Papers › FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction
FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction
Qiao Feng, Yebin Liu, Yu-Kun Lai, Jingyu Yang, Kun Li
The advent of deep learning has led to significant progress in monocular human reconstruction. However, existing representations, such as parametric models, voxel grids, meshes and implicit neural representations, have difficulties achieving high-quality results and real-time speed at the same time. In this paper, we propose Fourier Occupancy Field (FOF), a novel powerful, efficient and flexible 3D representation, for monocular real-time and accurate human reconstruction. The FOF represents a 3D object with a 2D field orthogonal to the view direction where at each 2D position the occupancy field of the object along the view direction is compactly represented with the first few terms of Fourier series, which retains the topology and neighborhood relation in the 2D domain. A FOF can be stored as a multi-channel image, which is compatible with 2D convolutional neural networks and can bridge the gap between 3D geometries and 2D images. The FOF is very flexible and extensible, e.g., parametric models can be easily integrated into a FOF as a prior to generate more robust results. Based on FOF, we design the first 30+FPS high-fidelity real-time monocular human reconstruction framework. We demonstrate the potential of FOF on both public dataset and real captured data. The code will be released for research purposes.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Human Reconstruction | CustomHumans | FOF | Chamfer Distance P-to-S | 2.079 | #2 of 8 | Archive leaderboard | report |
| 3D Human Reconstruction | CustomHumans | FOF | Chamfer Distance S-to-P | 2.644 | #2 of 8 | Archive leaderboard | report |
| 3D Human Reconstruction | CustomHumans | FOF | Normal Consistency | 0.808 | #2 of 8 | Archive leaderboard | report |
| 3D Human Reconstruction | CustomHumans | FOF | f-Score | 36.013 | #2 of 8 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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