rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Computer Vision - ECCV 2022
    sub title: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXVI
  name:
    name part: Avidan, Shai.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Brostow, Gabriel.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Cissé, Moustapha.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Farinella, Giovanni Maria.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Hassner, Tal.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2022
    edition: 1st ed. 2022.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (LVI, 759 pages 252 illustrations, 247 illustrations in color)
  abstract: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23-27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
  table of contents: Contrastive Deep Supervision -- Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective -- LocVTP: Video-Text Pre-training for Temporal Localization -- Few-Shot End-to-End Object Detection via Constantly Concentrated Encoding across Heads -- Implicit Neural Representations for Image Compression -- LiP-Flow: Learning Inference-Time Priors for Codec Avatars via Normalizing Flows in Latent Space -- Learning to Drive by Watching YouTube Videos: Action-Conditioned Contrastive Policy Pretraining -- Learning Ego 3D Representation As Ray Tracing -- Static and Dynamic Concepts for Self-Supervised Video Representation Learning -- SphereFed: Hyperspherical Federated Learning -- Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning -- Posterior Refinement on Metric Matrix Improves Generalization Bound in Metric Learning -- Balancing Stability and Plasticity through Advanced Null Space in Continual Learning -- DisCo: Remedying Self-Supervised Learning on Lightweight Models with Distilled Contrastive Learning -- CoSCL: Cooperation of Small Continual Learners Is Stronger than a Big One -- Manifold Adversarial Learning for Cross-Domain 3D Shape Representation -- Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial Patches -- LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling -- On the Versatile Uses of Partial Distance Correlation in Deep Learning -- Self-Regulated Feature Learning via Teacher-Free Feature Distillation -- Balancing between Forgetting and Acquisition in Incremental Subpopulation Learning -- Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification -- DAS: Densely-Anchored Sampling for Deep Metric Learning -- Learn from All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition -- A Non-Isotropic Probabilistic Take On Proxy-Based Deep Metric Learning -- TokenMix: Rethinking Image Mixing for Data Augmentation i…
  note: edited by Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner.
  subject:
    topic: Computer vision
  subject:
    topic: Computer Vision
  classification: TA1634
  classification: 006.37
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Lecture Notes in Computer Science, 13686
  identifier: 9978-3-031-19809-0
  identifier: 9783031198090
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 221031
    record change date: 20240805183148.1
    record identifier: in00004658901