Search Results for author:
Found 10 papers, 4 papers with code
Generalized Neural Networks for Real-Time Earthquake Early Warning
Deep learning enhances earthquake monitoring capabilities by mining seismic waveforms directly.
Convolutional Embedding Makes Hierarchical Vision Transformer Stronger
Vision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias.
MobRecon: Mobile-Friendly Hand Mesh Reconstruction from Monocular Image
In this work, we propose a framework for single-view hand mesh reconstruction, which can simultaneously achieve high reconstruction accuracy, fast inference speed, and temporal coherence.
Ranked #7 on
3D Hand Pose Estimation
on DexYCB
Hand Image Understanding via Deep Multi-Task Learning
To further improve the performance of these tasks, we propose a novel Hand Image Understanding (HIU) framework to extract comprehensive information of the hand object from a single RGB image, by jointly considering the relationships between these tasks.
Real-time Earthquake Early Warning with Deep Learning: Application to the 2016 Central Apennines, Italy Earthquake Sequence
Earthquake early warning systems are required to report earthquake locations and magnitudes as quickly as possible before the damaging S wave arrival to mitigate seismic hazards.
Differentially Private Linear Regression over Fully Decentralized Datasets
This paper presents a differentially private algorithm for linear regression learning in a decentralized fashion.
Asymmetrical Vertical Federated Learning
To relax their privacy concerns about ID privacy, this paper formally proposes the notion of asymmetrical vertical federated learning and illustrates the way to protect sample IDs.
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
Neural Architecture Search (NAS) has shown great potentials in automatically designing scalable network architectures for dense image predictions.
Ranked #13 on
Semantic Segmentation
on Cityscapes test
(using extra training data)
Teddy: A System for Interactive Review Analysis
They contain a wealth of information about the opinions and experiences of users, which can help better understand consumer decisions and improve user experience with products and services.
End-to-end Hand Mesh Recovery from a Monocular RGB Image
In this paper, we present a HAnd Mesh Recovery (HAMR) framework to tackle the problem of reconstructing the full 3D mesh of a human hand from a single RGB image.
