LPR4M: A Large-Scale Multimodal Livestreaming Product Recognition Dataset and the RICE Cross‑View Semantic Alignment Model

This paper introduces LPR4M, a 4‑million‑pair multimodal dataset for livestreaming product recognition, and proposes the RICE model that combines instance‑level contrastive learning with patch‑level cross‑view semantic alignment, demonstrating state‑of‑the‑art performance on both LPR4M and MovingFashion benchmarks.

Deep Learningcross-view alignmentlivestreaming

0 likes · 19 min read

LPR4M: A Large-Scale Multimodal Livestreaming Product Recognition Dataset and the RICE Cross‑View Semantic Alignment Model

Baidu Geek Talk

Apr 13, 2022 · Artificial Intelligence

Smart Retail Product Recognition Solution Using PaddlePaddle PP-ShiTu

The article presents PaddlePaddle’s PP‑ShiTu‑based smart retail product recognition solution, detailing a complete pipeline—from data preparation and model optimization to low‑latency deployment—that overcomes high‑similarity packaging, rapid SKU changes, and costly retraining, achieving over 98 % Top‑1 recall with 0.2‑second CPU inference.

AI deploymentImage ClassificationPP-ShiTu

0 likes · 7 min read

Smart Retail Product Recognition Solution Using PaddlePaddle PP-ShiTu

Suning Technology

Oct 15, 2020 · Artificial Intelligence

How AI Powers Offline Product Recognition in Smart Retail Stores

This lecture details the evolution of product recognition algorithms from traditional image classification to deep‑learning‑based object detection, discusses challenges in dense retail scenes, presents solutions like rotated bounding boxes and multi‑source sensor fusion, and explains practical deployment in digital and unmanned stores.

Deep Learningdense sceneobject detection

0 likes · 18 min read

How AI Powers Offline Product Recognition in Smart Retail Stores