---
res:
  bibo_abstract:
  - Object-centric learning (OCL) extracts the representation of objects with slots,
    offering an exceptional blend of flexibility and interpretability for abstracting
    low-level perceptual features. A widely adopted method within OCL is slot attention,
    which utilizes attention mechanisms to iteratively refine slot representations.
    However, a major draw-back of most object-centric models, including slot attention,
    is their reliance on predefining the number of slots. This not only necessitates
    prior knowledge of the dataset but also overlooks the inherent variability in
    the number of objects present in each instance. To overcome this fundamental limitation,
    we present a novel complexity-aware object auto-encoder framework. Within this
    framework, we introduce an adaptive slot attention (AdaSlot) mecha-nism that dynamically
    determines the optimal number of slots based on the content of the data. This
    is achieved by proposing a discrete slot sampling module that is responsible for
    selecting an appropriate number of slots from a candidate list. Furthermore, we
    introduce a masked slot decoder that suppresses unselected slots during the decoding
    process. Our framework, tested extensively on object discovery tasks with various
    datasets, shows performance matching or exceeding top fixed-slot models. Moreover,
    our analysis substantiates that our method exhibits the capability to dynamically
    adapt the slot number according to each instance's complexity, offering the potential
    for further exploration in slot attention research. Project will be available
    at https://kfan21.github.io/AdaSlot/@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Ke
      foaf_name: Fan, Ke
      foaf_surname: Fan
  - foaf_Person:
      foaf_givenName: Zechen
      foaf_name: Bai, Zechen
      foaf_surname: Bai
  - foaf_Person:
      foaf_givenName: Tianjun
      foaf_name: Xiao, Tianjun
      foaf_surname: Xiao
  - foaf_Person:
      foaf_givenName: Tong
      foaf_name: He, Tong
      foaf_surname: He
  - foaf_Person:
      foaf_givenName: Max
      foaf_name: Horn, Max
      foaf_surname: Horn
  - foaf_Person:
      foaf_givenName: Yanwei
      foaf_name: Fu, Yanwei
      foaf_surname: Fu
  - foaf_Person:
      foaf_givenName: Francesco
      foaf_name: Locatello, Francesco
      foaf_surname: Locatello
      foaf_workInfoHomepage: http://www.librecat.org/personId=26cfd52f-2483-11ee-8040-88983bcc06d4
    orcid: 0000-0002-4850-0683
  - foaf_Person:
      foaf_givenName: Zheng
      foaf_name: Zhang, Zheng
      foaf_surname: Zhang
  bibo_doi: 10.1109/cvpr52733.2024.02176
  dct_date: 2024^xs_gYear
  dct_identifier:
  - UT:001342515506043
  dct_language: eng
  dct_publisher: IEEE@
  dct_title: 'Adaptive slot attention: Object discovery with dynamic slot number@'
...