human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "detecting human object interactions via functional generalization"):
  Abstract: We present an approach for detecting human-object interactions (HOIs) in images, based on the idea that humans interact with functionally similar objects in a similar manner. The proposed model is simple and efficiently uses the data, visual features of the human, relative spatial orientation of the human and the object, and the knowledge that functionally similar objects take part in similar interactions with humans. We provide extensive experimental validation for our approach and demonstrate state-of-the-art results for HOI detection. On the HICO-Det dataset our method achieves a gain of over 2.5% absolute points in mean average precision (mAP) over state-of-the-art. We also show that our approach leads to significant performance gains for zero-shot HOI detection in the seen object setting. We further demonstrate that using a generic object detector, our model can generalize to interactions involving previously unseen objects.

Includes members:
  Member "zero shot object detection learning to simultaneously recognize and localize novel concepts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "incremental few shot object detection")
  Member "interact as you intend intention driven human object interaction detection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "pose aware multi level feature network for human object interaction detection")
  Member "detecting unseen visual relations using analogies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "classifying all interacting pairs in a single shot")
  Member "women also snowboard overcoming bias in captioning models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unbiased scene graph generation from biased training")
  Member "ican instance centric attention network for human object interaction detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "visual semantic graph attention networks for human object interaction detection")
  Member "zero shot object detection by hybrid region embedding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "any shot object detection")
  Member "no frills human object interaction detection factorization layout encodings and training techniques":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "visual semantic graph attention networks for human object interaction detection")
  Member "detecting visual relationships using box attention":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vsgnet spatial attention network for detecting human object interactions using graph convolutions")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)