Image, Video, and Multidimensional Signal Processing

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Point clouds (PC) are widely used for storing and transmitting 3D visual data in applications like virtual reality, autonomous driving, etc. To deal with the large size and complexity of point clouds, efficient compression methods have been developed, including MPEG standards and recent deep-learning-based approaches. To optimize and benchmark processing algorithms and codecs, point cloud quality metrics are crucial.

Associated SPS Event: IEEE ICIP 2022 Grand Challenge

KP Labs, together with ESA (European Space Agency) and partner QZ Solutions, has created an extraordinary challenge, as they will revolutionize the future of farming with the help of in-orbit processing. Maintaining farm sustainability through improving the agricultural management practices by the usage of recent advances in Earth observation and artificial intelligence has become an important issue nowadays. It can not only help farmers face the challenge of producing food at an affordable price, but can also be crucial step toward the planet-friendly agriculture.

Associated SPS Event: IEEE ICIP 2022 Grand Challenge

The perceptual quality of images/videos in the context of video surveillance has a very significant impact on high-level tasks such as object detection, identification of abnormal events, visual tracking, to name a few. Despite the development of advanced video sensors with higher resolution, the quality of the acquired video is often affected by some distortions due to the environment, encoding and storage technologies, which can only be avoided by employing of intelligent post-processing solutions.

Associated SPS Event: IEEE ICIP 2022 Grand Challenge

Intestinal parasitic infections remain among the leading causes of morbidity worldwide, especially in tropical and sub-tropical areas with more temperate climates. According to WHO, approximately 1.5 billion people, or 24% of the world’s population, are infected with soil-transmitted helminth infections (STH), and 836 million children worldwide required preventive chemotherapy for STH in 2020.

Associated SPS Event: IEEE ICIP 2022 Grand Challenge

High Dynamic Range (HDR) imaging provides the ability to capture, manipulate and display real-world lighting. This is a significant upgrade from Standard Dynamic Range (SDR) which only handles up to 255 luminance values concurrently. While capture technologies have advanced significantly over the last few years, currently available HDR capturing sensors (e.g., smartphones) only improve the dynamic range by a few stops over conventional SDR. 

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

MISP Challenge 2021 has been accepted as a Signal Processing Grand Challenge (SPGC) of ICASSP 2022!Please refer to more details of ICASSP 2022 SPGC.

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

The CORSMAL challenge focuses on the estimation of the capacity, dimensions, and mass of containers, the type, mass, and filling (percentage of the container with content), and the overall mass of the container and filling. The specific containers and fillings are unknown to the robot: the only prior is a set of object categories (drinking glasses, cups, food boxes) and a set of filling types (water, pasta, rice).

Associated SPS Event: IEEE MMSP 2021 Grand Challenge

This challenge is meant to consolidate and strengthen research efforts about image inpainting using structural guidance. We will prepare two tracks: image restoration (IR) and image editing (IE). In the IR track, we mask out random areas in an image and provide the edge maps within the areas to help restore the image.

EDICS

Technical Committee

EDICS

NOTE: The Technical Committee's EDICS list is derived from the Society's Unified EDICS list. You can view the Society's complete Unified EDICS ist and EDICS list approval process on the Unified EDICS page.

Outdoor scenes are often affected by fog, haze, rain, and smog. Poor visibility in the atmosphere is due to suspended particles. This challenge is meant to consolidate research efforts about single image recovering in adverse weather, especially hazy and rainy days. The challenge consists of two tracks: Hazy Image Recovering (HIR) and Rainy Image Recovering (RIR). In both tracks the researchers are required to recover sharp images from give degraded (hazy and rainy) inputs.

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