NEC Labs America Team Attending CVPR 2024 in Seattle

June 11, 2024||inEvents|tagsCVF, IEEE, bingbing zhuang, computer vision, cvpr, deep patel, di liu, erik kruus, james m moore, junhui zhao, martin renqiang min, media analytics, sarper ozharar, shanlin sun, shaobo han, ting wang, yangmin ding, yue tian, zhuocheng jiang

Our team will be attending CVPR 2024 (The IEEE /CVF Conference on Computer Vision & Pattern Recognition) from June 17-21! See you there at the NEC Labs America Booth 1716! Stay tuned for more information about our participation.

CVPR2024

Weakly-Supervised Temporal Action Localization with Multi-Modal Plateau Transformers Poster

Workshop: 3rd Workshop on Learning with Limited Labelled Data for Image and Video Understanding

Authors: Xin Hu, Tulane University; Kai Li, NEC Labs America; Deep Patel, NEC Labs America (Presenting); Erik Kruus, NEC Labs America; Martin Renqiang Min, NEC Labs America and Zhengming Ding, Tulane University

Poster timing: Tuesday, June 18, 2024

Deep Patel NEC Labs America

Deep Patel, NEC Labs America (Presenting)

Seeing the Vibration from Fiber-Optic Cable: Rain Intensity Monitoring using Deep Frequency Filtering Poster

Workshop: 20th Workshop on Perception Beyond the Visible Spectrum

Authors: Zhuocheng Jiang (Presenter), Yangmin Ding, Junhui Zhao, Yue Tian, Shaobo Han, Sarper Ozharar, Ting Wang and James M. Moore

Poster timing: Tuesday, June 18, 2024

Zhuocheng Jiang NEC Labs America

Zhuocheng Jiang, NEC Labs America (Presenter)

Data-Driven Autonomous Driving Simulation (DDASD) Workshop

Abstract: Real-world on-road testing of autonomous vehicles can be expensive or dangerous, making simulation a crucial tool to accelerate the development of safe autonomous driving (AD), a technology with enormous real-world impact. However, to minimise the sim-to-real gap, good agent behaviour models and sensor/perception imitation are paramount. A recent surge in published papers in this fast-growing field has led to a lot of progress, but several fundamental questions remain unanswered, for example regarding the fidelity and diversity of generative behaviour and perception models, generation of realistic controllable scenes at scale and the safety assessment of the simulation toolchain. In this workshop, our goal is to bring together practitioners and researchers from all areas of AD simulation and to discuss pressing challenges, recent breakthroughs and future directions.

Presenters: Our Intern Shanlin Sun will have an oral presentation at the workshop.

More Information:https://agents4ad.github.io/

Date: Tuesday, June 18, 2024

Shanlin Sun

Shanlin Sun (Presenter)

S’More: Instantaneous Perception of Moving Objects in 3D

Presenters: Bingbing Zhuang, Intern Di Liu

Date: Friday, June 21, 2024 from 10:30am-12pm

Bingbing Zhuang NEC Labs

Bingbing Zhuang, NEC Labs America (Presenter)

S'More Instantaneous Perception of Moving Objects in 3D

LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenes

Presenters: Bingbing Zhuang, Ziyu Jiang, Intern Shanlin Sun

Date: Friday, June 21 from 10:30am-12pm

Bingbing Zhuang NEC Labs

Bingbing Zhuang, NEC Labs America (Presenter)

Ziyu Jiang

Ziyu Jiang, NEC Labs America (Presenter)

LidaRF Delving into Lidar for Neural Radiance Field on Street Scenes

Presented Papers

Taming Self-Training for Open-Vocabulary Object Detection

/CVPR2024

Recent studies have shown promising performance in open-vocabulary object detection (OVD) by utilizing pseudo labels (PLs) from pretrained vision and language models (VLMs). However, teacher-student self-training, a powerful and widely used paradigm to leverage PLs, is rarely explored for OVD.

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AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving

/CVPR2024

Autonomous vehicle (AV) systems rely on robust perception models as a cornerstone of safety assurance. However, objects encountered on the road exhibit a long-tailed distribution, with rare or unseen categories posing challenges to a deployed perception model. This necessitates an expensive process of

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Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement

/CVPR2024

Visual program synthesis is a promising approach to exploit the reasoning abilities of large language models for compositional computer vision tasks. Previous work has used few-shot prompting with frozen LLMs to synthesize visual programs. Training an LLM to write better visual programs is an attractive

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Instantaneous Perception of Moving Objects in 3D

/CVPR2024

The perception of 3D motion of surrounding traffic participants is crucial for driving safety. While existing works primarily focus on general large motions, we contend that the instantaneous detection and quantification of subtle motions is equally important as they indicate the nuances in driving behavior

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LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenes

/CVPR2024

Photorealistic simulation plays a crucial role in applications such as autonomous driving, where advances in neural radiance fields (NeRFs) may allow better scalability through the automatic creation of digital 3D assets. However, reconstruction quality suffers on street scenes due to largely collinear

