Face Anything: 4D Face Reconstruction from Any Image Sequence (ECCV 2026)
rsasaki0109 · x · 2026-08-26
- Paper Context: Accepted as an Oral (Spotlight) paper at ECCV 2026.
- Core Capability: A unified feed-forward model for high-fidelity 4D face reconstruction and dense tracking from arbitrary image sequences.
- Technical Approach: Introduces "canonical facial point prediction," assigning each pixel a normalized facial coordinate in a shared canonical space. This transforms dense tracking and dynamic reconstruction into a single canonical reconstruction problem for temporally consistent geometry.
- Availability: Official implementation is available on GitHub with installation scripts and inference code.
More from Multimodal
- OraRL: Efficient and Scalable RL for Video MLLMs — Yunheng Li · 2026-08-26
- Seeking Fast HD MiniMax Video Generation Without Quality Loss — OkMeat6773 · 2026-08-26
- Emotional animation of girl touching sky whale generated by Google Gemini — michaelrabone · 2026-08-26
- AI generated dance video shows cool moves — No-Bookkeeper-char · 2026-08-26
- Ref2V demo: H3 model handles complex prompts in just 15 seconds — Jeffu · 2026-08-26
- GPT Image 2 technique transforms everyday photos into shape translation posters — RealJamesOfficial · 2026-08-26