2026 The 8th International Conference on Video, Signal and Image Processing (VSIP)
VSIP 2026 will
provide fertile ground for engineers and scientists from around the world to
escalate collaboratively the research frontiers within the field of video,
signal and image processing and related areas. Original and unpublished work
relevant to, but are not limited to, the following topics are hereby
solicited.
To see the information of Track Chairs, please kindly
click.
Track 1: Signal Processing and Applications
Track 2: Image Processing and Computer Vision
- Underwater Acoustic Signal
Processing
- Marine Information Processing and Analysis
- Adaptive and Nonlinear Signal Processing
- Biomedical Signal Processing and Analysis
- Speech and Audio Signal Processing
- Time-Frequency Analysis and Wavelet Transforms
- Edge Computing and Fog Computing in Signal Processing
- Sparse Signal Processing and Compressed Sensing
- Underwater Image Processing
- Marine Remote Sensing Image Processing
- Intelligent Perception of Marine Information
- Image Segmentation and Object Detection
- Deep Learning-Based Image Classification
- Medical Image Processing (e.g., MRI, CT)
- Hyperspectral and Multispectral Imaging
- Image Fusion and Panoramic Stitching
- Generative Models for Image Synthesis (GANs, Diffusion Models)
Track 3: Video Processing and Analysis
Track 4: Multimedia Systems and Applications
- Marine Target Detection Techniques
- Real-Time Video Processing Algorithms
- Marine Big Data Mining and Applications
- Video Compression and Coding Standards (e.g., H.265, AV1)
- Video Super-Resolution and Enhancement
- Motion Estimation and Object Tracking
- 3D Video Processing and Stereoscopic Vision
- Video Summarization and Retrieval
- Marine Stereoscopic Perception
Systems
- Marine Visualization and Digital Twin Systems
- Multimedia Content Analysis and Indexing
- Augmented/Virtual Reality (AR/VR) Technologies
- Multimedia in Autonomous Driving
- Haptic and Tactile Multimedia Systems
- Cloud-Based Multimedia Processing
- Multimedia Security and Watermarking Techniques
Track 5: Machine Learning & AI for Visual Data
- Self-supervised learning for
video/image data
- Few-shot learning in visual recognition
- Transformer models for visual processing
- Federated learning for distributed vision systems
- Bias and fairness in visual AI models
- Neural architecture search (NAS) for vision tasks
- AI-powered video generation and deepfakes
- Reinforcement learning for video analysis
- Edge AI for real-time visual inference
- Multimodal learning (text-image-video)
- AI in remote sensing and satellite imagery
- Robustness and adversarial attacks in vision models
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