The 2nd International Workshop on Real-World Computer Vision from Inputs with Limited Quality (RLQ) @ ECCV 2020

Website: [ Ссылка ]
YouTube Recordings Playlist: [ Ссылка ]

Invited Talks:
- Imaging the Invisible, Katie Bouman, CalTech
- Recognition from Low Quality Data, Rama Chellappa, Johns Hopkins University
- Designing Cameras to Detect the "Invisible": Computational Imaging for Adverse Conditions, Felix Heide, Princeton University & Algolux
- Computation + Photography: How the Mobile Phone Became a Camera, Peyman Milanfar, Google Research
- Increasing Quality of Active 3D Imaging, Srinivasa Narasimhan, CMU
- Compositional Models and Occlusion, Alan L. Yuille, Johns Hopkins University

Workshop Papers:
1. Reinforcement Learning for Improving Object Detection, IIT Madras, India
2. Collaborative Learning with Pseudo Labels for Robust Classification in the Presence of Noisy Labels, Samsung Research, South Korea
3. Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training, Atos France & Univ. Grenoble Alpes, France
4. What does CNN Shift Invariance Look Like? A Visualization Study, Columbia University & UT Austin, USA
5. Challenges from Fast Camera Motion and Image Blur: Dataset and Evaluation, Hangzhou Dianzi University & Tsinghua University, China
6. Self-Supervised Attribute-Aware Refinement Network for Low-Quality Text Recognition, GIST & Korea Culture Technology Institute, South Korea
7. Two-stage Training for Improved Classification of Poorly Localized Object Images, Object Video Labs LLC, USA
8. Face Mask Invariant End-to-End Face Recognition, Verihubs, Indonesia
9. Visible Feature Guidance for Crowd Pedestrian Detection, Algorithm Research, Aibee Inc. China
10. The Impact of Real Rain in a Vision Task, Instituto de Matem´atica e Estat´ıstica (IME) & Universidade de S˜ao Paulo (USP), Brasil
11. Hard Occlusions in Visual Object Tracking, Informatics Institute, University of Amsterdam, Netherlands

Prize Challenges:
- TOD: Tiny Object Detection Challenge
- UDC: Under-Display Camera Challenge

свернуть