UG2+ Workshop and Prize Challenge: Bridging the Gap between Computational Photography and Visual Recognition. Call for Papers

The 4th UG2+ Workshop and Prize Challenge: Bridging the Gap between Computational Photography and Visual Recognition.
In conjunction with CVPR 2021, June 19



Track 1: Object Detection in Poor Visibility Environments

A dependable vision system must reckon with the entire spectrum of
complex unconstrained and dynamic degraded outdoor environments. It is
highly desirable to study to what extent, and in what sense, such
challenging visual conditions can be coped with, for the goal of
achieving robust visual sensing.

Track 2: Action Recognition from Dark Videos 

Videos shot under adverse illumination are unavoidable, such as night
surveillance, and self-driving at night. It is therefore highly
desirable to explore robust methods to cope with dark scenarios. It
would be even better if such methods could utilize web videos, which
are widely available and normally shot under poor illumination.

Paper Track:

    Novel algorithms for robust object detection, segmentation or
    recognition on outdoor mobility platforms, such as UAVs, gliders,
    autonomous cars, outdoor robots, etc.

    Novel algorithms for robust object detection and/or recognition in
    the presence of one or more real-world adverse conditions, such as
    haze, rain, snow, hail, dust, underwater, low-illumination, low
    resolution, etc.

    The potential models and theories for explaining, quantifying, and
    optimizing the mutual influence between the low-level
    computational photography (image reconstruction, restoration, or
    enhancement) tasks and various high-level computer vision tasks.

    Novel physically grounded and/or explanatory models, for the
    underlying degradation and recovery processes, of real-world
    images going through complicated adverse visual conditions.

    Novel evaluation methods and metrics for image restoration and
    enhancement algorithms, with a particular emphasis on no-reference
    metrics, since for most real outdoor images with adverse visual
    conditions it is hard to obtain any clean "ground truth" to
    compare with.


Important Dates:

    Paper submission: April 5, 2021 (11:59PM PST)
    Camera ready deadline: April 16, 2021 (11:59PM PST)
    Challenge result submission: May 1, 2021 (11:59PM PST)
    Winner Announcement: May 20, 2021 (11:59PM PST)
    CVPR Workshop: June 19, 2021 (Full day)


    Raquel Urtasun (University of Toronto, Uber ATG)
    Peyman Milanfar (Google Research)
    Chelsea Finn (Stanford University, Google)
    Stanley H. Chan (Purdue University)
    Yunchao Wei (University of Technology Sydney)
    Bihan Wen (Nanyang Technological University (NTU), Singapore)
    Sifei Liu (NVIDIA)
    Shanghang Zhang (University of California, Berkeley)


    Wuyang Chen (UT Austin)
    Zhangyang Wang (UT Austin)
    Vishal M. Patel (Johns Hopkins University)
    Jiaying Liu (Peking University)
    Walter J. Scheirer (University of Notre Dame)
    Danna Gurari (UT Austin)
    Wenqi Ren (Chinese Academy of Sciences)
    Shalini De Mello (NVIDIA)
    Wenhan Yang (City University of Hong Kong)
    Yuecong Xu (Nanyang Technological University, Singapore)
    Jianxiong Yin (NVIDIA AI Tech Center)