Copy Detection
21 papers with code • 1 benchmarks • 2 datasets
Libraries
Use these libraries to find Copy Detection models and implementationsLatest papers
VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models
In this paper, we introduce VidProM, the first large-scale dataset comprising 1. 67 million unique text-to-video prompts from real users.
PW-Self: Patch-Wise Self-Supervised Visual Representation Learning
To this end, we present a simple yet effective patch-matching algorithm that can find the corresponding patches across the augmented views.
Representation Learning via Consistent Assignment of Views over Random Partitions
We extensively ablate our method and demonstrate that our proposed random partition pretext task improves the quality of the learned representations by devising multiple random classification tasks.
The 2023 Video Similarity Dataset and Challenge
The problem comprises two distinct but related tasks: determining whether a query video shares content with a reference video ("detection"), and additionally temporally localizing the shared content within each video ("localization").
A Similarity Alignment Model for Video Copy Segment Matching
We propose a Similarity Alignment Model(SAM) for video copy segment matching.
A Dual-level Detection Method for Video Copy Detection
With the development of multimedia technology, Video Copy Detection has been a crucial problem for social media platforms.
3rd Place Solution to Meta AI Video Similarity Challenge
This paper presents our 3rd place solution in both Descriptor Track and Matching Track of the Meta AI Video Similarity Challenge (VSC2022), a competition aimed at detecting video copies.
Feature-compatible Progressive Learning for Video Copy Detection
Video Copy Detection (VCD) has been developed to identify instances of unauthorized or duplicated video content.
Active Image Indexing
First, a neural network maps an image to a vector representation, that is relatively robust to various transformations of the image.
A Benchmark and Asymmetrical-Similarity Learning for Practical Image Copy Detection
Moreover, this paper further reveals a unique difficulty for solving the hard negative problem in ICD, i. e., there is a fundamental conflict between current metric learning and ICD.