Search Results for author:
Found 8 papers, 3 papers with code
Locally-Focused Face Representation for Sketch-to-Image Generation Using Noise-Induced Refinement
This paper presents a novel deep-learning framework that significantly enhances the transformation of rudimentary face sketches into high-fidelity colour images.
Task Progressive Curriculum Learning for Robust Visual Question Answering
In this work, we show for the first time that robust Visual Question Answering is attainable by simply enhancing the training strategy.
Real-time Multi-modal Object Detection and Tracking on Edge for Regulatory Compliance Monitoring
Regulatory compliance auditing across diverse industrial domains requires heightened quality assurance and traceability.
ICML 2023 Topological Deep Learning Challenge : Design and Results
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning.
OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision
To overcome the challenge in labeling RF imaging given its human incomprehensible nature, OCHID-Fi employs a cross-modality and cross-domain training process.
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
This paper is about where and how optimal transport is used in machine learning with a focus on the question of scalable optimal transport.
Topological Deep Learning: A Review of an Emerging Paradigm
The summaries obtained by these methods are principled global descriptions of multi-dimensional data whilst exhibiting stable properties such as robustness to deformation and noise.
Deep Learning for Radio-based Human Sensing: Recent Advances and Future Directions
While decade-long research has clearly demonstrated the vast potential of radio frequency (RF) for many human sensing tasks, scaling this technology to large scenarios remained problematic with conventional approaches.
