Journal Special Issues Schedules

Journal Title Topic Due Date
IEEE SPM Special Issue on Graph Signal Processing: Foundations and Emerging Directions
  • · Theoretical foundations for GSP: Advanced models for graphs, graph signals and graph filters
  • · Nonlinear GSP
  • · Beyond graph models: Hyper-based and tensor-based GSP
  • · Statistical and robust GSP
  • · Graph topology inference, including directed graphs and applications to causality
  • · Machine learning for graph signals and geometric data
  • · Applications of SP overdirected graphs to causal inference
  • · Deep learning architectures for graph signals and geometric data
  • · Algorithmic advances, distributed computations and large-scale graphs
  • · Bioengineering, neuroscience and bioinformatics using GSP-tools
  • · Communication, power, and transportation networks using GSP-tools
  • · Finance, economics, and social networks using GSP-tools
  • · Speech, image and video processing using GSP-tools
Oct. 7th, 2019
IEEE JSTSP Data Driven Media Authentication and Forensics
  • · Learning deep features relevant to low-level forensic analysis for problems like manipulation detection, identification of the social network of origin, camera model identification, or detection of artificially generated content.
  • · Pro-active protection based on digital signatures, watermarking or other such integrity mechanisms based on machine learning.
  • · Adoption of high-level vision to automate manual analysis that exposes physical inconsistencies, such as reflections, or shadows.
  • · Media-phylogeny.
  • · Addressing counter-forensic andadversarial attacks.
  • · Forensics in the presence of in-camera processing such as HDR, video stabilization, neural imaging pipelines and advanced image fusion techniques.
  • · Reconstruction of media genealogy.
  • · Analysis and detection of imagery and videos created by new synthesis methods such as Generative models (GANs and VAEs).
  • · Registration of media and their signatures in a central repository such as blockchains.
  • · Accountability of forensics techniques.
  • · Multimedia authorship attribution.
  • · Accountable Machine-Learning techniques for Forensics.
  • · Fairness, Accountability and Transparency in ML-based Forensics Methods.
Nov. 1st, 2019
Springer IJCV Computer Vision for All Seasons: Adverse Weatherand Lighting Conditions
  • · Image de-hazing (de-fogging), image de-raining and image de-snowing
  • · Shadow removal, glare removal and reflection removal
  • · Low-light image enhancement and HDR imaging
  • · Style transfer and image translation across weather conditions, time of day, and seasons
  • · Optical flow, depth estimation(from stereo or monocular),visual odometry, etc. in bad weather and at nighttime
  • · Semantic scene understanding in bad weather and at nighttime
  • · Domain adaptation from good weather/illumination conditions to adverse conditions
  • · Learning with synthetic data for adverse weather/illumination conditions
  • · Vision algorithms invariant to illumination, time of day, weather, and seasons
  • · Datasets for bad weather and adverse lighting conditions
  • · Fusing RGB cameras with other types of sensors to handle adverse conditions
  • · New sensors and novel hardware setups for adverse weather and lighting conditions
  • · Identification of visibility conditions
  • · Robust vision algorithms against other adverse conditions
Dec. 10th, 2019

Conferences Schedules

Conference Title Due Date Conferece Date Conference Location
CVPR 2020 TBD TBD Seattle, USA
ECCV 2020 TBD TBD Edinburgh, Scotland