11 citations · 13 across the 12 of their papers we have counts for
13 papers
FiLM-CAM: Keyed Feature Modulation for Conditional-Access Watermarking
Yash Kulthe, Vishal Asnani, Shruti Agarwal +2
We propose FiLM-CAM; a conditional-access image watermarking approach that enforces authorized encoding, decoding, and removal through keyed feature modulation. A secret key condit…
Signpost Watermarking: Joint Optimization for Visual Watermark Coexistence
Shruti Agarwal, Vishal Asnani, John Collomosse
We present a method for training imperceptible visual watermarks to coexist with other such watermarks. Recent work has shown that independently trained image watermarking models c…
FlowMark: Mask-Guided Video Watermarking
Vishal Asnani, Shruti Agarwal, John Collomosse
We present FlowMark, a video watermarking framework guided by automatically predicted object masks. In contrast to prior region-based approaches that require user-supplied mask gui…
What Do Deepfake Benchmarks Measure? An Audit Using Frozen Self-Supervised Representations
Samuel Pagon, Yixuan Shen, Vishal Asnani +1
As deepfake generators approach perceptual indistinguishability, reliable detection becomes critical. Yet, detectors that score well on benchmarks routinely fail in the wild. A con…
TokenTrace: Multi-Concept Attribution through Watermarked Token Recovery
Li Zhang, Shruti Agarwal, John Collomosse +2
Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without attribution. While watermarking o…
Your Text Encoder Can Be An Object-Level Watermarking Controller
Naresh Kumar Devulapally, Mingzhen Huang, Vishal Asnani +3
Invisible watermarking of AI-generated images can help with copyright protection, enabling detection and identification of AI-generated media. In this work, we present a novel appr…
Proactive Schemes: A Survey of Adversarial Attacks for Social Good
Vishal Asnani, Xi Yin, Xiaoming Liu
Adversarial attacks in computer vision exploit the vulnerabilities of machine learning models by introducing subtle perturbations to input data, often leading to incorrect predicti…
ProMark: Proactive Diffusion Watermarking for Causal Attribution
Vishal Asnani, John Collomosse, Tu Bui +2
Generative AI (GenAI) is transforming creative workflows through the capability to synthesize and manipulate images via high-level prompts. Yet creatives are not well supported to…
Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network
Xiao Guo, Vishal Asnani, Sijia Liu +1
Model Parsing defines the research task of predicting hyperparameters of the generative model (GM), given a generated image as input. Since a diverse set of hyperparameters is join…
PrObeD: Proactive Object Detection Wrapper
Vishal Asnani, Abhinav Kumar, Suya You +1
Previous research in object detection focuses on various tasks, including detecting objects in generic and camouflaged images. These works are regarded as passive works for ob…
MaLP: Manipulation Localization Using a Proactive Scheme
Vishal Asnani, Xi Yin, Tal Hassner +1
Advancements in the generation quality of various Generative Models (GMs) has made it necessary to not only perform binary manipulation detection but also localize the modified pix…
Proactive Image Manipulation Detection
Vishal Asnani, Xi Yin, Tal Hassner +2
Image manipulation detection algorithms are often trained to discriminate between images manipulated with particular Generative Models (GMs) and genuine/real images, yet generalize…
Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
Vishal Asnani, Xi Yin, Tal Hassner +1
State-of-the-art (SOTA) Generative Models (GMs) can synthesize photo-realistic images that are hard for humans to distinguish from genuine photos. Identifying and understanding man…