Copy Detection

20 papers with code • 1 benchmarks • 2 datasets

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Use these libraries to find Copy Detection models and implementations

Most implemented papers

Emerging Properties in Self-Supervised Vision Transformers

facebookresearch/dino ICCV 2021

In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets).

Contrastive Learning with Large Memory Bank and Negative Embedding Subtraction for Accurate Copy Detection

lyakaap/isc21-descriptor-track-1st 8 Dec 2021

Copy detection, which is a task to determine whether an image is a modified copy of any image in a database, is an unsolved problem.

Feature-compatible Progressive Learning for Video Copy Detection

wangwenhao0716/vsc-descriptortrack-submission 20 Apr 2023

Video Copy Detection (VCD) has been developed to identify instances of unauthorized or duplicated video content.

Video Re-localization

fengyang0317/video_reloc ECCV 2018

We first exploit and reorganize the videos in ActivityNet to form a new dataset for video re-localization research, which consists of about 10, 000 videos of diverse visual appearances associated with localized boundary information.

The 2021 Image Similarity Dataset and Challenge

facebookresearch/isc2021 17 Jun 2021

This benchmark is used for the Image Similarity Challenge at NeurIPS'21 (ISC2021).

Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?

romaroman/cdp-ml-fakes 5 Oct 2021

Nowadays, the modern economy critically requires reliable yet cheap protection solutions against product counterfeiting for the mass market.

D$^2$LV: A Data-Driven and Local-Verification Approach for Image Copy Detection

wangwenhao0716/isc-track1-submission 13 Nov 2021

In this paper, a data-driven and local-verification (D$^2$LV) approach is proposed to compete for Image Similarity Challenge: Matching Track at NeurIPS'21.

Bag of Tricks and A Strong baseline for Image Copy Detection

wangwenhao0716/isc-track2-submission 13 Nov 2021

In this paper, a bag of tricks and a strong baseline are proposed for image copy detection.

Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision

facebookresearch/vissl 16 Feb 2022

Discriminative self-supervised learning allows training models on any random group of internet images, and possibly recover salient information that helps differentiate between the images.