Update model card

README.md

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 **Paper:** *ID-V2V: Identity-Preserving Video-to-Video Generation* (SIGGRAPH Asia 2026)
 
-Yuancheng Xu, Mingming He, Pablo Salamanca, Li Ma, Yash Kant, Emmett Steven, Paul Debevec, Ning Yu
+[Yuancheng Xu](https://yuancheng-xu.github.io/), [Mingming He](https://mingminghe.com/), [Pablo Salamanca](https://pablosalaman.ca/), [Li Ma](https://limacv.github.io/homepage/), [Yash Kant](https://yashkant.github.io/), [Emmett Steven](https://www.linkedin.com/in/emmettsteven), [Paul Debevec](https://www.pauldebevec.com/), [Ning Yu](https://ningyu1991.github.io/)
 
-Netflix
-
-**Code & project:** https://github.com/Eyeline-Labs/ID-V2V
+**Code:** https://github.com/Eyeline-Labs/ID-V2V
 
 ID-V2V restyles a video while preserving the original characters' identity and performance. Given a source video and a stylized keyframe (plus optional extra keyframes and a text prompt), it generates a new video whose scene, lighting, and style follow the keyframe(s), while the source subjects' identity, expressions, gaze, and motion are kept intact — a *shoot first, restyle later* workflow. It is a research artifact, released for demonstration and inspiration only.
 
-This repository hosts the two finetuned ID-V2V checkpoints. Both share the same architecture (Wan 2.1 image-to-video with VACE control).
+This repository hosts the two finetuned ID-V2V checkpoints. Both share the same architecture (Wan 2.1 image-to-video with VACE control). See the [code repository](https://github.com/Eyeline-Labs/ID-V2V) for how to use this model.
 
 ## Checkpoints