We aim at incorporating explicit shape information into current 3D organ...
This paper seeks to address the dense labeling problems where a signific...
Pose transfer aims to transfer a given person into a specified posture, ...
An increasing number of public datasets have shown a marked clinical imp...
Active learning promises to improve annotation efficiency by iteratively...
Shape information is a strong and valuable prior in segmenting organs in...
Unpaired image-to-image translation aims to find a mapping between the s...
Recent advances in automated skin cancer diagnosis have yielded performa...
We propose space-aware memory queues for in-painting and detecting anoma...
The success of deep learning relies heavily on large datasets with exten...
Recently, there emerges a series of vision Transformers, which show supe...
Leveraging temporal information has been regarded as essential for devel...
Recent works of point clouds show that mulit-frame spatio-temporal model...
In this paper, we present a novel unsupervised domain adaptation (UDA)
m...
This work presents comprehensive results to detect in the early stage th...
When the input to pix2pix translation is a badly drawn sketch, the outpu...
State-of-the-art techniques in Generative Adversarial Networks (GANs) su...
Important high-level vision tasks such as human-object interaction, imag...
Although the object detection and recognition has received growing atten...
In order to track the moving objects in long range against occlusion,
in...