BestHub
Sign in
Tagged articles
6 articles
Page 1 of 1
iQIYI Technical Product Team
iQIYI Technical Product Team
Apr 10, 2020 · Big Data

Video Copyright Detection Solution Using SE-ResNeXt and Faiss in the 2019 CCF Big Data & Computational Intelligence Competition

The iQiyi team “都挺好” tackled the 2019 CCF Video Copyright Detection contest by extracting frame‑level features with SE‑ResNeXt, indexing them with Faiss, aligning temporally via a critical‑path method, and refining copy boundaries using SIFT re‑matching and a sliding‑window approach, ultimately achieving an F1 score of 0.9678 after three iterative stages of model selection, cascade detection, and feature fusion.

CCF competitionFAISSSE-ResNeXt
0 likes · 6 min read
Video Copyright Detection Solution Using SE-ResNeXt and Faiss in the 2019 CCF Big Data & Computational Intelligence Competition
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 27, 2020 · Artificial Intelligence

Beihang Team's Video Copyright Detection Solution: Frame Sampling, Feature Extraction, and Retrieval Matching

The Beihang University team’s video copyright detection solution samples frames every 200 ms, extracts 512‑dimensional ResNet‑18 features, and uses handcrafted cosine‑similarity matching to identify source videos and plagiarized segments, all while operating on limited hardware without training any models.

algorithm designfeature extractionframe sampling
0 likes · 12 min read
Beihang Team's Video Copyright Detection Solution: Frame Sampling, Feature Extraction, and Retrieval Matching
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 20, 2020 · Artificial Intelligence

Video Copyright Detection Algorithm: Competition Solution Overview

The Hulu Brothers’ competition solution tackles large‑scale video copyright detection by extracting I‑frames, encoding them with ResNet‑18 CNN features, performing approximate nearest‑neighbor search and ORB re‑ranking to match queries to reference videos, then linearly interpolating frame correspondences for precise temporal alignment, achieving high precision, recall and F1 scores.

CNN featuresCompetition Solutionframe extraction
0 likes · 15 min read
Video Copyright Detection Algorithm: Competition Solution Overview
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 13, 2020 · Artificial Intelligence

How to Detect Video Copyright Infringement with Two‑Stage Frame Matching

This article details a two‑stage video copyright detection pipeline that builds a frame‑level feature library, uses Hessian‑Affine + SIFT and Fisher Vectors for robust feature extraction, applies weighted bipartite graph matching and longest increasing subsequence localization, and achieves an F1‑score of 0.9086 on the CCF 2019 competition dataset.

AIfeature extractionframe matching
0 likes · 14 min read
How to Detect Video Copyright Infringement with Two‑Stage Frame Matching
iQIYI Technical Product Team
iQIYI Technical Product Team
Feb 21, 2020 · Artificial Intelligence

Top-1 Solution for the 2019 CCF Big Data & Computing Intelligence Competition: Video Copyright Detection

The Hengyang Data team won the 2019 CCF Big Data & Computing Intelligence video‑copyright detection contest by extracting VGG16‑based image features with Gaussian‑R‑MAC weighting, using a graph‑based NSG nearest‑neighbor search and a frame‑matching algorithm to locate infringing segments within three‑second precision, even under severe cropping and other transformations.

CCF competitionVGG16approximate nearest neighbor
0 likes · 9 min read
Top-1 Solution for the 2019 CCF Big Data & Computing Intelligence Competition: Video Copyright Detection