activity
20212026
most citedDINOv2: Learning Robust Visual Features without Supervision

1.1k citations · 1.3k across the 15 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2024★ 1 cited

Watermark Anything with Localized Messages

Tom Sander, Pierre Fernandez, Alain Durmus +2

Image watermarking methods are not tailored to handle small watermarked areas. This restricts applications in real-world scenarios where parts of the image may come from different…

cs.CV2024

Evaluation of Security of ML-based Watermarking: Copy and Removal Attacks

Vitaliy Kinakh, Brian Pulfer, Yury Belousov +3

The vast amounts of digital content captured from the real world or AI-generated media necessitate methods for copyright protection, traceability, or data provenance verification.…

cs.CV2023★ 1.1k cited

DINOv2: Learning Robust Visual Features without Supervision

Maxime Oquab, Timothée Darcet, Théo Moutakanni +23

The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision. Thes…

cs.CV2023★ 4 cited

The Stable Signature: Rooting Watermarks in Latent Diffusion Models

Pierre Fernandez, Guillaume Couairon, Hervé Jégou +2

Generative image modeling enables a wide range of applications but raises ethical concerns about responsible deployment. This paper introduces an active strategy combining image wa…

cs.CV2021★ 1 cited

Watermarking Images in Self-Supervised Latent Spaces

Pierre Fernandez, Alexandre Sablayrolles, Teddy Furon +2

We revisit watermarking techniques based on pre-trained deep networks, in the light of self-supervised approaches. We present a way to embed both marks and binary messages into the…