1st Workshop on Trustworthiness in Computer Vision ``TWYN: Trust What You learN''

[Lorenzo BARALDI]

1st Workshop on Trustworthiness in Computer Vision ``TWYN: Trust What You learN''

ECCV 2024, Sun Sep 29th through Fri Oct 4th, 2024 at MiCo Milano

website: https://www.twyn.unimore.it/

Submission website: https://cmt3.research.microsoft.com/TWYN2024/

Scope:
In an era of rapid advancements in Artificial Intelligence, the imperative to foster Trustworthy AI has never been more critical. The first ``Trust What You learN (TWYN)'' workshop seeks to create a dynamic forum for researchers, practitioners, and industry experts to explore and advance the intersection of Trustworthy AI and DeepFake Analysis within the realm of Computer Vision. The workshop aims to delve into the multifaceted dimensions of building AI systems that are not only technically proficient but also ethical, transparent, and accountable. The dual focus on Trustworthy AI and DeepFake Analysis reflects the workshop's commitment to addressing the challenges posed by the proliferation of deep fake technologies while simultaneously promoting responsible AI practices. The workshop will include several talks presented by recognized and important scientists in these 2 fields. Explore the detailed information about our workshop structure, esteemed confirmed speakers, and what to expect on the website of the workshop.

 
Tracks:
Track 1: From Learning to Unlearning: The Role of Privacy in Computer Vision - Dive into privacy-centric topics like differential privacy, privacy attacks, Machine Unlearning and more!
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 - Address the challenges of deep-fake technologies with approaches for detection and evaluation.
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

Confirmed Keynote Speakers:
- Dimosthenis Karatzas
- Reza Shokri
- Stefano Soatto
- Rita Cucchiara
- Luisa Verdoliva

- Cristian Canton Ferrer

Paper submissions:
Paper submission instructions are available at https://www.twyn.unimore.it/call-for-papers/. Accepted papers will be presented at the workshop posters session and included in the proceedings. The submission deadline has been postponed from  the 10th to the 19th  2024 of July. Don't miss out on this opportunity to contribute to the discussion!

Dates:
Paper Submission Deadline: July 10 July 19, 2024 AoE
Supplementary Material Deadline: 10 July 19 July, 2024 AoE

Decision to Authors:  August 01 August 10, 2024

Camera ready papers due: August, 20, 2024
Workshop date: 30 September, 2024
Submission Website: https://cmt3.research.microsoft.com/TWYN2024/

Organizers:
- Marco Cotogni, Leonardo Spa
- Luigi Sabetta, Leonardo Spa
- Jacopo Bonato, Leonardo Spa
- Sara Sarto, UniMoRe
- Samuele Poppi, UniMoRe
- Lorenzo Baraldi, UniMoRe