9 citations · 13 across the 11 of their papers we have counts for
11 papers
ESAM++: Efficient Online 3D Perception on the Edge
Qin Liu, Lavisha Aggarwal, Saptarashmi Bandyopadhyay +4
Online 3D scene perception in real time is essential for robotics, AR/VR, and autonomous systems, particularly in edge computing scenarios where computational resources are limited…
Fine-Grained Action Segmentation for Renorrhaphy in Robot-Assisted Partial Nephrectomy
Jiaheng Dai, Huanrong Liu, Tailai Zhou +7
Fine-grained action segmentation during renorrhaphy in robot-assisted partial nephrectomy requires frame-level recognition of visually similar suturing gestures with variable durat…
SutureFormer: Learning Surgical Trajectories via Goal-conditioned Offline RL in Pixel Space
Huanrong Liu, Chunlin Tian, Tongyu Jia +8
Predicting surgical needle trajectories from endoscopic video is critical for robot-assisted suturing, enabling anticipatory planning, real-time guidance, and safer motion executio…
PPBoost: Progressive Prompt Boosting for Text-Driven Medical Image Segmentation
Xuchen Li, Hengrui Gu, Mohan Zhang +6
Text-prompted foundation models for medical image segmentation offer an intuitive way to delineate anatomical structures from natural language queries, but their predictions often…
LiVOS: Light Video Object Segmentation with Gated Linear Matching
Qin Liu, Jianfeng Wang, Zhengyuan Yang +4
Semi-supervised video object segmentation (VOS) has been largely driven by space-time memory (STM) networks, which store past frame features in a spatiotemporal memory to segment t…
Rethinking Interactive Image Segmentation with Low Latency, High Quality, and Diverse Prompts
Qin Liu, Jaemin Cho, Mohit Bansal +1
The goal of interactive image segmentation is to delineate specific regions within an image via visual or language prompts. Low-latency and high-quality interactive segmentation wi…
Exploring Cycle Consistency Learning in Interactive Volume Segmentation
Qin Liu, Meng Zheng, Benjamin Planche +4
Automatic medical volume segmentation often lacks clinical accuracy, necessitating further refinement. In this work, we interactively approach medical volume segmentation via two d…
SimpleClick: Interactive Image Segmentation with Simple Vision Transformers
Qin Liu, Zhenlin Xu, Gedas Bertasius +1
Click-based interactive image segmentation aims at extracting objects with a limited user clicking. A hierarchical backbone is the de-facto architecture for current methods. Recent…
PseudoClick: Interactive Image Segmentation with Click Imitation
Qin Liu, Meng Zheng, Benjamin Planche +4
The goal of click-based interactive image segmentation is to obtain precise object segmentation masks with limited user interaction, i.e., by a minimal number of user clicks. Exist…
iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images
Qin Liu, Zhenlin Xu, Yining Jiao +1
We propose iSegFormer, a memory-efficient transformer that combines a Swin transformer with a lightweight multilayer perceptron (MLP) decoder. With the efficient Swin transformer b…
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound
Shuangchi He, Zehui Lin, Xin Yang +13
Standard plane recognition plays an important role in prenatal ultrasound (US) screening. Automatically recognizing the standard plane along with the corresponding anatomical struc…