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Meituan Technology Team
Meituan Technology Team
Apr 15, 2021 · Artificial Intelligence

Meituan Technical Team Shares CVPR 2021 Pre-lecture: Five Papers on Video Instance Segmentation, Facial Expression Recognition, Real-time Semantic Segmentation, Weakly Supervised Semantic Segmentation, and Multi-source Domain Adaptation

At a CVPR 2021 pre‑lecture, Meituan’s Visual Intelligence Center showcased five cutting‑edge papers—VisTR transformer‑based video instance segmentation, a feature‑decomposition facial expression recognizer, an accelerated BiSeNet for real‑time semantic segmentation, an embedded discriminative attention mechanism for weakly supervised segmentation, and a partial‑feature selection framework for multi‑source domain adaptation—highlighting the company’s large AI R&D team, university collaborations, real‑world deployment across its services, and ongoing recruitment.

AICVPR2021Facial Expression Recognition
0 likes · 10 min read
Meituan Technical Team Shares CVPR 2021 Pre-lecture: Five Papers on Video Instance Segmentation, Facial Expression Recognition, Real-time Semantic Segmentation, Weakly Supervised Semantic Segmentation, and Multi-source Domain Adaptation
JD Retail Technology
JD Retail Technology
Mar 15, 2021 · Artificial Intelligence

Two JD Retail Papers Accepted at ICRA 2021: Long‑tailed Facial Expression Recognition and Vanishing‑Point‑Aided LiDAR‑Visual‑Inertial Estimator

JD Retail’s Technology and Data Center announced that two of its papers were accepted at ICRA 2021: one presenting a deep balanced learning approach for long‑tailed facial expression recognition, and the other introducing a vanishing‑point‑aided LiDAR‑visual‑inertial estimator for robust state estimation.

Facial Expression RecognitionLiDARState Estimation
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Two JD Retail Papers Accepted at ICRA 2021: Long‑tailed Facial Expression Recognition and Vanishing‑Point‑Aided LiDAR‑Visual‑Inertial Estimator
UCloud Tech
UCloud Tech
Jul 20, 2017 · Artificial Intelligence

Build a Real-Time Facial Expression Recognition Service with UCloud AI-as-a-Service

This guide walks you through training an Inception‑V3 model on the FER2013 dataset with TensorFlow 1.1, packaging the model, and deploying a scalable facial expression recognition API using UCloud's AI‑as‑a‑Service platform, including performance testing against GPU benchmarks.

AIFacial Expression RecognitionModel Deployment
0 likes · 11 min read
Build a Real-Time Facial Expression Recognition Service with UCloud AI-as-a-Service