Image, Video, and Multidimensional Signal Processing

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Image restoration and image enhancement are key computer vision tasks, aiming at the restoration of degraded image content, the filling in of missing information, or the needed transformation and/or manipulation to achieve a desired target (with respect to perceptual quality, contents, or performance of apps working on such images). Recent years have witnessed an increased interest from the vision and graphics communities in these fundamental topics of research. Not only has there been a constantly growing flow of related papers, but also substantial progress has been achieved.

This workshop will bring together the participants of the first Robotic Vision Challenge, a new competition targeting both the computer vision and robotics communities. The new challenge focuses on probabilistic object detection. The novelty is the probabilistic aspect for detection: A new metric evaluates both the spatial and semantic uncertainty of the object detector and segmentation system. Providing reliable uncertainty information is essential for robotics applications where actions triggered by erroneous but high-confidence perception can lead to catastrophic results.

Computer vision technologies have made impressive progress in recent years, but often at the expense of increasingly complex models needing more and more computational and storage resources. This workshop aims to improve the energy efficiency of computer vision solutions for running on systems with stringent resources, for example, mobile phones, drones, or renewable energy systems. Efficient computer vision can enable many new applications (e.g., wildlife observation) powered by ambient renewable energy (e.g., solar, vibration, and wind).

The SUMO Challenge targets the development of algorithms for comprehensive understanding of 3D indoor scenes from 360° RGB-D panoramas. The target 3D models of indoor scenes include all visible layout elements and objects complete with pose, semantic information, and texture. Algorithms submitted are evaluated at 3 levels of complexity corresponding to 3 tracks of the challenge: oriented 3D bounding boxes, oriented 3D voxel grids, and oriented 3D meshes. SUMO Challenge results will be presented at the 2019 SUMO Challenge Workshop, at CVPR.

This challenge is the 4th annual installment of International Challenge on Activity Recognition, previously called the ActivityNet Large-Scale Activity Recognition Challenge which was first hosted during CVPR 2016. It focuses on the recognition of daily life, high-level, goal-oriented activities from user-generated videos as those found in internet video portals.

Tremendous progress has been achieved in the way consumers and professionals capture, store, deliver, display and process visual content. Emerging cameras and displays allow for the capture and visualization of new and rich forms of visual data. A new activity of the JPEG Standardization Committee, called JPEG Pleno, intends to provide a standard framework to facilitate capture, representation and exchange of plenoptic content in omnidirectional, depth-enhanced, point cloud, light field, and holographic imaging modalities.

Past Members

Past Members

The following lists all the past chairs and members of the SPS Image, Video, and Multidimensional Signal Processing Technical Committee. 

*NOTE: Please scroll up/down and left/right within the Past Members window to view the full list. Also, view the full downloadable list (right-click, Save As to save file).

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