Skip to main content

and
  1. No Access

    Chapter and Conference Paper

    k-means Mask Transformer

    The rise of transformers in vision tasks not only advances network backbone designs, but also starts a brand-new page to achieve end-to-end image recognition (e.g., object detection and panoptic segmentation). Or...

    Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins in Computer Vision – ECCV 2022 (2022)

  2. No Access

    Chapter and Conference Paper

    Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

    Convolution exploits locality for efficiency at a cost of missing long range context. Self-attention has been adopted to augment CNNs with non-local interactions. Recent works prove it possible to stack self-a...

    Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam in Computer Vision – ECCV 2020 (2020)

  3. No Access

    Chapter and Conference Paper

    Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

    Supervised learning in large discriminative models is a mainstay for modern computer vision. Such an approach necessitates investing in large-scale human-annotated datasets for achieving state-of-the-art resul...

    Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng in Computer Vision – ECCV 2020 (2020)