Explore featured sessions on computer vision solutions.

See the latest vision-AI advancements in developer tools, accelerated research, smart spaces, and deploying AI at the edge. With innovation happening across many industries, you won’t want to miss all the exciting use cases and discoveries that will be presented at this GTC.

Sessions By Topic

The Latest in Intelligent Video Analytics

Vision-AI across Industries

  • Combine Multi-Camera Tracking and Footfall to Reveal the Mall Part of the Multichannel Customer Journey

    • Nicolas Bouvattier, CEO, Digeiz

    Shopping malls are under pressure with commercial rents increasing, etailers’ declining profitability, environmental issues, excessive offer (USA), retail bashing, and stock prices (REITs). Learn how multi-camera tracking addresses these retail challenges. 

  • Building Safer Public Transportation with AI-Based Video Analytics

    • Johan Barthelemy, Lecturer, University of Wollongong, AU

    Enhancing the safety and operational efficiency of the world’s public transit is a worldwide imperative. The largest transportation network in Australia, Transport for New South Wales (TfNSW), is building an AI-enabled public safety system in collaboration with University of Wollongong (UOW).

  • Software 2.0 for Industry 4.0

    • Chitra Singh, Member of Technical Staff, Drishti

    Drishti is committed  to measuring, informing, and guiding the work at assembly lines of leading automotive, medical, and industrial manufacturing facilities. Learn how to perform intelligent video analytics at scale with cutting-edge computer vision and deep learning technologies, using only video data. 

  • The Rise of Smart Infrastructure: Automating Smart Spaces with NVIDIA Metropolis and Edge AI

    • Adam Scraba, Director of Product Marketing, NVIDIA

    From retail shops to warehouses to our city streets, every space is becoming smarter because of AI-enabled vision applications. In this talk, NVIDIA will share how the world’s smartest spaces are using the NVIDIA Metropolis AI application framework to accelerate time to impact—from development to deployment and management. 

Computer Vision - Research

  • Perceive, Reason, Act: Closing the AI Loop

    • Gal Chechik, Director of AI, NVIDIA

    AI can help build systems that interact with their environment, with people, and with other agents in the real world. This poses algorithmic challenges. We’ll go over research into these challenges, focusing on modelling the high-level structure of a visual scene; using compositional structures in attribute space to learn from descriptions without any visual samples; and teaching agents new concepts without labels by using elimination to reason about their environment.

  • 3D Perception for Semantic Scene Understanding

    • Angela Dai, Professor, Technical University of Munich

    Remarkable progress has been made in recent years in 2D visual understanding leveraging deep neural networks. But they largely make predictions in the 2D domain, rather than the underlying 3D structure of the world around us. We propose to leverage geometric structural priors for 3D object perception from 2D images. We'll demonstrate that learned implicit 3D priors (e.g., view-invariance) can be used to benefit 2D semantic scene-understanding tasks.

  • 3D Reconstruction for Game Development

    • Bo Yang, Manager of Graphics and Vision Team, Tencent

    Learn about 3D object reconstruction methods for game development. We'll discuss differentiable rendering techniques for mesh and implicit surface, so a 3D object could be refined iteratively by comparing its projections with 2D images, 3D game character creation based on a few 2D images, and how we use a deep learning approach for implicit surface estimation.

  • Generalized Neural Implicits, and Humans Interacting in the 3D World

    • Gerard Pons-Moll, Professor, University of Tübingen

    The field of 3D shape representation learning and reconstruction has been revolutionized by combinations of neural networks with implicit and field representations. Discover a new class of neural implicit models that are robust, preserve detail, can be trained from raw 3D scans, and are controllable by the user.

  • Computer Vision Research at NVIDIA

    • Jan Kautz Vice President, Learning and Perception Research NVIDIA

    In this talk, learn about the latest NVIDIA-powered advances in computer vision.

Computer Vision - Image Processing

  • How AI is Helping to Reduce Risk and Enable Text-Intensive Automation

    • Oscar Guerra, Inception Program Manager, NVIDIA
    • Armin Bauer, Co-Founder and Managing Director Technology, IDnow
    • Rachel Kirkham, Executive Director, Audit Risk and Analytics, MindBridge
    • Shay Strong, VP of Analytics, ICEYE
    • Susana Latorre, Business Development Manager, Munich RE
    • Filip Graliński, Chief Data Scientist, Applica

    The adoption of AI is wide and deep, and few industries exemplify this diversity better than finance. Learn how our startups are using computer vision to make financial services more efficient, flexible, and profitable.

  • Cryo-RALIB: A Modular Library for Accelerating Alignment in Cryo-EM

    • Szu-Chi Chung, Assistant Professor, Department of Applied Mathematics at National Sun Yat-sen University

    Cryo-EM has become a rapid structure determination method that permits capture of dynamical structures of molecules in solution, as was recently demonstrated by determining the COVID-19 virus's spike protein in March 2020. We introduce Cryo-RALib, a library that expands the functionality of CUDA library used by GPU ISAC, and we connect the cryo-EM image analysis with the Python data science stack to make it easier for users to perform data analysis and visualization.

  • AI Impacts to Healthcare and Life: A Journey of Infusing and Democratizing AI to Healthcare by VinBrain

    • Steven Truong, CEO, VinBrain Joint Stock Company

    VinBrain's team will share their cutting-edge work/DrAid# (winner of 2021 ACM SIGAI Industry Award for Excellence in Artificial Intelligence), covering medical imaging use cases developed through multiple medical modalities and big data, including CXR, CT scan, MRI, etc. See how NVIDIA’s pre-trained models, Clara SDKs, Transfer Learning Toolkit, Triton, and GPUs are integrated.

  • Progressive Semantic Segmentation

    • Minh Hoai, Head of Applied Perception Group, VinAI Research

    We present MagNet, a method to segment high-resolution images without overloading GPU memory usage or losing the fine details in the output segmentation map.

  • The Future of Identity in a Post-COVID World

    • Kedar Kulkarni, CEO, HyperVerge

    Nearly $56 billion has been lost by consumers, and nearly $721 billion is expected to be lost as a result of identity fraud in 2021. COVID has further accelerated the number of cases of account takeover, identity theft, and fraudulent transactions in a remote-first world. We’ll discuss the best methods of fraud prevention, and how organizations around the world are leveraging fraud data. 

  • Addressing Generalization and Scalability Challenges in Satellite Imagery Analysis Using NVIDIA GPUs and Deep Learning

    • Philipe Ambrozio Dias, Research Associate, Oak Ridge National Laboratory (ORNL) 
    • Hsiuhan Lexie Yang, Research Scientist, Oak Ridge National Laboratory (ORNL)

    Applying deep learning models for Earth observation is hampered by major challenges. We’ll share our experiences on extracting building footprint and roads from satellite imagery datasets and using multi-GPU and multi-node HPC platforms to use NVIDIA DGX machines and ORNL’s Summit supercomputer. We’ll also discuss our research using Jetson edge-computing devices and few-shot learning for unmanned aerial survey utility pole inspection and damage assessment.

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