FFVO: A Feedforward Pose Decoder for Long-Horizon Visual Odometry
Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camera motion and 3D structure in one pass, pose estimation over long videos remains challenged by computational cost, long-context ambiguity, and temporal instability. To address these challenges, we propose Feedforward Visual Odometry (FFVO), a pose-specialized adaptation of joint reconstruction architectures for efficient and temporally stable camera-pose estimation. FFVO uses (i) a compact camera-token representation for computationally efficient temporal aggregation, (ii) a hierarchical local-to-global temporal decoder that mitigates geome...
| Authors | Meng-Li Shih, Shih-Yang Su, Yuliang Zou et al. |
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| Primary category | cs.CV |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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