2023 The 2nd "Guangdong-Hong Kong-Macao Greater Bay Area (Whampoa) International Algorithm Computing Competition" (hereinafter referred to as the "Contest") will officially start on July 15, 2023. The competition is open to the world. We sincerely invite college students who are innovative and have a good foundation in AI algorithm calculation examples, practitioners and makers from related companies and research institutes in the AI field to sign up for the competition!
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Innovative competition system! Top questions!
2023 The flames of war reignite!
Introduction to the competition
The Guangdong-Hong Kong-Macao Greater Bay Area (Whampoa) International Algorithm Example Competition is an international competition in the field of algorithm examples established by Pazhou Laboratory (Whampoa) in 2022, entrusted by the Huangpu District Government of Guangzhou. It aims to promote the construction of the big data and artificial intelligence algorithm ecosystem in the Greater Bay Area by giving full play to the leading and leading role of the laboratory in the field of digital economy.
The competition actively responds to the national, Guangdong-Hong Kong-Macao Greater Bay Area, Guangzhou City, and Huangpu District's digital innovation and development strategies. It stands high and is at the forefront of the world in digital economy and artificial intelligence development. , artificial intelligence, Internet of Things, cloud computing and other new-generation information technologies, aiming at solving major national needs and cutting-edge technologies in the field, focusing on smart cities, smart health, smart manufacturing, smart finance and other industries, selecting high-quality algorithms for the whole country, and gathering for the world Big data and artificial intelligence high-precision technology, attracting international high-end talents in algorithms.
Competition details
The competition innovatively set up a dual-track competition system— the arena-based track & the competition-based track , condensing ten challenging questions, providing contestants with multi-scenario, multi-field, and multi-industry content, and promoting industry-university-research Use the fusion development.
arena competition
By inviting well-known experts in the field to write questions around the frontiers of the subject, focusing on the underlying and shared technologies of digital technology, inviting "competitors" to guard the competition, and "challenging" for scholars from all over the world, in order to select the highest level algorithms.
Problem 1: Continuous Learning of Sequential Tasks
Issuer: Xi'an Jiaotong University
Competition task: Design a novel and efficient continuous learning algorithm, so that the neural network can learn new knowledge on new tasks while retaining the knowledge on historical tasks as much as possible.
Fields involved in the competition: deep learning, continuous learning
Problem 2: Discovery of new categories of images based on language enhancement
Issuer: Harbin Institute of Technology
Competition task: Design a new image category discovery algorithm based on language enhancement, take multi-label image classification as an example, and improve the performance of image new category discovery using language knowledge.
Fields involved in the competition: computer vision, natural language processing, large models, deep learning
Question 3: Efficient and Reliable Vincent Diagram Method
Issuer: Tsinghua University
Competition task: Design personalized generation of image content under specific semantics and fine generation control, and promote the development of diffusion models in model personalization and controllable generation technology.
Fields involved in the competition: large models, generative models, image processing, deep learning
Question 4: Strengthening the Comprehensive Ability of Large Language Models
Issuer: Fudan University
Competition task: Design an algorithm to improve the comprehensive ability of large models in three aspects: harmlessness, credibility, and reasoning.
Fields involved in the competition: large models, natural language processing, ethics, reasoning ability
Question 5: Cross-scene Monocular Depth Estimation
Issuer: CVTE
Competition task: Design a cross-scene monocular depth estimation algorithm that can effectively predict the depth information of another target scene from one source scene.
Fields involved in the competition: computer vision, deep learning, geometric computing
Competition system
Facing the "pain points", "difficulties" and "stuck necks" of key enterprises, key industries and key fields, seek solutions from all over the world, and choose the best algorithm.
Problem 1: 3D Reconstruction of Objects with Neural Implicit Representation
Issuer: Tencent Technology
Competition task: Based on neural implicit representation technology, design an algorithm for 3D reconstruction of objects by using photos and camera pose information for specific object types.
Fields involved in the competition: computer vision, graphics, deep learning
Question 2: Watch the video and talk
Issuer: SenseTime
Competition task: Design a dialogue model algorithm that can target videos, and conduct dialogues based on given video clips.
Fields involved in the competition: large models, computer vision, natural language processing, dialogue systems
Question 3: Roadside millimeter-wave radar calibration and target tracking
Issuer: Guangzhou Research Institute of Xidian University
Competition task: Based on the calibration file and radar point cloud data set, realize the dynamic calibration of the roadside millimeter-wave radar and the precise detection and tracking algorithm of traffic vehicles.
Fields involved in the competition: sensor technology, radar signal processing, target detection, tracking, machine learning
Question 4: Emergency multi-organ and multi-disease screening
Issuer: National Health Commission & First Hospital of Jilin University
Competition task: Design an algorithm based on emergency CT image data to realize the rapid segmentation of multiple organs, and assist in the efficient screening of multiple diseases in the emergency department.
Fields involved in the competition: medical image analysis, computer vision, deep learning
Question 5: Video Frame Interpolation in Fast Motion Scenes
Issuer: DJI Technology
Competition task: Design a video frame interpolation algorithm to achieve frame interpolation for low frame rate videos in fast motion scenes, and output high frame rates with smooth and natural motion.
Fields involved in the competition: video processing, computer vision, deep learning
Competition timeline
July 15th-September 20th: Registration for the competition begins and preliminary competition (registration is available at the preliminary competition stage)
September 21-October 6: Preliminary evaluation
After October 7: Finals and Finals Evaluation
Early to mid-November: final defense and results announcement
December: Awards Ceremony and Prize Distribution
contest registration
The competition has set up a total prize pool of 10 million, and the prize money for a single track is as high as 1 million. It will attract global outstanding talents and top teams in the field of artificial intelligence, and cultivate and build a group of innovative artificial intelligence industrial clusters with international competitiveness.
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Check out the race page and sign up
Please pay attention to the official website and official account of the competition to learn about the latest progress of the competition!