Göm meny

Reading Group in Computer and Robot Vision

  • The purpose of this reading group is to provide an overview of the rapidly evolving computer vision literature. We meet once a week to discuss an article that all participants should read before the seminar.
  • All participants are welcome to suggest, and present articles of their choosing. The theme for articles should be computer and robot vision, with emphasis on new, high-impact conference papers (e.g. from ICCV, CVPR, RSS, or ECCV). To make best use of time, you may consider choosing an article that relates to your work, that you presumably would read anyway. If the article is well written that is also a plus.
  • You have the option to attend the seminars as part of a PhD course. You will get one 1hp for each time you present a paper, and participate in another three seminars. If you want to go for the PhD course option, let me know in advance by sending me an email with your personal number, so I can register your attendance.

  • Upcoming articles

    Article suggestions

    • Have a look at e.g. the following proceedings: ICCV'21, CVPR'22, ECCV'22, NeurIPS'21, SIGGRAPH'21, RSS'2021, ACCV'21. Some old, unused suggestions are listed below.
    • Oznan Sener and Vladlen Koltun, "Multi-task Learning as Multi-Objective Optimization", NeurIPS18 [PDF] SD201106
    • Qianqian Wang et al., "Learning Feature Descriptors using Camera Pose Supervision", ECCV20 [PDF] [GIT] SD200812
    • Ruiqu Gao et al. "Flow Contrastive Estimation of Energy-Based Models", CVPR20 [PDF] SD200630
    • M. Nakada et al., Deep Learning of Biomimetic Sensorimotor Control for Biomechanical Human Animation, TOG 2018 [PDF] SD201218
    • T. Takikawa et al., Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Surfaces ArXiv'21 [PDF] [GIT] SD210130
    • A. Dosovitskiy et al., An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, [ICLR21] SD210224
    • M. Charon et al., Emerging Properties in Self-Supervised Vision Transformers, ArXiv'21 [PDF] [blog] [GIT] SD210506

    Paper log spring 2023

    • Feb 23: Ioannis presents: Yi Zhang et al., On Predicting Generalization Using GANs, ICLR'22 [PDF] [openreview.net]
    • Mar 23: Yushan presents: Haisong Liu et al., CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation, CVPR'22 [PDF]
    • May 4: Johan presents: A. Ilyas et al., "Adversarial Examples Are Not Bugs, They Are Features", NeurIPS 2019 [NeurIPS page] [blog post]
    • June 15, 15:00: Ziliang presents: X. Liu et al. "GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection", CVPR 2023 [PDF] [GIT]

    Paper log autumn 2023

    • Oct 26: Arvi presents: A. Kirillov et al. Segment Anything, ICCV 2023 [PDF], ArXiv version: [PDF] [webpage]

    Old paper logs

Senast uppdaterad: 2023-11-28