Towards Robust and Smooth 3D Multi-Person Pose Estimation from Monocular Videos in the Wild

3D pose estimation is an invaluable task in computer vision with various practical applications. Especially, 3D pose estimation for multi-person from a monocular video (3DMPPE) is particularly challenging and is still largely uncharted, far from applying to in-the-wild scenarios yet. We pose three unresolved issues with the existing methods: lack of robustness on unseen views during training, vulnerability to occlusion, and severe jittering in the output. As a remedy, we propose POTR-3D, the first realization of a sequence-to-sequence 2D-to-3D lifting model for 3DMPPE, powered by a novel geometry-aware data augmentation strategy, capable of generating unbounded data with a variety of views while caring about the ground plane and occlusions. Through extensive experiments, we verify that the proposed model and data augmentation robustly generalizes to diverse unseen views, robustly recovers the poses against heavy occlusions, and reliably generates more natural and smoother outputs. The effectiveness of our approach is verified not only by achieving the state-of-the-art performance on public benchmarks, but also by qualitative results on more challenging in-the-wild videos. Demo videos are available at https://www.youtube.com/@potr3d.

Technologies for AI-Driven Fashion Social Networking Service with E-Commerce

The rapid growth of the online fashion market brought demands for innovative fashion services and commerce platforms. With the recent success of deep learning, many applications employ AI technologies such as visual search and recommender systems to provide novel and beneficial services. In this paper, we describe applied technologies for AI-driven fashion social networking service that incorporate fashion e-commerce. In the application, people can share and browse their outfit-of-the-day (OOTD) photos, while AI analyzes them and suggests similar style OOTDs and related products. To this end, we trained deep learning based AI models for fashion and integrated them to build a fashion visual search system and a recommender system for OOTD. With aforementioned technologies, the AI-driven fashion SNS platform, iTOO, has been successfully launched.