13 papers
THEval. Evaluation Framework for Talking Head Video Generation
Nabyl Quignon, Baptiste Chopin, Yaohui Wang +1
Video generation has achieved remarkable progress, with generated videos increasingly resembling real ones. However, the rapid advance in generation has outpaced the development of…
DenVisCoM: Dense Vision Correspondence Mamba for Efficient and Real-time Optical Flow and Stereo Estimation
Tushar Anand, Maheswar Bora, Antitza Dantcheva +1
In this work, we propose a novel Mamba block DenVisCoM, as well as a novel hybrid architecture specifically tailored for accurate and real-time estimation of optical flow and dispa…
Now You See Me, Now You Don't: A Unified Framework for Expression Consistent Anonymization in Talking Head Videos
Anil Egin, Andrea Tangherloni, Antitza Dantcheva
Face video anonymization is aimed at privacy preservation while allowing for the analysis of videos in a number of computer vision downstream tasks such as expression recognition,…
AI killed the video star. Audio-driven diffusion model for expressive talking head generation
Baptiste Chopin, Tashvik Dhamija, Pranav Balaji +2
We propose Dimitra++, a novel framework for audio-driven talking head generation, streamlined to learn lip motion, facial expression, as well as head pose motion. Specifically, we…
Beyond Real versus Fake Towards Intent-Aware Video Analysis
Saurabh Atreya, Nabyl Quignon, Baptiste Chopin +2
The rapid advancement of generative models has led to increasingly realistic deepfake videos, posing significant societal and security risks. While existing detection methods focus…
Do You See What I Say? Generalizable Deepfake Detection based on Visual Speech Recognition
Maheswar Bora, Tashvik Dhamija, Shukesh Reddy +4
Deepfake generation has witnessed remarkable progress, contributing to highly realistic generated images, videos, and audio. While technically intriguing, such progress has raised…