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Tencent Advertising Technology
Tencent Advertising Technology
Jun 22, 2021 · Artificial Intelligence

Technical Insights and Solution Strategies from the Tencent Advertising Algorithm Competition – Video Ad Track

The article outlines the Tencent Advertising Algorithm Competition’s video ad challenge, details the paper submission guidelines, and shares a participant’s step‑by‑step technical approach—including baseline experiments, model re‑implementation with Paddle, multimodal feature extraction, optimizer choices, and future improvement directions—providing practical AI insights for multimedia video classification.

Feature ExtractionTencent competitiondeep learning
0 likes · 7 min read
Technical Insights and Solution Strategies from the Tencent Advertising Algorithm Competition – Video Ad Track
DataFunTalk
DataFunTalk
May 22, 2021 · Artificial Intelligence

Baidu's Video Foundation Technology Architecture and Key AI Techniques

This article presents an overview of Baidu's video foundation technology architecture, covering the video R&D platform, core AI techniques for video understanding, editing, surveillance, and general vision, and detailing innovations such as Attention‑Cluster networks, cross‑modality attention with graph convolution, GANs, super‑resolution, and adaptive encoding.

Adaptive EncodingGANSuper-Resolution
0 likes · 14 min read
Baidu's Video Foundation Technology Architecture and Key AI Techniques
Amap Tech
Amap Tech
Feb 1, 2021 · Artificial Intelligence

AMAP-TECH Algorithm Competition: Dynamic Road Condition Analysis Using In-Vehicle Video

The AMAP‑TECH competition challenged participants to infer real‑time road conditions from in‑vehicle video, prompting the authors to combine lane‑wise vehicle detection with LightGBM and later an end‑to‑end DenseNet‑GRU model, augment data, ensemble five networks, and achieve a 0.7237 F1 score while outlining future deployment and research directions.

computer visiondeep learningfeature engineering
0 likes · 15 min read
AMAP-TECH Algorithm Competition: Dynamic Road Condition Analysis Using In-Vehicle Video
Amap Tech
Amap Tech
Jan 22, 2021 · Artificial Intelligence

Dynamic Road Condition Analysis Using EfficientNet and ConvLSTM: Solution to the AMAP‑TECH Algorithm Competition

The winning solution for the AMAP‑TECH competition combines EfficientNet spatial features with ConvLSTM temporal modeling, adds a mask‑prediction branch for closed‑road obstacles, and mitigates severe class imbalance through a two‑stage decoupled training pipeline, achieving first place on leaderboard A and top‑5 on leaderboard B without ensembling.

AI competitionConvLSTMEfficientNet
0 likes · 7 min read
Dynamic Road Condition Analysis Using EfficientNet and ConvLSTM: Solution to the AMAP‑TECH Algorithm Competition
Youku Technology
Youku Technology
Apr 16, 2020 · Artificial Intelligence

Multimodal Video Classification: Image Feature Improvements and System Insights

The talk presents Alibaba’s hierarchical video‑category system and a multimodal classification pipeline—leveraging EfficientNet, NeXtVLAD fusion, attention‑dropping augmentation, and MoCo contrastive learning—that together boost cold‑start recall by 43%, improve program classification over 20%, and set the stage for larger models and advanced unsupervised methods.

AIEfficientNetfeature engineering
0 likes · 17 min read
Multimodal Video Classification: Image Feature Improvements and System Insights
DataFunTalk
DataFunTalk
Mar 30, 2020 · Artificial Intelligence

Enhancing Multimodal Video Classification with Improved Image Features and Category System

This article presents a comprehensive overview of Alibaba Entertainment's category system and multimodal video classification algorithm, detailing the construction of a high‑accuracy hierarchical taxonomy, improvements to image feature extraction using EfficientNet and data augmentation, unsupervised training techniques, experimental results, practical pitfalls, and future research directions.

AIcategory systemimage features
0 likes · 17 min read
Enhancing Multimodal Video Classification with Improved Image Features and Category System
iQIYI Technical Product Team
iQIYI Technical Product Team
Feb 21, 2019 · Artificial Intelligence

Multimodal Soft‑Porn Detection for Short Videos: Models, Challenges, and Lessons Learned

The article describes iQIYI's multimodal soft‑porn detection system for short videos, covering challenges like subjective definitions and class imbalance, and detailing text (Convolutional Bi‑LSTM), image (Xception‑CBAM), video (NeXtVLAD) models, integration strategies, key takeaways, and future improvements.

AIcontent moderationdeep learning
0 likes · 15 min read
Multimodal Soft‑Porn Detection for Short Videos: Models, Challenges, and Lessons Learned