{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T06:36:09Z","timestamp":1772087769302,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T00:00:00Z","timestamp":1771718400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We present GANimate, a lightweight method for animating talking faces that leverages recent advances in latent-space manipulation of Generative Adversarial Networks (GANs). Unlike existing approaches based on computationally intensive diffusion models, transformers, or complex 3DMM representations, which are impractical for mobile and other low-resource edge devices due to high memory and compute demands, GANimate is designed for efficient operation on low-memory, low-compute edge devices. The model operates on 2D lip landmarks extracted from standard mobile vision-sensor inputs and requires no pre-training, making it easily integrable with any lip-landmark generator. Through an optimization process in the GAN feature latent space, these landmarks act as geometric constraints to animate a static portrait, producing realistic and expressive lip movements. To maintain stability and visual coherence across frames, we employ a Kalman filter to detect and track lip landmarks during video synthesis, enabling adaptive refinement and improved temporal consistency. The result is a compact and modular framework that bridges the gap between performance and accessibility in talking face synthesis, delivering high-quality and stable animations with minimal computational overhead. GANimate represents an important step toward lifelike, real-time avatars suitable for sensor-enabled and mobile human\u2013computer interaction.<\/jats:p>","DOI":"10.3390\/s26041377","type":"journal-article","created":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T08:58:21Z","timestamp":1771837101000},"page":"1377","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GANimate: Ultra-Efficient Lip-Landmark-Driven Talking Face Animation Using a Learned Kalman Filter on GAN Feature Latent Space for Human\u2013Computer Interaction on Mobile Devices"],"prefix":"10.3390","volume":"26","author":[{"given":"Ethan","family":"Fenakel","sequence":"first","affiliation":[{"name":"School of Electrical and Computer Engineering, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben","family":"Ohayon","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Raviv","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Tel Aviv University, Tel Aviv 6997801, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xu, S., Chen, G., Guo, Y.X., Yang, J., Li, C., Zang, Z., Zhang, Y., Tong, X., and Guo, B. 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