Search Results for author:
Found 16 papers, 3 papers with code
SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans
We develop a Dual-encoder Contrastive Ordinal Learning (DCOL) framework that learns the contrastive ordinal representation at global and local levels to improve the feature separability and class diversity in latent space among the AAC-24 genera.
Fast Semantic-Assisted Outlier Removal for Large-scale Point Cloud Registration
The volume of data to handle, and still elusive need to have the registration occur fully reliably and fully automatically, mean there is a need to innovate further.
Maximum Consensus by Weighted Influences of Monotone Boolean Functions
In particular, we study endowing the Boolean cube with the Bernoulli measure and performing biased (as opposed to uniform) sampling.
Generating Dataset For Large-scale 3D Facial Emotion Recognition
The main reason for the slow development of 3D FER is the unavailability of large training and large test datasets.
Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach
In this paper, we introduce a novel unsupervised learning framework that learns to directly solve robust model fitting.
Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach
In this paper, we introduce a novel unsupervised learning framework that learns to directly solve robust model fitting.
Relation Graph Network for 3D Object Detection in Point Clouds
Convolutional Neural Networks (CNNs) have emerged as a powerful strategy for most object detection tasks on 2D images.
Point Attention Network for Semantic Segmentation of 3D Point Clouds
We propose a point attention network that learns rich local shape features and their contextual correlations for 3D point cloud semantic segmentation.
Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning
The final representation is projected to a compact space and fed to a language model.
Unsupervised Deep Multi-focus Image Fusion
Convolutional neural networks have recently been used for multi-focus image fusion.
Video Description: A Survey of Methods, Datasets and Evaluation Metrics
Video description is the automatic generation of natural language sentences that describe the contents of a given video.
Deep Keyframe Detection in Human Action Videos
Detecting representative frames in videos based on human actions is quite challenging because of the combined factors of human pose in action and the background.
Learning from Millions of 3D Scans for Large-scale 3D Face Recognition
Unlike 2D photographs, 3D facial scans cannot be sourced from the web causing a bottleneck in the development of deep 3D face recognition networks and datasets.
3D Face Reconstruction from Light Field Images: A Model-free Approach
Reconstructing 3D facial geometry from a single RGB image has recently instigated wide research interest.
Shape-Based Automatic Detection of a Large Number of 3D Facial Landmarks
Our approach does not use texture and is completely shape based in order to detect landmarks that are morphologically significant.
Dense 3D Face Correspondence
A deformable model (K3DM) is constructed from the dense corresponded faces and an algorithm is proposed for morphing the K3DM to fit unseen faces.
