicine through Inpainting, we introduce a refined video inpainting technique optim…
MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
Jiuming Liu, Jinru Han, Lihao Liu +4
Point cloud videos can faithfully capture real-world spatial geometries and temporal dynamics, which are essential for enabling intelligent agents to understand the dynamically cha…
Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation
Lipei Zhang, Yanqi Cheng, Lihao Liu +2
Recent advances in deep learning have significantly improved brain tumour segmentation techniques; however, the results still lack confidence and robustness as they solely consider…
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios
Lihao Liu, Yanqi Cheng, Zhongying Deng +6
Multi-object tracking in traffic videos is a crucial research area, offering immense potential for enhancing traffic monitoring accuracy and promoting road safety measures through…
Traffic Video Object Detection using Motion Prior
Lihao Liu, Yanqi Cheng, Dongdong Chen +4
Traffic videos inherently differ from generic videos in their stationary camera setup, thus providing a strong motion prior where objects often move in a specific direction over a…
MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening
Yijun Yang, Shujun Wang, Lihao Liu +4
Breast cancer is a major cause of cancer death among women, emphasising the importance of early detection for improved treatment outcomes and quality of life. Mammography, the prim…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
Learning Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation
Jing Zou, Noémie Debroux, Lihao Liu +3
Deformable image registration is a fundamental task in medical image analysis and plays a crucial role in a wide range of clinical applications. Recently, deep learning-based appro…
Continuous U-Net: Faster, Greater and Noiseless
Chun-Wun Cheng, Christina Runkel, Lihao Liu +3
Image segmentation is a fundamental task in image analysis and clinical practice. The current state-of-the-art techniques are based on U-shape type encoder-decoder networks with sk…
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Zhongying Deng, Yanqi Chen, Lihao Liu +4
Traffic flow analysis is revolutionising traffic management. Qualifying traffic flow data, traffic control bureaus could provide drivers with real-time alerts, advising the fastest…
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Lihao Liu, Jean Prost, Lei Zhu +4
Shadows in videos are difficult to detect because of the large shadow deformation between frames. In this work, we argue that accounting for shadow deformation is essential when de…
Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness
Yanqi Cheng, Lihao Liu, Shujun Wang +3
Surgical action triplet recognition provides a better understanding of the surgical scene. This task is of high relevance as it provides the surgeon with context-aware support and…
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting
Lihao Liu, Chenyang Hong, Angelica I. Aviles-Rivero +1
We address the problem of automated nuclear segmentation, classification, and quantification from Haematoxylin and Eosin stained histology images, which is of great relevance for s…
LAMBDA: Covering the Solution Set of Black-Box Inequality by Search Space Quantization
Lihao Liu, Tianyue Feng, Xingyu Xing +1
Black-box functions are broadly used to model complex problems that provide no explicit information but the input and output. Despite existing studies of black-box function optimiz…
PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation
Lihao Liu, Zhening Huang, Pietro Liò +2
Medical image registration and segmentation are critical tasks for several clinical procedures. Manual realisation of those tasks is time-consuming and the quality is highly depend…
Contrastive Registration for Unsupervised Medical Image Segmentation
Lihao Liu, Angelica I Aviles-Rivero, Carola-Bibiane Schönlieb
Medical image segmentation is a relevant task as it serves as the first step for several diagnosis processes, thus it is indispensable in clinical usage. Whilst major success has b…
Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration
Lihao Liu, Xiaowei Hu, Lei Zhu +1
Brain image registration transforms a pair of images into one system with the matched imaging contents, which is of essential importance for brain image analysis. This paper presen…