activity
20192024
most citedProbabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration

5 citations · 12 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV20241 cited

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV20231 cited

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…

cs.CV20234 cited

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…

cs.CV20231 cited

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…