Call for Papers
We invite participants to submit their work to the workshop as full papers.
Full papers must present original research, not published elsewhere, and follow the ECCV main conference format. Papers are limited to 14 pages, including figures and tables, in the LNCS style of Springer. Additional pages containing only cited references are allowed. Please download the ECCV 2024 Author Kit for detailed formatting instructions.
Supplemental materials are also allowed, both in PDF and ZIP format. Accepted papers will be included in the conference proceedings.
Once accepted, contributions are expected to be presented in-person during the workshop.
Topics
Track 1 - From Learning to Unlearning: The Role of Privacy in Computer Vision
The first track explores the intricate interplay between learning and unlearning, and the critical role of privacy in shaping the future of Computer Vision. Topics covered include:
- Differential privacy
- Statistical and information-theoretic notions of privacy
- Privacy-preserving data sharing, anonymization, privacy of synthetic data and distillation
- Privacy attacks
- Federated and decentralized privacy-preserving algorithms
- Privacy and bias correction in generative models
- Privacy in autonomous systems
- Privacy and private learning in computer vision and natural language processing tasks
- Relations of privacy with fairness, transparency and adversarial robustness
- Machine unlearning and data-deletion
- Privacy-preserving continual learning systems
Track 2 - DeepFake Analysis and Detection
The “DeepFake Analysis and Detection” track focuses on identifying and addressing the challenges posed by deep-fake technologies. Topics include:
- Approaches for fake image detection, relying on both low-level, hand-crafted features or learnable and semantic approaches
- Partially-altered fake image detection
- GAN and Diffusion-based techniques with safety reassurance for image and video synthesis and generation
- Video Deepfake detection and multimodal approaches to deep-fake detection
- Approaches for detecting generated text and fake news, also based on multimodal analysis
- Approaches and techniques for explainable deep-fake detection
- Evaluation metrics for deep-fake generation and detection systems
We invite submissions of papers addressing any of the above topics or related areas. Accepted papers will be presented at the workshop posters session and included in the workshop proceedings. The best paper will be presented orally during the workshop.
Important Dates
- Paper Submission Deadline: July 10th, 2024 AoE
- Supplementary Material Deadline: July 10th, 2024 AoE
- Decision to Authors: August 1st, 2024 AoE
- Camera ready papers due: August, 20th 2024
- Workshop date: September, 30th 2024
Submission
All submissions will be handled electronically via CMT.