ADFactory: An Effective Framework for Generalizing Optical Flow With NeRF
Han Ling, Quansen Sun, Yinghui Sun, Xian Xu, Xingfeng Li
摘要
Scale-flow (Ours) Scale-flow MDFlow GMFlow RAFT 𝑥 𝑦 Self-supervised :Trained by our automated data factory Supervised: Trained by existing synthetic and real-world datasets Self-supervised: Trained by photometric loss Figure 1. Zero-Shot Generalization Results in Real World. On top is Scale-flow using our data factory scheme to estimate optical flow results in real-world scenarios. Below is a comparison with existing advanced supervised and self-supervised methods. Our method shows unprecedented accuracy and clarity. Moreover, our fully automated data factory requires no manual intervention and only utilizes photos captured by a monocular camera to train optical flow tasks.
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引用它的顶会 Paper2
- SMRABooth: Subject and Motion Representation Alignment for Customized Video GenerationXuancheng Xu, Yaning Li, Sisi You, Bing-Kun BaoCVPR 2026 · 被引用 11 次
- OCSplats: Observation Completeness Quantification and Label Noise Separation in 3DGSHan Ling, Xian Xu, Yinghui Sun, Quansen SunICCV 2025 · 被引用 2 次
它引用的顶会 Paper19
- Instant neural graphics primitives with a multiresolution hash encodingThomas Müller, Alex Evans, Christoph Schied, Alexander KellerSIGGRAPH 2022 · 被引用 4,089 次
- Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan 等CVPR 2022 · 被引用 1,603 次
- Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan 等ICCV 2023 · 被引用 799 次
- Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance FieldsDor Verbin, Peter Hedman, Ben Mildenhall, Todd E. Zickler 等CVPR 2022 · 被引用 477 次
- Learning to Estimate Hidden Motions with Global Motion AggregationShihao Jiang, Dylan Campbell, Yao Lu, Hongdong Li 等ICCV 2021 · 被引用 402 次
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