Simon Denman
8 papers · 2019–2026 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (26) 🌍 Conference Polyglot · Silver 🚀 Conference Pioneer
🔥
Unstoppable · Bronze
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(5)
Computer Vision
(4)
Deep Learning
(4)
Analysis · Computer Vision
(4)
Learning Types · Machine Learning
(4)
Artificial Intelligence
(3)
Speech & Audio
(2)
Analysis · Speech & Audio
(2)
Architectures
(2)
Core AI
(2)
Learning Paradigms
(2)
Learning Types · Deep Learning
(2)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Clinical
(1)
Keywords
memory fusion
(2)
image generation
(1)
cross-modal retrieval
(1)
domain adaptation
(1)
image retrieval
(1)
embedding learning
(1)
self-supervised learning
(1)
prompt engineering
(1)
multimodal learning
(1)
point cloud
(1)
3d vision
(1)
person re-identification
(1)
image translation
(1)
future prediction
(1)
transfer learning
(1)
object tracking
(1)
sparse regularization
(1)
generative adversarial network
(1)
text embedding
(1)
zero-shot learning
(1)
Papers
PDV: Prompt Directional Vectors for Zero-shot Composed Image Retrieval
WACV 2026
HOTFormerLoc: Hierarchical Octree Transformer for Versatile Lidar Place Recognition Across Ground and Aerial Views
CVPR 2025
Dual Memory Fusion for Multimodal Speech Emotion Recognition
Interspeech 2023
Detecting Heart Failure Through Voice Analysis using Self-Supervised Mode-Based Memory Fusion
Interspeech 2022
SESS: Saliency Enhancing with Scaling and Sliding
ECCV 2022
IGSSTRCF: Importance Guided Sparse Spatio-Temporal Regularized Correlation Filters for Tracking
WACV 2021
Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification
WACV 2020
Predicting the Future: A Jointly Learnt Model for Action Anticipation
ICCV 2019