human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups authors who co-authored the same paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "SegFlow: Joint Learning for Video Object Segmentation and Optical Flow"):
  Abstract: This paper proposes an end-to-end trainable network, SegFlow, for simultaneously predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow has two branches where useful information of object segmentation and optical flow is propagated bidirectionally in a unified framework. The segmentation branch is based on a fully convolutional network, which has been proved effective in image segmentation task, and the optical flow branch takes advantage of the FlowNet model. The unified framework is trained iteratively offline to learn a generic notion, and fine-tuned online for specific objects. Extensive experiments on both the video object segmentation and optical flow datasets demonstrate that introducing optical flow improves the performance of segmentation and vice versa, against the state-of-the-art algorithms.

Includes members:
  Member "Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "First International Workshop on Video Segmentation - Panel Discussion")
  Member "Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Optical Flow with Geometric Occlusion Estimation and Fusion of Multiple Frames")
  Member "Are we ready for autonomous driving? The KITTI vision benchmark suite":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Optical Flow with Geometric Occlusion Estimation and Fusion of Multiple Frames")
  Member "Video Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting.":
    also connected through other hyperedges:
      (none)

Question: Please tell me which research area the co-authored paper (i.e., the source paper of the center hyperedge) belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science