Overview
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Previous workshops: CVPR 2021 CVPR 2020
The rapid development in computer vision and machine learning has caused a major disruption in the retail industry. In addition to the rise of the web and online shopping, traditional markets also quickly embrace AI-related technology solutions at the physical store level. Following the introduction of computer vision to the world of retail a new set challenges emerged, such as the detection of products in crowded store displays, fine-grained classification of many visually similar classes, as well as dynamically adapting to changes in data in terms of class appearance variation over time, and new classes that may appear in the images before they are labeled in the dataset. The scene complexity, scale, class imbalance, lack of reliable supervised samples, and dynamic nature of the data, encourage solutions such as context based detection and classification, few-shot learning, uncertainty modeling and open set recognition, and so forth.
This workshop aims to present and progress the revolution that is already occuring in the word of retail and welcomes any work on relevant computer vision challenges, including but not limited to:- - Detection in densely packed scenes
- - Class imbalance and lack of labeled data. New classes introduced over time
- - Ultrafine-grained object classification: Classes are often virtually indistinguishable by visual appearance
- - Hierarchical classification: products fall into product, brand, and sub-brand hierarchies
- - Context modeling of geometric structures
- - Multi-person tracking
- - Recognition of actions such as taking/returning/examining products
Program
Challenge
AliProducts2: Large-scale Cross-Modal Product Retrieval
The growing customer demand for E-commerce is becoming more and more diversified, growing the need for methods that not only require a single modality such as product images, but also call for the usage of textual captions that describe said images. Bridging the gap between visual representation and high-level semantic concepts remains an open research topic for obtaining users' search intentions. This challenge is based on the the AliProducts2 dataset that is designed to bridge this gap. This realistic large-scale and multi-model dataset consists of ~5M image-caption pairs of ~100K fine-grained products. Challenge participants must find the top-K product candidates to match a query such as "blue men's turtleneck sweater". This challenge is a natural continuation of our previous image-only AliProducts challenge which had more than 1000 competing teams.
Challenge Important Dates
March 22, 2022, 10:00 UTC+8
Registration opens
March 31, 2022, 10:00 UTC+8
Entire training data released
May 31, 2022, 10:00 UTC+8
Registration deadline and test data released
June 19, 2022
CVPR 2022 Workshop
Invited Speakers
Organizers
For questions about the workshop please contact Ehud Barnea (ehud.barnea at gmail dot com). For questions about the challenge please see challenge pages.
Sponsors
