(The following topics include but are not limited to)
Track 1: Deep Learning
Basics of Deep Learning Algorithms
Deep Learning in Computer Vision
Combination of Natural Language Processing and Vision
Transfer Learning, Reinforcement Learning
Domain Adaptation
Joint Learning and Privacy Protection
Self-supervised and Unsupervised Learning
Interpretability of Deep Learning Models
Edge Computing
Track 2: Computer Vision
Big Data and Computer Vision
Biometric Recognition
Biomedical Image Analysis
Remote Sensing Images, Computational Photography
Object Detection Algorithms
Sensing and Display
Databases and Performance Analysis
Deep Learning in Computer Vision
Document Image Analysis
Character Recognition, Posture Analysis, Behavior Recognition
Visual Models
Video Analysis, Multimodal Information Processing
Vision and Language
Motion and Tracking
3D Reconstruction, Human-Computer Interaction
Track 3: Artificial Intelligence
Computer Vision
Image Classification, Object Detection, Semantic Segmentation
Image Generation, Natural Language Processing
Machine Translation, Speech Recognition
Dialogue Systems
Theoretical Model Construction
Machine Consciousness and Self-Consciousness
Understanding and Reasoning Ability
General Intelligent Systems
Ethics and Security Issues