FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow
Authors: Jihyun Lee, Junbong Jang, Donghwan Kim, Minhyuk Sung, Tae-Kyun Kim
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In the experiments, our method achieves state-of-the-art results on video-based 4D reconstruction while being computationally more efficient than the existing 3D/4D implicit shape representations. In the experiments, we validate the effectiveness of FOURIERHANDFLOW on video-based 4D hand reconstruction using Inter Hand2.6M [26] dataset, where we achieve state-of-the-art results in comparison to the existing (1) image-based 3D hand shape reconstruction methods and (2) 4D implicit shape reconstruction methods modified to take RGB hand sequences as inputs. |
| Researcher Affiliation | Academia | 1KAIST 2Imperial College London {jyun.lee, junbongjang, kdoh2522, mhsung, kimtaekyun}@kaist.ac.kr |
| Pseudocode | No | The paper includes a block diagram (Figure 2) but no formal pseudocode or algorithm block. |
| Open Source Code | Yes | Our code is available at https://github.com/jyunlee/Fourier Hand Flow. |
| Open Datasets | Yes | We use the two-hand (TH) and single-hand (SH) subsets of 30 FPS version Inter Hand2.6M [26] dataset, which contains diverse hand motions captured in RGB sequences with dense shape annotations. |
| Dataset Splits | Yes | For each subset, we use samples annotated as valid hand type and follow the train/val/test splits of the original Inter Hand2.6M dataset. The resulting TH subset contains 477K training and 4K validation sequences, and SH subset contains 656K training and 5K validation sequences. |
| Hardware Specification | No | The paper mentions computational efficiency and inference time but does not provide specific hardware details (e.g., GPU/CPU models) used for running the experiments. |
| Software Dependencies | No | The paper mentions using 'PyTorch [31] library' but does not specify its version or the versions of any other software dependencies. |
| Experiment Setup | No | The paper states 'For more details on network training and architecture, please refer to the supplementary section.', indicating that specific experimental setup details are not provided in the main text. |