About This Talk
Generative image and video models are rapidly entering ad-creative workflows, turning briefs into assets at scale. Yet product fidelity—accurate geometry, textures, colors, logos, and on-pack text—remains non-negotiable for customer trust, brand/legal compliance, and credible measurement. In this talk, I’ll outline a few fidelity-first approaches for steering generative video models toward product-faithful ad creative. I’ll discuss product-aware generation conditioned on a reference product, a model-agnostic post-restoration module that repairs drift from reference image(s), and a supervisory agent that automatically clips or discards distorted shots and, when needed, revises prompts or switches base models.
Presenters
Baris Gecer, Phd
Senior Applied Scientist, Amazon Ads
Baris Gecer is a Senior Applied Scientist at Amazon Ads advancing production-grade generative video for advertising and product content. A founding member of the team that built Amazon Ads Video Generator, he develops diffusion- and transformer-based pipelines for scalable, high-fidelity creation, and contributed to Nova Reel. His prior work spans photorealistic 3D face reconstruction, neural avatars, and telepresence across Huawei, FaceSoft, and Meta Reality Labs. He holds a PhD in Computer Science from Imperial College London. His research appears in CVPR, ICCV, ECCV and TPAMI and has led to granted patents. Beyond product impact, he contributes to open-source and reviews for leading computer vision venues.