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Generating Enhanced Negatives for Training Language-Based Object Detectors

/CVPR2024

The recent progress in language-based open-vocabulary object detection can be largely attributed to finding better ways of leveraging large-scale data with free-form text annotations. Training such models with a discriminative objective function has proven successful, but requires good positive and negative

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Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport

/ICRA 24, PACIFICO Yokohama, Japan & CVPR2024 Seattle, WA

We aim to address key challenges in long-horizon embodied exploration and navigation by proposing a long-horizon object transport task called Long-HOT and a novel modular framework for temporally extended navigation. Agents in Long-HOT need to efficiently find and pick up target objects that are scattered

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Influential NEC Researchers in the United States Who Helped Shape Modern Computing

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AI Fiber Optic Combo Poised To Improve Telecommunications

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Existing underground fiber-optic telecommunications cable networks that can be accessed through street manholes are helping a team at NEC Labs America improve wireless communications systems and the Internet of Things (IoT). "Hundreds of millions of fiber-optic cables are already there for communications purposes,” says Shaobo Han, a researcher at NEC Labs America who focuses on the design and development of machine learning and signal-processing techniques for real-world sensing applications. “We’re turning it all into a ‘thinking’ device, using the same cable that’s already there.”
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OFC Confererence Recap

NEC Labs America Presentation Highlight from OFC 2023

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Our Time Series Data Research Drives Space Systems Innovation

NEC Labs America’s Time Series Data Research Drives Space Systems Innovation

With decreasing hardware costs and increasing demand for autonomic management, many of today’s physical systems are equipped with an extensive network of sensors, generating a considerable amount of time series data daily. A highly valuable source of information, time series data is used by businesses and governments to measure and analyze change over time in complex systems. Organizations must consolidate, integrate and organize a vast amount of time series data from multiple sources to generate insights and business value.
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Next-Generation Computing Finally Sees Light Blog Post

Next-Generation Computing Finally Sees Light

Moore's law is dead, as we have squeezed all the innovation out of silicon. Fiber optics is the solution to meet the computing needs of tomorrow. Today, we can already use the light traveling inside fiber optic cables as sensors that measure vibrations, sound, temperature, light, and pressure changes. We're now developing the means to take this to the next level with photonic computing at the speed of light to provide faster reaction time, reduce energy consumption and improve battery range
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SystemX New

NEC Labs America Heads to Stanford University’s SystemX Alliance Annual Fall Conference

NEC Labs America’s (NECLA) President Christopher White is attending Stanford University’s SystemX Alliance 2022 Fall Conference this week, where he is meeting with Ph.D. students, industry-leading researchers and business leaders presenting on a wide range of research topics. The annual conference will highlight exciting research in the areas of advanced materials, data analytics, energy and power management, 3D nanoprinting, and photonic and quantum computing, to name but a few!
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Using AI To Safely Put The First Woman On The Moon

Using AI To Safely Put The First Woman On The Moon

We are helping to safely bring the first woman astronaut to the moon as part of NASA - National Aeronautics and Space Administration's Artemis Project with our System Invariant Analysis Technology (SIAT). With Lockheed Martin Space's T-Tauri AI platform, our SIAT analytics engine takes the data from the 150,000 sensors and creates a model incorporating over 22 billion data relationships. The AI model is then analyzed to find any irregularities which could lead to a possible malfunction of any of the spacecraft's systems.
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Our AI Research Contributing to NASA’s Artemis Space Program

By 2024, the spacecraft "Orion" developed by Lockheed Martin will bring humans to the moon in NASA's Artemis program. The system invariant analysis technology, one of NEC's Artificial Intelligence technologies, will perform checks to ensure that the spacecraft is tested and operating properly during the production phase.
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5 Accepted Papers CVPR2022!

Check out our Computervision Papers at #CVPR2022

The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. NEC Laboratories Media Analytics department is excited to be presenting at CVPR 2022, being held in New Orleans, LA from Sunday, June 19 to Friday, June 24, 2022.
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NEC provides AI-based traffic monitoring system with fiber-optic sensing technology for NEXCO CENTRAL

NEC Corporation has deployed an AI-based traffic monitoring system to Central Nippon Expressway Company Limited (NEXCO CENTRAL). The system uses fiber-optic sensing and AI technologies to visualize traffic conditions, such as the location, speed, and direction of travel, from vibrations produced by vehicle movement.
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Our Media Analytics Research

Media Analytics

We solve fundamental challenges in computer vision, with a focus on understanding and interaction in 3D scenes, foundational vision-language models, robust learning across domains and responsible AI. Our technological breakthroughs contribute to socially-relevant solutions that address key enterprise needs in mobility, safety and smart spaces. Our work aims to democratize autonomous driving, develop agentic LLMs that solve user workflows and enable interactive robots, with a commitment to computer vision that promotes privacy, fairness and sustainability. Our award-winning research regularly features at top-tier venues such as CVPR, ICCV, ECCV and NeurIPS.