212 citations · 361 across the 30 of their papers we have counts for
8 papers · 1 filter
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…
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…
LIA-X: Interpretable Latent Portrait Animator
Yaohui Wang, Di Yang, Xinyuan Chen +3
We introduce LIA-X, a novel interpretable portrait animator designed to transfer facial dynamics from a driving video to a source portrait with fine-grained control. LIA-X is an au…
Just Dance with ! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection
Snehashis Majhi, Giacomo D'Amicantonio, Antitza Dantcheva +5
Weakly-supervised methods for video anomaly detection (VAD) are conventionally based merely on RGB spatio-temporal features, which continues to limit their reliability in real-worl…
Dimitra: 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 tr…
MVP: Multimodal Emotion Recognition based on Video and Physiological Signals
Valeriya Strizhkova, Hadi Kachmar, Hava Chaptoukaev +9
Human emotions entail a complex set of behavioral, physiological and cognitive changes. Current state-of-the-art models fuse the behavioral and physiological components using class…