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 "knowledge transfer for scene specific motion prediction"):
  Abstract: When given a single frame of the video, humans can not only interpret the content of the scene, but also they are able to forecast the near future. This ability is mostly driven by their rich prior knowledge about the visual world, both in terms of (i) the dynamics of moving agents, as well as (ii) the semantic of the scene. In this work we exploit the interplay between these two key elements to predict scene-specific motion patterns. First, we extract patch descriptors encoding the probability of moving to the adjacent patches, and the probability of being in that particular patch or changing behavior. Then, we introduce a Dynamic Bayesian Network which exploits this scene specific knowledge for trajectory prediction. Experimental results demonstrate that our method is able to accurately predict trajectories and transfer predictions to a novel scene characterized by similar elements.

Includes members:
  Member "discovery of shared semantic spaces for multiscene video query and summarization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "i vise interactive video surveillance as an edge service using unsupervised feature queries")
  Member "forecasting social navigation in crowded complex scenes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multipath multiple probabilistic anchor trajectory hypotheses for behavior prediction")
  Member "a data driven approach for tag refinement and localization in web videos":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "layout induced video representation for recognizing agent in place actions")
  Member "learning to divide and conquer for online multi target tracking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a review of tracking prediction and decision making methods for autonomous driving")
  Member "anticipating visual representations from unlabeled video":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "joint inference of groups events and human roles in aerial videos":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "era a dataset and deep learning benchmark for event recognition in aerial videos")
  Member "anticipating the future by watching unlabeled video":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transformation based adversarial video prediction on large scale data")

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)