Segment anything model (SAM), an eminent universal image segmentation mo...
In this paper, we propose a bi-modality medical image synthesis approach...
Ultrasound (US) image segmentation is an active research area that requi...
Interactive medical image segmentation refers to the accurate segmentati...
Ultrasound (US) imaging is indispensable in clinical practice. To diagno...
Quantitative organ assessment is an essential step in automated abdomina...
Large language models (LLMs) have demonstrated exceptional performance a...
Existing LiDAR-inertial state estimation methods treats the state at the...
Curvilinear object segmentation is critical for many applications. Howev...
Ultrasound (US) imaging is a popular tool in clinical diagnosis, offerin...
Deep learning-based deformable registration methods have been widely
inv...
Mammogram image is important for breast cancer screening, and typically
...
Deep neural networks have been widely applied in dichotomous medical ima...
Localization of the narrowest position of the vessel and corresponding v...
Deep classifiers may encounter significant performance degradation when
...
Most existing RGB-based trackers target low frame rate benchmarks of aro...
This study aimed to solve the semantic gap and misalignment issue betwee...
Large language models (LLMs) have had a profound impact on numerous aspe...
The Segment Anything Model (SAM) is the first foundation model for gener...
Ultrasound is the primary modality to examine fetal growth during pregna...
Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials i...
The proliferation of IoT and mobile devices equipped with heterogeneous
...
Scene flow estimation, which predicts the 3D motion of scene points from...
LiDAR-inertial odometry and mapping (LIOAM), which fuses complementary
i...
As a crucial building block in vertical Federated Learning (vFL), Split
...
In this paper, we propose CGI-Stereo, a novel neural network architectur...
The fidelity of Generative Adversarial Networks (GAN) inversion is imped...
Computing John Ellipsoid is a fundamental problem in machine learning an...
Vessel segmentation is essential in many medical image applications, suc...
Clone detection is widely exploited for software vulnerability search. T...
Projection maintenance is one of the core data structure tasks. Efficien...
The GAN-based infrared and visible image fusion methods have gained
ever...
This paper proposes a novel LiDAR-inertial odometry (LIO), named SR-LIO,...
Semi-supervised learning via teacher-student network can train a model
e...
This paper reviews recent deep-learning-based matting research and conce...
Most matting researches resort to advanced semantics to achieve high-qua...
3D scene graph generation (SGG) has been of high interest in computer vi...
We present a deep reinforcement learning method of progressive view
inpa...
Medical anomaly detection is a crucial yet challenging task aiming at
re...
This paper proposes a sensor data anonymization model that is trained on...
Stereo matching is a fundamental building block for many vision and robo...
Over the past few years, the rapid development of deep learning technolo...
Glass is very common in our daily life. Existing computer vision systems...
Glass is very common in the real world. Influenced by the uncertainty ab...
Deep reinforcement learning has achieved great success in laser-based
co...
Federated learning (FL) has gained significant attention recently as a
p...
Deep segmentation models often face the failure risks when the testing i...
Standard plane (SP) localization is essential in routine clinical ultras...
Ultrasound (US) is widely used for its advantages of real-time imaging,
...
Regression learning is classic and fundamental for medical image analysi...