12th International Conference on Image Processing and Pattern Recognition (IPPR 2026)
July 25 ~ 26, 2026, Toronto, Canada
Call for Papers
The 12th International Conference on Image Processing and Pattern Recognition (IPPR 2026) serves as a premier global forum for presenting the latest advances, research innovations, and emerging trends in Digital Image Processing, Computer Vision, and Pattern Recognition. As these fields continue to evolve rapidly—driven by breakthroughs in deep learning, generative models, multimodal AI, 3D vision, and advanced sensing—IPPR 2026 brings together leading researchers, engineers, and scientists from around the world to exchange ideas, foster collaboration, and showcase cutting‑edge developments.
The conference welcomes contributions that span the full spectrum of theoretical foundations, algorithmic innovations, and practical applications. From fundamental image processing techniques to next‑generation vision systems, from neural rendering and multimodal perception to medical imaging and scientific discovery, IPPR 2026 aims to highlight impactful research that pushes the boundaries of what intelligent visual systems can achieve.
Authors are invited to submit high‑quality papers that present original research results, innovative projects, survey studies, and industrial experiences demonstrating significant advances in Image Processing, Computer Vision, Pattern Recognition, and related fields. Submissions may address theoretical contributions, methodological developments, experimental evaluations, or application‑driven research. demonstrating significant advances in Image Processing, Computer Vision, Pattern Recognition, and related fields. Submissions may address theoretical contributions, methodological developments, experimental evaluations, or application driven research.
Topics of interest include, but are not limited to, the following
Image Processing and Computational Imaging
l Image Enhancement, Restoration and Super Resolution
l Image Coding, Compression and Learned Compression
l Image Segmentation, Matting and Contour Detection
l Denoising, Deblurring and Inverse Problems
l Computational Photography and Computational Optics
l HDR Imaging, Low Light Imaging and Reflectance Modeling
l PDE Based Image Processing and Variational Methods
l Physics Informed Imaging and Model Based Deep Learning
l AI Designed Optics, Coded Aperture Imaging and Diffractive Neural Networks
Computer Vision and Scene Understanding
l Object Detection, Recognition and Categorization
l Semantic, Instance and Panoptic Segmentation
l 3D Vision, 3D Reconstruction and Neural Radiance Fields (NeRFs)
l 3D Gaussian Splatting and Real Time Neural Rendering
l Multi View Geometry, Stereo Vision and Structure from Motion
l SLAM, Visual Odometry and Scene Mapping
l Vision Transformers (ViT, Swin, Mamba Vision)
l Cognitive and Biologically Inspired Vision
l Neuro Symbolic Vision and Scene Reasoning
Deep Learning, Generative Models and Foundation Models
l Deep Learning Architectures for Vision
l Generative AI (GANs, Diffusion Models, Autoregressive Models)
l Video Diffusion Models and Generative Video Synthesis
l Foundation Models for Vision and Multimodal Tasks
l Vision Language Models (CLIP, BLIP, LLaVA, VLMs)
l Vision Language Action (VLA) Models and Embodied Perception
l Self Supervised, Weakly Supervised and Semi Supervised Learning
l Continual Learning, Lifelong Learning and Domain Adaptation
l Neural Rendering, Implicit Neural Fields and Neural Light Transport
Pattern Recognition and Machine Intelligence
l Statistical Learning and Pattern Recognition
l Biometrics (Face, Iris, Gait, Fingerprint)
l Document Analysis, OCR and Handwriting Recognition
l Shape Analysis, Feature Extraction and Representation Learning
l Pattern Recognition in New Modalities (Thermal, Hyperspectral, Event Cameras)
l Knowledge Driven Vision and Semantic Reasoning
Medical, Biological and Scientific Imaging
l Medical Image Analysis (MRI, CT, Ultrasound, PET, X ray)
l Medical Foundation Models and Cross Modality Imaging
l Computational Pathology and Microscopy Foundation Models
l Radiomics, Image Guided Diagnosis and Surgical Vision
l Bioinformatics Driven Imaging and Genomic Imaging
l Vision for Materials Science, Physics and Scientific Discovery
Signal Processing, Audio and Multidimensional Data
l Audio, Speech and Acoustic Signal Processing
l Time Frequency and Time Scale Analysis
l Multidimensional Signal Processing and Tensor Methods
l Nonlinear Signals and Systems
l Sensor Array Processing and Multi Channel Signal Processing
l Distributed Source Coding and Signal Reconstruction
l Learned Signal Processing and Neural DSP
Video Processing, Analysis and Understanding
l Video Compression, Streaming and Transmission
l Video Super Resolution, Frame Interpolation and Restoration
l Video Object Tracking, Motion Analysis and Event Recognition
l Video Surveillance, Activity Recognition and Behavior Understanding
l Video Language Models and Video Text Understanding
l Video Agents and Long Horizon Temporal Reasoning
l 4D Vision, Dynamic Scene Reconstruction and Motion Fields
Remote Sensing, Earth Observation and Geospatial Vision
l Satellite and Aerial Image Processing
l Hyperspectral and Multispectral Imaging
l SAR, Radar and Sonar Signal Processing
l Geospatial Vision, Mapping and Positioning
l Foundation Models for Remote Sensing
l Environmental Monitoring and Climate Driven Vision Applications
Emerging Modalities and Advanced Sensing
l Event Based Vision and Neuromorphic Imaging
l Spiking Neural Networks for Vision
l Light Field Imaging, Plenoptic Cameras and Holography
l Thermal, Infrared and Hyperspectral Imaging
l LiDAR, Depth Sensors and Range Imaging
l Multimodal Sensor Fusion
Security, Privacy and Ethical Vision Systems
l Watermarking, Steganography and Digital Forensics
l Adversarial Attacks, Robustness and Secure Vision Models
l Deepfake Detection and Synthetic Media Forensics
l Synthetic Identity Detection and Content Provenance
l Privacy Preserving Vision and Federated Learning
l Bias, Fairness and Responsible Vision Systems
Vision Applications and Industry Use Cases
l Autonomous Driving, Robotics and Intelligent Transportation
l BEV Perception, Occupancy Networks and Trajectory Prediction
l AR/VR/MR, Metaverse and Immersive Vision Systems
l Smart Cities, IoT Vision and Edge AI Vision Systems
l Industrial Inspection, Manufacturing and Quality Control
l Retail, Agriculture, Sports Analytics and Cultural Heritage
l Vision for Digital Twins and Simulation Driven Environments
Hardware, Systems and Real Time Vision
l DSP Implementation and Embedded Vision Systems
l Hardware Acceleration (GPU, FPGA, ASIC, NPU)
l Real Time Vision Systems and Low Latency Processing
l Energy Efficient Vision and TinyML for Imaging
l Edge Computing for Vision and Distributed Vision Systems
l Vision Centric Robotics Systems
Paper Submission
Authors are invited to submit papers through the conference Submission System by May 16, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).
Selected papers from IPPR 2026, after further revisions, will be published in the special issue of the following journal.
Important Dates
l Submission Deadline: May 16, 2026
l Authors Notification: June 20, 2026
l Registration & camera - Ready Paper Due: June 27, 2026
Contact Us
Here's where you can reach us: ippr@csit2026.org or ipprconf@gmail.com
