human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "adversarial discriminative heterogeneous face recognition"
  Abstract: The gap between sensing patterns of different face modalities remains a challenging problem in heterogeneous face recognition (HFR). This paper proposes an adversarial discriminative feature learning framework to close the sensing gap via adversarial learning on both raw-pixel space and compact feature space. This framework integrates cross-spectral face hallucination and discriminative feature learning into an end-to-end adversarial network. In the pixel space, we make use of generative adversarial networks to perform cross-spectral face hallucination. An elaborate two-path model is introduced to alleviate the lack of paired images, which gives consideration to both global structures and local textures. In the feature space, an adversarial loss and a high-order variance discrepancy loss are employed to measure the global and local discrepancy between two heterogeneous distributions respectively. These two losses enhance domain-invariant feature learning and modality independent noise removing. Experimental results on three NIR-VIS databases show that our proposed approach outperforms state-of-the-art HFR methods, without requiring of complex network or large-scale training dataset.

Connected through hyperedge HE-1 (induced by source paper "relational deep feature learning for heterogeneous face recognition"):
  with members:
    - "graph neural networks a review of methods and applications"
    - "cosface large margin cosine loss for deep face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "deep face recognition a survey"
    - "videos as space time region graphs"
    - "cbam convolutional block attention module"
    - "non local neural networks"
    - "sphereface deep hypersphere embedding for face recognition"

Connected through hyperedge HE-2 (induced by source paper "dual variational generation for low shot heterogeneous face recognition"):
  with members:
    - "mode seeking generative adversarial networks for diverse image synthesis"
    - "high fidelity face manipulation with extreme pose and expression"
    - "introvae introspective variational autoencoders for photographic image synthesis"
    - "arcface additive angular margin loss for deep face recognition"
    - "delta encoder an effective sample synthesis method for few shot object recognition"
    - "synthesis of high quality visible faces from polarimetric thermal faces using generative adversarial networks"
    - "disentangled variational representation for heterogeneous face recognition"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"

Connected through hyperedge HE-3 (induced by source paper "cross resolution face recognition via prior aided face hallucination and residual knowledge distillation"):
  with members:
    - "low resolution face recognition in the wild via selective knowledge distillation"
    - "esrgan enhanced super resolution generative adversarial networks"
    - "look across elapse disentangled representation learning and photorealistic cross age face synthesis for age invariant face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "super identity convolutional neural network for face hallucination"
    - "adversarial network compression"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "cross age lfw a database for studying cross age face recognition in unconstrained environments"

Connected through hyperedge HE-4 (induced by source paper "pose agnostic cross spectral hallucination via disentangling independent factors"):
  with members:
    - "high fidelity face manipulation with extreme pose and expression"
    - "dual variational generation for low shot heterogeneous face recognition"
    - "multimodal unsupervised image to image translation"
    - "a style based generator architecture for generative adversarial networks"
    - "disentangled variational representation for heterogeneous face recognition"
    - "arbitrary style transfer in real time with adaptive instance normalization"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "perceptual losses for real time style transfer and super resolution"

Connected through hyperedge HE-5 (induced by source paper "an efficient framework for visible infrared cross modality person re identification"):
  with members:
    - "cross spectral face completion for nir vis heterogeneous face recognition"
    - "zernet convolutional neural networks on arbitrary surfaces via zernike local tangent space estimation"
    - "skipnet learning dynamic routing in convolutional networks"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "momentsnet a simple learning free method for binary image recognition"
    - "not afraid of the dark nir vis face recognition via cross spectral hallucination and low rank embedding"
    - "deep residual learning for image recognition"
    - "batch normalization accelerating deep network training by reducing internal covariate shift"

Connected through hyperedge HE-6 (induced by source paper "facial feature embedded cyclegan for vis nir translation"):
  with members:
    - "mobilenetv2 inverted residuals and linear bottlenecks"
    - "arcface additive angular margin loss for deep face recognition"
    - "mobilefacenets efficient cnns for accurate real time face verification on mobile devices"
    - "semi supervised sparse representation based classification for face recognition with insufficient labeled samples"
    - "coupled deep learning for heterogeneous face recognition"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "not afraid of the dark nir vis face recognition via cross spectral hallucination and low rank embedding"
    - "image to image translation with conditional adversarial networks"

Connected through hyperedge HE-7 (induced by source paper "lamp hq a large scale multi pose high quality database for nir vis face recognition"):
  with members:
    - "disentangled variational representation for heterogeneous face recognition"
    - "arbitrary style transfer in real time with adaptive instance normalization"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "wasserstein cnn learning invariant features for nir vis face recognition"
    - "perceptual losses for real time style transfer and super resolution"
    - "not afraid of the dark nir vis face recognition via cross spectral hallucination and low rank embedding"
    - "image to image translation with conditional adversarial networks"
    - "a light cnn for deep face representation with noisy labels"

Connected through hyperedge HE-8 (induced by source paper "synthesis of high quality visible faces from polarimetric thermal faces using generative adversarial networks"):
  with members:
    - "polarimetric thermal to visible face verification via attribute preserved synthesis"
    - "translating and segmenting multimodal medical volumes with cycle and shape consistency generative adversarial network"
    - "jointly optimize data augmentation and network training adversarial data augmentation in human pose estimation"
    - "deep cross polarimetric thermal to visible face recognition"
    - "disentangled variational representation for heterogeneous face recognition"
    - "context encoding for semantic segmentation"
    - "densely connected pyramid dehazing network"
    - "generative image inpainting with contextual attention"

Question: Please tell me which class the center node 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)